Leading AI, Delivering Transformation, and Building Community with Areti Iles [MVP]

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Hello everyone and welcome back to the M365FM podcast.

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Today's guest is someone who has built an incredible reputation across both the Microsoft

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community and enterprise technology landscape.

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With over 15 years in technology sector, she is currently the head of professional services

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with Telephonica, takes AI business solutions division and Microsoft MVP in customer experience

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and power apps.

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Through her career, she delivered complex dynamic 365 and power platform solution to major

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FTSE's organizations while also becoming one of the most recognizable community leaders

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in Europe.

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She serves on Microsoft Global User Group Committee, responding, representing Europe,

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both the real thing and the London All Day Dynamics 365 and Power Platform User Group helps

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organize the Scottish Submit course of the Power Delivery podcast, Medvo with the Women

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in Power Platform and even, yeah, animal as a part of the UK delegation of the United

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Nation Commission on the status of women.

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On top of all the CVK respected boys on an eye-lead organization, compliance, governance and

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responsible adoption, I'd be welcome to the show.

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Thank you for having me, it's great to be here.

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Yeah, I hope I have forgotten anything.

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Oh, God, I don't know maybe, but yes, I don't say no to anything if anyone has a guest

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from that list and thank you for that lovely intro.

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Yeah, I'm involved in a lot of things, but I love it.

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It keeps me busy.

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Yeah, for those who know the MVP speaker and community leader, Virgin Avarti, tell us about

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the person before all that, how did your journey and technology begin?

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Yeah, so it happens to me in the way that it does for most people I find when I ask them

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about their stories and how they can involve the Microsoft platform.

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It's a case of doing a job and then somehow interacting with the software and realizing

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you quite like it and want to get more involved.

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That was definitely the case for me.

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So I was working, having finished my degree in my master's, I went into a job into IT support

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and I was working for a facilities management company in the UK, which is where I'm based.

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And as part of a change in the business and acquiring a new business to bring into our

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current portfolio businesses in the facilities management company, they were looking to

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introduce a CRM system and we chose Dynamics 365, well, the Uniseer as it was at the time

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to implement it.

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And I worked with a Microsoft partner at the time as the product owner effectively to create

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that solution with them and test it and do the data migration and do the go live and

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eventually support it.

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And as part of that process, I just really enjoyed creating the IT system and I got really

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heavily involved in the partner in the consultants I was working with joke that, you know, I should

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do this because I was really good and I was getting it and I was really enjoying it.

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And I didn't really do anything about it at the time.

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I was very much enjoying where I was.

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But over the years, then I moved on to other organizations as a Dynamics CRM manager, systems

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manager, I was a SharePoint manager at one point as well.

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And I just expanded what I was doing with the system, I worked with other Microsoft partners

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as the client and eventually I got to the point where I knew enough that I felt I could actually

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come in as a consultant.

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And that's what I did.

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I joined the Microsoft partner in the UK, became a consultant and then eventually I was a

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principal consultant and a solution architect.

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And as time went on, so this was in over about 15 plus years, as you said, in your intro,

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I eventually then decided to move on to be a delivery lead, which is what I am now for

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telephone protect.

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So yeah, it was very much just a gradual process over many, many years, but it all started

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with just getting that exposure to the software and really liking the way it worked and the

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functionality it had and how you could use it.

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Okay, awesome.

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You know, the professional service teams was leadership always an ambition or did that evolve

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naturally as your career processed?

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It wasn't something I was aiming for necessarily.

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I always saw myself as part of a delivery team on projects.

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I didn't ever see myself moving a level above that and overseeing it rather than doing the

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actual build, but I got to a point where I had the opportunity internally due to the Microsoft

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partner was working for being acquired by another bigger partner.

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I had the opportunity to go for a head of delivery role and I thought that it would be silly of

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me not to go for it.

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I very much owe being in the leadership position now to encouragement though from other people

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because when I saw the job description, I felt like maybe I didn't have enough experience

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to be a delivery lead, having led delivery teams in projects.

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I thought maybe I was missing kind of key people management leadership skills.

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I didn't know if I had enough experience in terms of commercial awareness, managing pre-sales,

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customer relationships, I wasn't sure if I had that much of the commercial experience around

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it to be able to be a head of delivery.

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I almost talked to myself out of it and I had someone in the business that I reached out

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and said, "I don't think I should actually go and interview for this because I don't

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think, you know, this and this and this and this thing, I don't have an experience in

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at all and if you're looking for that, then I don't want to waste their time."

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She said to me, "Don't even worry about it.

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Just talk about the things you do now."

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Sure enough, I got the role which I was very excited and relieved by because I wasn't

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really sure I was going to get it because of those reasons.

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Yeah, any of the end it didn't really matter because I learned those things in my job and

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the fact that I have a technical background helps me support the delivery teams a lot better

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as well.

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And I can also poke my little head into their meetings and go, "What are you building?

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What's going on?

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How are you making this?"

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And we can still have geeky conversations about it which is really nice.

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Amazing.

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Yeah, great career.

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But you are widely recognized for your expertise across Dynamics, 365 Customer Engagement,

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ERP and Power Platform.

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What was it about Microsoft Business Applications ecosystem that really captured your attention?

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So initially it was the fact that it was fairly straightforward and easy to use as an

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end user when I was an end user, but also it was very easy to configure in the background

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and it was, it's a very logical system and most kind of software is.

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So for me it was, I really liked the fact that it was easy and straightforward to use and

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you can understand what you were looking at and you could see how things were linked together,

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but then also in the background it was very easy to customize things.

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Back when I started, we didn't, you know, Power Platform didn't exist, which is unthinkable

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now, but back then it was a simpler in a way life.

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There was no A&M, there was no pipelines, it was just the case of manual deployments,

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you know, and solution packages and things like that.

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So it has, the role has changed a lot, but for me I really enjoyed how easy it was

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to understand how the solution worked in the background.

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And I didn't come from a technical background at the time.

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My, my education wasn't really in software development or anything like that at all.

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So for me I just really liked the fact that it was, if you followed it through and you

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read through the documentation, you were actually able to pick it up fairly quickly and

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getting that experience and being able to create things and change things and develop

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a system that was used by people and it made the difference to them having a system that

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they were able to use and made their work life better.

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That was the thing for me that I really liked.

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When Power Platform came along and kind of dataverse to begin with, that just changed

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it and it made it a lot more useful in terms of having more than one part of the business

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using a Microsoft solution or Microsoft tool.

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So you started seeing these economies of scale between departments and the integration between

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the different types of the stack and then obviously the Power Platform itself came along,

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admin centers came along that linked it all together and now you can actually have multiple

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first-party apps and multiple solutions, but you can also have things in Azure for governance,

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you know, for you defend foundry now.

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It's all developing and it's all changing and that was a nice thing for me as well.

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It's nice to know something inside out and definitely in the time when I started it was,

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you could say, I know CRM, I know what's in the CRM system in terms of functionality and

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how it works.

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Now it's very, very difficult to say that you know everything in the stack.

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It's impossible so you have to pick one area and even then it's developing so, so quickly

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now that your knowledge is out of date very, very quickly.

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So it's, and this wasn't the case when I first started but it definitely is now.

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So for me, the fact that it's changing, it's developing, new features are coming out all

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the time, things are changing all the time.

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It's great, don't get me wrong, it's also very difficult to, to, to, to be like, I just

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went through this and I thought I knew everything and I do know and it's, but it's really nice

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and this is where the community comes in as well.

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Everyone getting together from different points of view, different product stacks and

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actually, you know, the best conversations I have had in the community are with other

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MVPs or other people in the community that represent different parts of the stack and

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discussing the challenges that we may have in, in C and the challenges they may have in

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Azure or the challenges they have from a security perspective or from a compliance perspective.

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And that's all very interesting and they are part of it for me was more recent.

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So when I became head of delivery, I started delivering also ERP projects and that was

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something I needed to upskill on because I hadn't spent much time on the ERP space and that

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was a very interesting learning curve for me as well because the ERP projects, although

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some parts of the stack are shared, both as project delivery is different to see projects

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but also the way they, they work and the functionality within D3.5, F and O, F and C and

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however you want to, whatever you want to call it, it's all really different and it's

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a different part of the business obviously that uses them that has different challenges

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altogether to the operational teams.

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So all of that was very interesting for me as well.

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It really has become a huge stack now and it's very, very difficult to know, know it all.

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I think it's more accurate to say, I know people that know parts of the stack.

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So if I have a question about an area I don't know, I will know a person that knows about

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it and I can probably go and ask a question and I think that's the great thing about the

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community.

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Yeah, that's a little bit deep dive in and projects.

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You worked on a lot of projects ranging from relative straight forward implementations

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to I think in Telephonicar, it's a thing that's hugely complex enterprise transformation.

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What separates successful projects from unsuccessful ones?

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Yeah, there is definitely quite a few things and it depends sometimes on the project.

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There will be different challenges I think is sometimes for your P projects versus C projects

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for example or more recently a GNI projects.

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I think it's fair to say that there is some kind of key things that happen between successful

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and unsuccessful projects and a lot of the time a project won't fail because of the technology

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it will fail because of the people.

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You could have the most brilliantly technologically speaking built system.

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And if the people that are supposed to use it don't then that investment in the technology

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will have come to nothing.

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And a lot of the time we may think of the end position of a project being the goal live

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but really from an organization's point putting a system live is only the beginning for them

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because the value has to come after that point and the benefits has to come after that

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point.

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Getting to the goal lives great but that's only the beginning.

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I think a lot of organizations sometimes underestimate the amount of time that is needed

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by their SMEs to work on a project to make it successful from a technical perspective.

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So people will have their day jobs in that organization.

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They will then be asked to fulfill a project role like there might be a product owner or

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there might be testing or they may need to do UAT or there might be a super user.

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And a lot of effort has to go into both the discovery sessions so telling the consultants

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what they need, how they needed getting the user stories written, the acceptance criteria,

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the test scripts that they need to create data migration checks.

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There is a lot of effort that is needed from the organization before they can go live.

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And I've seen situations where projects have not been successful because that time couldn't

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be given or those people had to rush through things.

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And then you could end up with a system where it would go live but because processes had

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not been tested then to end, you had issues that go live.

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It could be the case that there wasn't much support in terms of super users or training

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internally by the organization.

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So people had a difficult experience to begin with with the software learning how to use

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it and getting frustrated because of that or missing kind of key information or the system

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itself in some cases not being as simple as it could be having kind of all complicated

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processes that need to over complicated systems that affect the adoption.

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It really depends on how you define a successful project to be honest because different parts

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of the project teams will define it differently.

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From a much of partners perspective you may consider a project successful if it's gone live,

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the customers happy and hypergames finished.

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But from a client's perspective the project will only be considered successful if it meets

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the KPIs and the metrics that they want to see out of it perhaps it could be how long the

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sales process might take for salespeople to complete before the system was put in place

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or in terms of you know, if you're doing edge edge edge edge AI for example, how much more

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productive is the team, what benefits are they getting from using edge edge AI, have they

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defined that before they started, a lot of the time with a genetic AI some people will start

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with the solution not the problem.

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So you know AI is the answer, what is the question and a lot of the time these kind of pilots

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AI pilots can be unsuccessful because the AI is being introduced but there is no problem

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being solved.

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It's more of an experiment than an actual project with aims and objectives.

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So it is really a case of having a look at what you are trying to achieve by doing this

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project whether it's the ERP power platform, a genetic AI, it doesn't really matter and

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really identifying exactly what you are what you are aiming for and who it is for is it

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the project for a team, is it the whole organization, is it the case of depending on other systems,

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how complicated is it going to be, who is going to own it once it's live as well, sometimes

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I see projects fail because of lack of ownership internally and in some cases as a set of engineering

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and that is a, that can be a real problem and sometimes the cost, the ongoing cost of

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having that solution live particularly now with a genetic AI solutions isn't really considered

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so you can get a bit of regret as an organization for putting something in place that then is

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very costly as time goes on.

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And yeah, particularly now with the genetic solutions and tokens and the cost of that it can

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be a bit unpredictable so and of course the licenses are changing all the time as we know

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in the structure of them and what isn't included in the license and all of that stuff so it's

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yeah it really depends on how you define success and from whose point of view you look at

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it but I would say these are the things, the areas I should say that will make or break

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the project from my experience across them.

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Awesome, yeah that's really good.

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I think, I have seen you are a course of the Power Delivery Podcast which often focus on

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implementation best in practice.

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What are some of the recurrent themes you see when projects begin to struggle?

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I think projects begin to struggle sometimes when there is a lack of time for resumes they

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there can be kind of a slow, slow progress or progress that has been quick before kind

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of slows down a bit and there isn't that much that can be progressed and signed off and

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your goal lives lips basically.

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That is one way that you can have a problem in a project.

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Another one could be scope control, scope creep.

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If you're not controlling the requests from the business sometimes you can start wanting

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to have an MVP and then a lot of different organizations and sorry, a lot of different departments

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in an organization can want different things and they might come with a you know bucket list

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of things that they would like for the system to do and you try to create a lot of functionality

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that then makes the project run very long and also it takes takes a lot more time to

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to put all that together and tested and so on.

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It creates additional complexity when in some cases don't give me wrong complexity sometimes

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is needed if you go complex processes but what I see a lot is that there is a lot of requirements

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that are marked as MVP must have on day one when actually the organization will be better

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off to have those on the face too and actually have a system that is very simple to begin

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with so to speak that can get embedded people can start using it they can give that

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me show feedback and then build on it and keep working and iterating through development

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cycles and giving additional functionality as they go on because the longer you leave it

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to give a solution to the end users that will be using it the more likely it is that

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it won't meet the requirements of those users and if you don't give them visibility early

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on as you're building that solution as well so that they can give you their feedback and

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they can tell you what isn't going to work for them.

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I think that's where you can get into trouble as well there's nothing worse I think than

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having a development team going into a dark room for weeks or months and then coming out

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with something that hasn't had any of the end users give or SMEs give feedback to it

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at all because sometimes people will tell you what they want and actually what they want

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is something completely different and you want to know that and they want to know that until

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they see and play with something in front of them and go actually you know what I know I

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told you I wanted this but actually what would really be good is that and if you don't

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get that feedback you miss out on that information but also you miss out on their engagement with

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the project and them feeling like this is a real thing that is that they have an invested

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interest in that they have helped happen if you leave them at arms length until the

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goal I for the end user training they won't feel like they've been part of creating the

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system and therefore they will be less likely to to feel invested in using it and adopting

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it and making it a success and change management is a is a great thing that makes or break

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makes a project or breaks a project if it's not thought about from the very beginning

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you have to think about the goal live and the adoption of the system from the moment

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you start a project if not before and figure out how are you going to engage the people

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that are going to drive the project forward and who are those people that are going to

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be owning that system and driving its adoption because that's where your benefit is going

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to come from not from having a successful project implementation and I think a lot of

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the time there isn't much consideration given to that or people are in roles that are

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very they don't have the bandwidth in their role to to put the right time in an effort to

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to make these things happen because it does take a lot of time and it does take a lot of

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effort the organizations that have done that well tend to in some cases backfill people

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to allow them to have that space to drive this forward until the project is finished

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and the adoption has happened and a lot of time has passed since the goal live that

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it has been embedded in and implemented and that kind of high level of support needed at

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the beginning after goal live isn't there anymore but not every organization can afford

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to do this honestly so it's always a case of a juggling act I think and yeah it's not

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always easy to do many projects fail and there's you know we could have a new episode just

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talking about why projects fail I think and we definitely doing our broadcast as well

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on the part delivery broadcast we talk a lot about changes that are happening in the

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stack what what they mean and what you need to look out for and and the things that you need

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to consider because we try to help people avoid those pitfalls of things that can go wrong

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if people don't think about it and you know particularly with a gender AI you've got

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different ways that you could achieve the same result so it's a case of actually thinking

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about what the best of root to solve your problem is as well so as time goes on I think

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it gets more complicated this is awesome and there was one one thing I think a lot of companies

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use change management as best work and and you have both perspective so you come from

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the technic at the now you're leading the professional service team how has your definition

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of change management change over this from this post perspective yeah I think I've I've

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become much more aware of the conversations being had that executive and senior level around

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the project so I've before when when I was not head of delivery and I wasn't part of those

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conversations taking place because traditionally delivery teams will focus on the day to day as

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you would expect delivery of the project but they wouldn't look at the strategic direction

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of that project or have conversations with the executives of the of the organization the

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project is being done done with necessarily now that I get to see that side of it I'm much

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more aware of the challenges that the organizations have when looking to use Microsoft technology

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that I didn't before before I had a different level of understanding in terms of the day to

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day the system managers the the obviously the end users themselves but I didn't really

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know from a a KPI's a return on investment perspective that didn't necessarily come

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into those conversations it was more focused around how can we create a system that meets

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the requirements fully and meets the acceptance criteria and works well and efficiently and

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the the IT team or the business teams that were going to support it have they got enough

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knowledge and experience and understand the system well enough have we done the right

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handover for them to be self reliant after we're gone that was more my focus when I was part

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of a delivery team and when I was managing the consultants that I was working with to build

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those solutions that was where we we focused and that's where we probably should have focused

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as well. But being ahead of delivery now I have those conversations around we're investing

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this much in putting this system in what benefits are we going to get how are we going

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to make sure that we have the right solution in place what do we do after it's been put

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in place how do we manage upgrades how do we manage new functionality what can we do

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in terms of agent KIOs they coming into it now how are we going to use AI in our

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existing systems how do we need to change our processes how do we need to change the

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organization what we do and who does what how do we bring agents into our workflows who

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owns them what does that mean so there's a lot broader conversations that I'm part of now

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that I wasn't at before and it's a lot more of a strategic view and long term view on

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the technology than a shorter term view than I had before and and that's what makes it

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interesting for me as well like and I know technically what is available and it's about then having

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conversations about what that means for the humans using that technology and what that means for

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organizations long term implementing that technology so I look at it from a different perspective now

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and it's really it's it's a great I feel privileged to be in that position to be able to have those

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conversations with senior level executives and understand their challenges and how we can help

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in what we do so I think it gives you a lot of a better perspective of the impact the projects have

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more outside of the immediate people using it it allows you to see the organizational impact as

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well which is great awesome I think a little about agent KIO a lot of people especially on linked

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in every time I think nearly I don't know a lot of posts are about a genetic AI but for listener who

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hear the term yeah we hear the term frequently but aren't actually sure what it means how would you

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explain a genetic AI well that's that is a very good question so in terms of the the Microsoft stack

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itself there's a number of different AI solutions it's really when it comes to gender KIO it's not

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really one thing it's a group of AI systems that have agency which is why we call them agentic it means

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that they can autonomously make decisions take actions to achieve a goal and they're not simply

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responding to a prompt they are actually autonomously doing something they have that agency it's a it's

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really a case of having if you think if we think about the things that we've discussed so far

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part platform dynamism is six five first parts the app c systems the Rp systems they themselves are

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not agentic because the human has to make decisions so they are they are not acting autonomously

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effectively where you have a genetic AI is where you've got an agent or a solution that is acting

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autonomously to achieve an outcome and it's not just producing outputs and historically with

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produced with with use systems as humans to produce outputs so it's it's a case of moving

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beyond just providing answers to executing tasks and executing workflows and working independently

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with minimal human input so it really from a a definition perspective at the high level that's

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what i would say there's also different types of agentic AI so agentic AI itself is a bit of a

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category so it is all based on you know planning and executing actions but then you have generative

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AI you've got co-pilot style assistance they're also considered AI but the agentic part of it is

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particularly that automation which we're seeing a lot of organizations looking to to use right now

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what's exciting especially when we think about Microsoft yeah are they having up with agents

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i think it's the way our role is changing when it comes to interacting with technology i think

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this is the main thing for me because traditionally it's a case of getting an answer from a system

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whereas now it's a it's a case of having agents say i will solve the problem for you

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and it's not deterministic anymore so we can't really test agentic solutions the way we would test

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first-party apps because we can't really predict what they're going to say or how they're going to

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say it now this is changing a bit with creating for example agent evaluations or e-bunnels and things

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like that where we're making it a lot more stringent as to trying to create some guidelines as to

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how they will behave but it's very much involving technology at the moment and for me i think it's a

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it's a case of knowing that we are we are no longer central to the use of technology it used to be

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that the human being was central in the way technology was used but now we are in the periphery we

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are not in the center anymore we are brought into a system or we will be once we get fully autonomous

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agentic solutions out there we will be coming in by exception and i i truly believe that we will

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get to the point and in some cases some organizations are already at that point those that are very very

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much as marxas says in the frontier so i think i think it's a it's a very much a learning curve but at

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the same time we need to pace ourselves and of course you know you've got things like quantum AI

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that's gonna come along and change things for us again so this is only the beginning of a very

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long road yeah i think a lot of organizations are rushing to deploy i actually what questions show the

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leaders be asking for the start why are we doing this and what i and what i mean by that is

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we shouldn't we shouldn't just be jumping on the bandwagon of the latest technology and

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doing it purely because we feel like we there's a competitive advantage out there that we are going

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to lose if if we don't jump on although that is technically speaking true because if our competitors

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are looking to use the AI to become more efficient or quicker in responding or providing a better

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customer experience however you want to you want to define your competitive advantage in your

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in your industry or in your organization i think it's important to know that organizations have

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existed for many many many decades years you know since commerce began and your business strategy

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can't be an AI strategy and what i mean by that is the reason your organization exists and what

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you're trying to do in the world should be the same before and after AI because at the end of the day

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AI is just the latest technological tool we can use to achieve that strategy it's not a strategy in

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itself so i always get a little bit uneasy when organizations say you know our strategies to use a

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AI to become the best in next one said and thinking well okay great but what is what do you exist as

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an organization how is AI going to help you continue to be the best in what you can do so you

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definitely see a difference between new companies and older more established companies in terms of

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how they approach the technology and as i said it is going to change it's it's a case of identifying

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also what that means for us as organizations we are changing what it means to be a in certain role

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job role here whatever our job role is right now so at the moment i might for example if i take

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myself as an example as a head of delivery i might be doing my job and i have a job description

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that doesn't include being the manager of agents but i am sure at some point our job descriptions will

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start to change to to say that the head of delivery manages x, y and z and and these responsible for

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x, y and z in the organization and those are also responsible as the owner of the

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you know time should approve all this agent and the and the resource scheduling agent and

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that we will actually have job roles that are a combination of a human being and agents the job

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description will involve both and i and i think that that changes what we do at work what it means to

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be any any job type any job description will change i think our processes will change

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and we will become this hybrid way of living and working and then potentially more

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forgetting to something different so yeah it's for me it's very interesting to see how we make

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that transition and how far do we go with trusting because at the end of the day i think it really

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does come down to trust how far do we trust these the the agency that we will give these these tools

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and also unfortunately where my things go wrong because we love to think of these things as things

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that will only be used for good but there is absolutely people out there groups whatever you

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want to call them that we'll be looking to use these not for good but as a weapon and it's a case of

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being very vigilant to that and and finding ways to use the tools that we've got in a responsible

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secure way and i think that's where the challenge is going to be even more so as time goes on and we

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start providing this agency to very critical critical systems and even you know having a purchasing

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agent that that buys things for us you know that could go very wrong so i think it's going to be very

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interesting to see how we how we as both create the infrastructure but also create the levels of

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security needed to be able to use these things without risk awesome i i like a little bit speak

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about the trust topic and i think one error where you become particularly well known is AI

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governance and compliance and yeah many organizations are enthusiastic about AI but nervous about

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regulatory landscape how would you describe the current state of AI legislation globally

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chaos so we've got there is a there is a lot of a lot of focus at the moment on first of all creating

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guardrails for AI use and that is because initially when AI solutions started being made available

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there was a question of do we need to regulate AI or not we've very much moved past that now

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it's really a question of how far do we need to regulate it without stifling innovation

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and allowing the the benefits to be realized without actually making it so controlled that we're not

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actually allowing the benefits to to to be seen so a lot of different countries will have different

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approaches to this there's there's over seven three countries in the world that have some level

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of legislation or regulations in place or guidance but it really varies and in the EU we have we're

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very much in a better situation of having the UAE act very much a legal law that that governs

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how AI is is to be developed and used within the EU but it only applies within the EU and it is

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a very much a good good basis on which I think other legislation will be brought out but if if you

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look at the US for example there is no federal law there's over a thousand state bills every state

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does its own thing there is lots of conflicts and there is that question around how do we actually get

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to get get to a point where this is a little bit more straightforward in terms of at federal level

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so it's it's a lot more difficult when you look at it from a US perspective and then you've got

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things in between so in the UK for example we do not have a law but we do have sector-specific

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regulations so it really depends on which sector you're in and what regulations you've got but then

422
00:36:52,480 --> 00:36:58,800
if you're dealing with any part of the EU or your users are in you located then the EUAA act applies

423
00:36:58,800 --> 00:37:03,600
anyway because it's extraterritorial so there's all sorts of things that need to be considered

424
00:37:03,600 --> 00:37:11,120
there is really differences at the moment across the board but I think as time goes on more and more

425
00:37:11,120 --> 00:37:17,440
legislation will be introduced and more and more regulations will be introduced the good news is that

426
00:37:17,440 --> 00:37:24,320
there are some standards that are being globally recognized things like the the NIST AI

427
00:37:24,320 --> 00:37:28,880
risk management framework that came from the US very much considered a global standard for

428
00:37:28,880 --> 00:37:33,920
for doing AI risk management well there's ISO standards on AI management systems that are

429
00:37:33,920 --> 00:37:41,200
certifiable as well and and also on risk management so there's there's a lot of guidance there on how to

430
00:37:41,200 --> 00:37:46,480
how to implement regulations and legislation well and I think we're going to see a lot more of that

431
00:37:46,480 --> 00:37:56,320
as time goes on yeah I think a little bit of a hot topic is the EUAA act I think it generates significant

432
00:37:56,320 --> 00:38:04,800
discussions and companies but for organization it hasn't started preparing what shall they be

433
00:38:04,800 --> 00:38:13,920
thinking about today and a second question cannot be yeah it's only regulation or can it also be a

434
00:38:13,920 --> 00:38:23,040
chance for companies I think it's definitely a chance to to consider how they are using AI and

435
00:38:23,040 --> 00:38:30,000
making sure they're using AI in a responsible way and the secure way in terms of what they should be

436
00:38:30,000 --> 00:38:38,400
looking at the EUAA act really creates a a basis on which to do things that should be in place

437
00:38:38,400 --> 00:38:44,240
anyway and what I mean by that is it's things like having an AI inventory knowing what AI has been

438
00:38:44,240 --> 00:38:50,000
used in your organization and for what use cases and that is very much required under the EUAA act

439
00:38:50,000 --> 00:38:57,920
as of August 26th anyway but it's also best practice to have it classifying the risk of which of your AI

440
00:38:57,920 --> 00:39:04,160
solutions is it minimal is it limited is it high risk so are you using for example scoring mechanisms

441
00:39:04,160 --> 00:39:09,840
and things like that which are very much high risk in some cases depending on on what it's for

442
00:39:09,840 --> 00:39:15,760
it might be prohibited so it's it's really understanding what your exposure is from using AI

443
00:39:15,760 --> 00:39:20,640
and making sure that you have governance in place because they might as I said they're unpredictable

444
00:39:20,640 --> 00:39:26,640
so they might go wrong do you have the processes in place to monitor that is they're logging do you

445
00:39:26,640 --> 00:39:31,680
have that human oversight in cases where there's privacy impact assessments or data protection

446
00:39:31,680 --> 00:39:36,960
impact assessments that need to happen are those in place do you have data loss prevention to ensure

447
00:39:36,960 --> 00:39:43,360
your data isn't being used in in a way that is non-compliant how are you doing your risk testing

448
00:39:43,360 --> 00:39:47,600
do you align with international standards so all of these things are our best practices and you

449
00:39:47,600 --> 00:39:54,000
should have them and then there is the AI literacy part of it as well we all have under the

450
00:39:54,000 --> 00:40:01,200
EUAA act there is an obligation to to provide AI training but I think generally there is an

451
00:40:01,200 --> 00:40:07,200
element of all of us needing to have the right level of literacy for the the extent to which we

452
00:40:07,200 --> 00:40:12,800
use AI so if you are obviously a developer creating AI you should have a high level of AI literacy

453
00:40:12,800 --> 00:40:17,840
particularly when it comes to developing AI in a responsible way for example if you're just an

454
00:40:17,840 --> 00:40:22,880
end user of it you need to understand its limitations where ways it can go wrong bias the fact that

455
00:40:22,880 --> 00:40:26,400
it won't give you the right answer you'll just give you the most probable answer these are things

456
00:40:26,400 --> 00:40:32,400
that people need to understand to evaluate what AI is giving them and also having the monitoring

457
00:40:32,400 --> 00:40:38,400
and the life cycle oversight as well having that auditability being able to show that you are

458
00:40:38,400 --> 00:40:46,960
compliant in the first place and that you have control over how the AI is being used and

459
00:40:46,960 --> 00:40:53,680
that you are governing how it's behaving but also you are controlling how the data that it uses is

460
00:40:53,680 --> 00:41:00,560
being used and securing where it runs and how it runs all of those things need to be in place to

461
00:41:00,560 --> 00:41:06,160
make sure that you are not exposed as an organization and that you're not exposing the users of AI

462
00:41:06,160 --> 00:41:11,680
to unintended consequences all of that is within the UAE Act but even if it was and I think it's

463
00:41:11,680 --> 00:41:18,640
things that should be in place as a as a as a minimum I would say and I think Microsoft had a lot

464
00:41:18,640 --> 00:41:24,560
of solutions Microsoft peer view Microsoft Defender and as I have for you has also tools for responsible AI

465
00:41:24,560 --> 00:41:35,920
adoption but we have these tools side and we have the people side how good can can we use this

466
00:41:35,920 --> 00:41:47,680
these tools to be safe be responsible and how important are or how many persons left

467
00:41:48,720 --> 00:41:56,320
on user training what did you think these both yeah I think the tool thinking companies and people

468
00:41:56,320 --> 00:42:03,440
thinking companies yeah it's I think you have to be a people thinking company noted tool thinking

469
00:42:03,440 --> 00:42:08,960
company because I think if you're only looking to implement tools without consideration for the human

470
00:42:08,960 --> 00:42:14,720
element of it you won't get very far unless you are trying to be truly agentic first which are

471
00:42:14,720 --> 00:42:20,480
don't think many organizations are at that stage yet there is always a balance I think between

472
00:42:20,480 --> 00:42:25,520
the teams looking to create and use the technology and the risk and compliance teams within

473
00:42:25,520 --> 00:42:30,320
organizations because one is focused on innovation and the other one is more on security and

474
00:42:30,320 --> 00:42:35,360
compliance and I think it's about finding the right balance and there will be organizations that are

475
00:42:35,360 --> 00:42:43,040
more or less risk averse and more or less innovative and it's okay either way I think what's

476
00:42:43,040 --> 00:42:48,000
important is to identify the right level of innovation for your organization what you're trying to

477
00:42:48,000 --> 00:42:57,440
achieve in terms of the tools it really for me there's three in the stack that I talk about a lot

478
00:42:57,440 --> 00:43:03,200
from a security perspective if we take that first so where and how AI runs

479
00:43:03,200 --> 00:43:11,520
Microsoft has defended very much driven around or focused on security driven compliance

480
00:43:11,520 --> 00:43:16,640
preventing breaches that could cause regulatory violations so you can use defender for things

481
00:43:16,640 --> 00:43:22,880
like discovering any AI models agents and apps you've got it helps with that AI inventory know your

482
00:43:22,880 --> 00:43:27,920
enemy as I say and then detecting any security risks you know things like malicious models or prompt

483
00:43:27,920 --> 00:43:33,840
injections and scanning your models for any vulnerabilities in malware and preventing the all

484
00:43:33,840 --> 00:43:39,760
important kind of data exploration and abuse as well and allowing you to have management of that

485
00:43:39,760 --> 00:43:46,000
of that security and constant monitoring so defender is great from that perspective as a tool then you

486
00:43:46,000 --> 00:43:51,120
would have purview purview would not really be used by your security teams it would be used more

487
00:43:51,120 --> 00:43:56,160
from your compliance and governance teams because it's all about and your legal teams of course

488
00:43:56,160 --> 00:44:01,440
and it's all about logging AI interactions so the prompts and the responses for auditing and

489
00:44:01,440 --> 00:44:09,120
investigations as needed you can classify sensitive data that is being used or generated by AI as well

490
00:44:09,120 --> 00:44:15,440
so it allows you to control again the what data AI uses which is extremely important and

491
00:44:15,440 --> 00:44:20,400
applies in forces policies as well whether that sensitivity labels for your data data loss prevention

492
00:44:20,400 --> 00:44:27,120
or retention policies as well on NEAI outputs again extremely important and giving you that

493
00:44:27,120 --> 00:44:34,560
visibility as well in terms of how your solutions are complying so there's a solution in in

494
00:44:34,560 --> 00:44:38,880
purview I talk about a lot which is the compliance mamaja where you can give it any regulation and you

495
00:44:38,880 --> 00:44:44,720
will review your solutions and give you a score and you will tell you exactly what your tasks are

496
00:44:44,720 --> 00:44:50,720
and what Microsoft's tasks are as the as the provider of that model or technology and it will

497
00:44:50,720 --> 00:44:55,440
give you a list of tasks that you need to improve on to to increase your compliance score

498
00:44:55,440 --> 00:45:00,720
so it does things like you know all these experts are kind of thinking it supports inspections as

499
00:45:00,720 --> 00:45:06,000
well and the enforcement of them which is what's again happening from August 26th there is

500
00:45:06,800 --> 00:45:13,600
if you're in the UAI Act space you have to be able to show that you are monitoring the compliance

501
00:45:13,600 --> 00:45:19,200
and the data AI uses and purview very much allows you to do that for most organizations I think those

502
00:45:19,200 --> 00:45:23,520
two would be would suffice if they're not creating their own models or customizing them

503
00:45:23,520 --> 00:45:29,280
but if you are creating your own custom models through Copa la Studio if you're using Foundry as well

504
00:45:29,280 --> 00:45:34,640
then Foundry itself governs how AI behaves and that's very important as well because

505
00:45:34,640 --> 00:45:43,040
it's all about governance and having responsible AI operationally really so we're talking about

506
00:45:43,040 --> 00:45:47,680
allowed and disallowed models through your Azure policies so having the model governance but also

507
00:45:47,680 --> 00:45:53,440
guardrails and content controls safety filters you know output constraints that kind of thing

508
00:45:53,440 --> 00:45:58,480
and also the actual documentation of your models your versions the purpose of of them existing in

509
00:45:58,480 --> 00:46:05,920
the first place and policy checks guardrail violations all of those things are done within Foundry there's

510
00:46:05,920 --> 00:46:12,560
a lot more that we need to worry about the moment we start customizing or creating our own agents

511
00:46:12,560 --> 00:46:19,600
or models because we are responsible for what they're doing how they're operating and we really need

512
00:46:19,600 --> 00:46:25,440
to make sure that we we have evaluated the their safety and also documented the datasets and

513
00:46:26,640 --> 00:46:31,120
making sure that we've risk assessed them so there's a lot there's a lot more we need to worry about

514
00:46:31,120 --> 00:46:36,560
if we have customized them but I'm not sure them and your organizations are extensively doing this

515
00:46:36,560 --> 00:46:44,000
yet but I think in the future we will see a lot more of that for sure. How do you handle those

516
00:46:44,000 --> 00:46:52,160
regulation topics without slowing down innovation in your company or from how can we do this?

517
00:46:53,600 --> 00:46:59,120
I think the important thing with legislation is that it doesn't change very often because it is set

518
00:46:59,120 --> 00:47:05,840
by lawmakers so it doesn't tend to change very fast regulations move much faster and the I think

519
00:47:05,840 --> 00:47:11,360
the best way right now if you're using the Microsoft stack is to use PerView and the compliance manager

520
00:47:11,360 --> 00:47:18,240
because they keep the regulations up to date so you can constantly evaluate really your solutions and

521
00:47:18,240 --> 00:47:24,560
see where the the changes are and when you're not compliant. A lot of the time these things are

522
00:47:24,560 --> 00:47:28,960
are going to be communicated well and your compliance and your legal teams will very likely be

523
00:47:28,960 --> 00:47:36,080
paying attention to that to identify what applies. The main thing to remember because all of

524
00:47:36,080 --> 00:47:41,200
this can sound very very complex and people can worry a lot when it comes to legal obligations around

525
00:47:41,200 --> 00:47:48,160
the AI. It really depends on what you're using AI for and whether it is truly autonomous and whether

526
00:47:48,160 --> 00:47:55,760
it is actually making its own decisions or if you're using it in a very minimal limited risk way

527
00:47:55,760 --> 00:48:04,640
because you won't have that much compliance or legal obligations concerns. If you're using AI

528
00:48:04,640 --> 00:48:14,080
in a fairly there I say basic way you won't have much exposure but you do need to do that assessment

529
00:48:14,080 --> 00:48:20,160
as a minimum to identify who's using a young or in your organization what are they using it for

530
00:48:20,160 --> 00:48:26,080
and do you have any exposure there in terms of data in terms of risk in terms of security that is

531
00:48:26,080 --> 00:48:30,960
I think the the the important thing because you you need to you need to know your enemy. The other thing

532
00:48:30,960 --> 00:48:36,720
to be aware of as well is I think what is particularly important that I don't see that many organizations

533
00:48:36,720 --> 00:48:43,440
doing it's important to have a use an acceptable use policy for AI in your organization and what I

534
00:48:43,440 --> 00:48:50,320
mean by that is a lot of people will be using their own business accounts to use your accounts I

535
00:48:50,320 --> 00:48:57,680
mean by that to use AI that you may not know of so rogue AI or shadow AI is very much a thing

536
00:48:57,680 --> 00:49:03,040
and it's really a case of doing that analysis within your systems and your tenants to identify

537
00:49:03,040 --> 00:49:09,760
who is using what that you don't know about I think there is this element at the moment of because

538
00:49:09,760 --> 00:49:13,920
everyone is experimenting which again you don't want to stop people from doing so because this is

539
00:49:13,920 --> 00:49:18,240
new technology and you want to encourage innovation you want to encourage new ways of working but at the

540
00:49:18,240 --> 00:49:23,520
same time you need to be doing that in a secure responsible way it's about getting visibility of

541
00:49:23,520 --> 00:49:29,920
what people are trying to use AI for and can you make that official can you make that controlled

542
00:49:29,920 --> 00:49:35,600
and managed and monitored it's not about stopping it I think it would it would be the wrong thing to

543
00:49:35,600 --> 00:49:41,680
stop it but it is about identifying what isn't isn't allowed based on the own your policies so I

544
00:49:41,680 --> 00:49:47,680
think that's a very important part of it too as well is creating those guidelines so that people

545
00:49:47,680 --> 00:49:54,880
understand what they can and and shouldn't use AI for and having that visibility in the first place

546
00:49:54,880 --> 00:50:01,920
that's great and I have seen on session lives you have on yeah you're delivering a session title

547
00:50:01,920 --> 00:50:08,480
AI legislation what you need to know what's the single most important takeaway you want attendees to

548
00:50:08,480 --> 00:50:18,080
leave with no no your enemy know what they are you've got in your tenants know you know have have an

549
00:50:18,080 --> 00:50:25,120
understanding of what you're using AI for right now and and and what that means a lot of organizations

550
00:50:25,120 --> 00:50:30,000
I think are experimenting their people are experimenting but not that not many organizations

551
00:50:30,000 --> 00:50:35,120
truly know where AI solutions are being used whether that's a genticae or not I'm using the

552
00:50:35,120 --> 00:50:43,280
the term very very generally here it's a it's a case of understanding what what people are

553
00:50:43,280 --> 00:50:48,160
trying to do with AI in your organization and are you giving are you being proactive

554
00:50:48,160 --> 00:50:54,880
enough are you making sure that they understand the risks are you giving them that they are

555
00:50:54,880 --> 00:51:00,880
literacy training and are you putting those cardless card rails in place to to support them I think

556
00:51:00,880 --> 00:51:06,400
that's the main thing it's a lot of organizations I don't think have a good understanding right now

557
00:51:06,400 --> 00:51:13,680
what AI is being used were and that's a big big risk for organizations yeah also your day job your

558
00:51:13,680 --> 00:51:21,200
community involvement is extraordinary what organially inspired you to become so active in the

559
00:51:21,200 --> 00:51:29,120
Microsoft community I really enjoyed the first time I presented I was encouraged by my manager

560
00:51:29,120 --> 00:51:33,520
to submit a session at a conference for a solution a had built and I didn't think we get accepted

561
00:51:33,520 --> 00:51:37,200
in a million years because I didn't think anyone would find that interesting but I was wrong you

562
00:51:37,200 --> 00:51:44,320
got accepted so I I panicked because I might speak publicly quite a lot now now you can't get me

563
00:51:44,320 --> 00:51:50,000
to not jump on stage and talk about something but I used to be absolutely terrified of public speaking

564
00:51:50,000 --> 00:51:56,400
and when I tell people this now they don't believe it but I absolutely was and I and I very much

565
00:51:56,400 --> 00:52:01,760
was terrified of speaking the first time I did that conference and I think there's a YouTube video

566
00:52:01,760 --> 00:52:08,640
somewhere of me which I cannot bring myself to watch because someone recorded the session and it was

567
00:52:08,640 --> 00:52:14,480
you know I've come a long way since then the the reason why I I decided to do it that that first

568
00:52:14,480 --> 00:52:18,960
time I did it because I wanted to get over the fear of doing it quite honestly but the reason I

569
00:52:18,960 --> 00:52:25,440
continue to do it after that point was because it was great to hear people in the audience finding

570
00:52:25,440 --> 00:52:30,880
the information and the knowledge and my experiences that I shared useful it made the difference to

571
00:52:30,880 --> 00:52:36,640
them and I helped another person try to do something with the technology or understand the technology

572
00:52:36,640 --> 00:52:43,360
better and that's very rewarding when you see people actually really benefit from your experiences

573
00:52:43,360 --> 00:52:46,960
and it makes their lives easier and you get to have conversations with them afterwards and you

574
00:52:46,960 --> 00:52:52,160
learn something from them as well. I think that is very rewarding and also seeing other people in the

575
00:52:52,160 --> 00:52:56,480
community doing the same thing from their knowledge areas and as I said in the beginning speaking to

576
00:52:56,480 --> 00:53:01,280
them about the things they're doing and exchanging thoughts and opinions about where the technology is

577
00:53:01,280 --> 00:53:06,000
going the challenges they're facing in their roles but also meeting people that are in the same job

578
00:53:06,000 --> 00:53:11,680
as you are in a different organization and sort of comparing notes to a certain extent and realizing

579
00:53:11,680 --> 00:53:16,800
the challenges you face down a day to day you're not alone in this it's not just you there's other

580
00:53:16,800 --> 00:53:21,840
people out there facing the same challenges and there is a great thing about coming to get and

581
00:53:21,840 --> 00:53:29,440
discussing those and having that group therapy and them in love it but also at the same time discussing

582
00:53:29,440 --> 00:53:34,960
how do we change this how do we do this differently what can we use technology for how are you

583
00:53:34,960 --> 00:53:40,480
using AI in your day to day role and and having that exchange of knowledge and ideas I think that

584
00:53:40,480 --> 00:53:46,320
is extremely powerful and the opportunity that you get as well from from having that exposure from

585
00:53:46,320 --> 00:53:53,120
a network perspective from a career perspective can't be over estimated really I think it's it really

586
00:53:53,120 --> 00:54:01,600
does allow you to understand your role a lot more and the technology a lot at a much broader level

587
00:54:01,600 --> 00:54:05,920
than if you didn't become part of the community if you didn't attend those events it really helps

588
00:54:05,920 --> 00:54:13,600
you upskill and expand your network and really get a better a different perhaps if not better a

589
00:54:13,600 --> 00:54:19,760
different perspective of of the technology at the at the much broader level nothing that's very very

590
00:54:19,760 --> 00:54:26,080
very beneficial and that's why I attend events and that's why it's because events I I I remember my life

591
00:54:26,080 --> 00:54:31,760
before I was involved in the community and I can definitely tell you it's it's a much more enriched one

592
00:54:31,760 --> 00:54:38,000
now because you you make friendships as well within the community you can present with people together

593
00:54:38,800 --> 00:54:44,240
and you become a better professional as a result and I think that's you know it's it's great that

594
00:54:44,240 --> 00:54:51,440
the community exists I think we would be at all of us at a disadvantage if it didn't I think also

595
00:54:51,440 --> 00:54:57,680
one of the topics is mentorship you are in the yeah a moment in power platform can you tell a little

596
00:54:57,680 --> 00:55:06,480
bit about these yeah organization and also how important was mentoring for you in your career

597
00:55:07,920 --> 00:55:14,960
yeah absolutely I am very passionate about mentoring others because I I benefited from mentoring myself

598
00:55:14,960 --> 00:55:19,040
very early in my career and and as I said that wouldn't be in the position I mean now if someone

599
00:55:19,040 --> 00:55:23,840
hadn't really in a way mentored me unofficially and said no you should you know go for this off you go

600
00:55:23,840 --> 00:55:30,560
I am part of the women in power platform mentorship program so it is a a Microsoft initiative

601
00:55:30,560 --> 00:55:36,240
bringing women within the the power platform space together to mentor and support each other

602
00:55:36,240 --> 00:55:42,320
either on a one-to-one basis or on a group basis they run a cohort every quarter so you spend

603
00:55:42,320 --> 00:55:47,680
three months with your mentor or mentorship group and every every three months there is a new cohort

604
00:55:47,680 --> 00:55:53,760
basically it's very well organized by Danielle Moonin and Shravanis City and they do a great great

605
00:55:53,760 --> 00:55:59,200
work in terms of the mentorship program itself it's very well supported and there's a great love

606
00:55:59,200 --> 00:56:04,560
and appreciation for them and for all that they do it's it's very much a global global network

607
00:56:05,280 --> 00:56:10,400
on our own caradjian you body that's thinking about mentorship to submit an application once the

608
00:56:10,400 --> 00:56:15,040
the next cohort opens we're currently in the middle of a cohort finishing in a month or two

609
00:56:15,040 --> 00:56:22,000
all right so for me I would say mentorship is great if particularly when you're feeling stuck and you

610
00:56:22,000 --> 00:56:28,240
feel like you can't figure out a way you can't figure out the way through your next step you're not

611
00:56:28,240 --> 00:56:32,800
really sure what that right thing to do is it could be technically it could be from a career

612
00:56:32,800 --> 00:56:36,800
progression perspective it could be that you want to try something new but you're not really sure

613
00:56:36,800 --> 00:56:42,160
how to go about it it could be that you're looking for someone to help you get introduced to people

614
00:56:42,160 --> 00:56:47,520
or identify if even just talk talk to them about where you're at and try and figure out your blind

615
00:56:47,520 --> 00:56:53,920
spots or get that fresh perspective as to what you could do in my life I've been in a couple a

616
00:56:53,920 --> 00:56:58,080
couple of times bit stuck and I wasn't really sure where I wanted to go next and what I wanted to do

617
00:56:58,080 --> 00:57:02,160
and it's really helpful to talk to someone about where you're at because nothing

618
00:57:02,160 --> 00:57:06,960
itself can help you figure out the answer but sometimes you might not believe in yourself as much

619
00:57:06,960 --> 00:57:14,560
as someone else does and that might might it might help you have someone look at you as a person of

620
00:57:14,560 --> 00:57:18,960
unlimited potential you could do anything even if you don't believe you could do anything you could

621
00:57:18,960 --> 00:57:24,160
do anything and if you speak to someone who is a mentor who looks at you without unlimited potential

622
00:57:24,160 --> 00:57:30,720
they will say to you well okay you are here right now what if you aimed for insert crazy goal over

623
00:57:30,720 --> 00:57:35,520
here and they they might say I can't do that there's no way I could do it is about would you want to

624
00:57:35,520 --> 00:57:41,760
would you like to because you can and it's having that person believe in you and say to you you can do

625
00:57:41,760 --> 00:57:47,520
it I will support you if you want to do it do you want to do it and in having that guidance as well

626
00:57:47,520 --> 00:57:53,440
and not starting from zero having someone that can help you and use their experiences to to give

627
00:57:53,440 --> 00:58:00,560
you that knowledge of what lies ahead to a certain extent and and show you the common pitfalls and

628
00:58:00,560 --> 00:58:05,840
show you what's important and and help you through it and have that sounding board and for me I think

629
00:58:05,840 --> 00:58:10,400
everyone should at any point in their life have a mentor because I think if you if you don't you're

630
00:58:10,400 --> 00:58:15,680
you're missing that reflection but it but I think it's particularly important at moments in your

631
00:58:15,680 --> 00:58:22,960
life where you want to make a change or try something new or different you will know when you need

632
00:58:22,960 --> 00:58:26,720
it because something will be bugging you and you won't know what to do about it and I think mentorship

633
00:58:26,720 --> 00:58:32,880
is great for those moments but also finding the right mentor is key you need to to find someone who

634
00:58:32,880 --> 00:58:38,320
you trust and who understands you and who has the right experience to support in the thing you're

635
00:58:38,320 --> 00:58:42,720
trying to do and and that's what women in power platform is is great that they match mentors and

636
00:58:42,720 --> 00:58:48,160
mentees based on the knowledge of the mentor and what the mentees looking to get out of the

637
00:58:48,160 --> 00:58:55,440
mentorship cohort so that is very important as well yeah I think you do do so much all all all the other

638
00:58:55,440 --> 00:59:02,400
things but one with me really impressed is you are here in the UK delegation to the United

639
00:59:02,400 --> 00:59:08,960
Nation Commission on the status of women but well how is the status of the women actually?

640
00:59:08,960 --> 00:59:19,120
How is the status of the women not great? So the it is I've done this for three years now I've

641
00:59:19,120 --> 00:59:24,720
been part of the the the the participating the UK delegation for the the commission for the

642
00:59:24,720 --> 00:59:30,720
states of women for for three years in a row and it's it definitely is my my favorite and part of

643
00:59:30,720 --> 00:59:36,480
the year but also the one I dread the most because the topics that get discussed on women's experiences

644
00:59:36,480 --> 00:59:41,040
globally as you can imagine being the UN we don't really necessarily talk about just

645
00:59:41,040 --> 00:59:46,160
the the the areas where women are struggling but areas where women are really struggling and I'm

646
00:59:46,160 --> 00:59:56,560
talking about war conflict abuse it can get very very difficult to just to be in the room and listen

647
00:59:56,560 --> 01:00:03,200
to the issues that are that women are having to face we are very lucky and I always have a lot of

648
01:00:03,200 --> 01:00:10,960
gratitude for the life that myself as a woman in the UK has and I grew up in Greece I'm Greek originally

649
01:00:11,920 --> 01:00:18,080
I didn't have war and conflict in my life as a woman growing up and I believed in the the

650
01:00:18,080 --> 01:00:25,040
developed world all of my life when you contrast that to what life for a woman is in areas that have

651
01:00:25,040 --> 01:00:30,080
been plagued by war and conflict or their life and we're talking about young girls as well

652
01:00:30,080 --> 01:00:36,640
the horrors that they face they don't even enter our consciousness necessarily in Europe but they

653
01:00:36,640 --> 01:00:41,600
exist they happen all the time there's millions of them that are suffering and and that's what the

654
01:00:41,600 --> 01:00:47,760
commutions for the status of women is trying to to change it brings nations together to re in there's

655
01:00:47,760 --> 01:00:53,520
a different theme every year that they look to address so for example the theme this year was all about

656
01:00:53,520 --> 01:00:59,360
access to justice and legal systems and one of the things that was discussed was the fact that a lot

657
01:00:59,360 --> 01:01:03,360
of women in the world do not have access to justice in the first place let alone actually getting

658
01:01:03,360 --> 01:01:07,920
justice that's a whole different problem altogether so it's things that we don't even think about

659
01:01:07,920 --> 01:01:16,160
necessarily it's a very humbling experience but it's very it's a very I'm grateful to be part of it

660
01:01:16,160 --> 01:01:22,800
because aid gives me perspective it reminds me how lucky we are but it also reminds me how long

661
01:01:22,800 --> 01:01:31,440
we've got to go and I try to take what I learned from that into my role and trying to keep it moving

662
01:01:31,440 --> 01:01:40,240
forwards it's obviously a much bigger macro level government countries level event but it's all about

663
01:01:40,240 --> 01:01:45,440
taking taking those experiences back and identifying what I can do in my role in my organization

664
01:01:45,440 --> 01:01:52,320
in the initiatives I'm involved in to ensure that we have a better world for for women as well and

665
01:01:52,320 --> 01:01:58,640
you know I'm a mom and a six year old daughter I want to see progress made in my lifetime for her as well

666
01:01:59,600 --> 01:02:07,120
awesome yeah we're running a little bit out of time I ask you have you time for a rapid fire out

667
01:02:07,120 --> 01:02:16,800
yes go for it okay good coffee tea or energy drink coffee if you have to choose one two

668
01:02:16,800 --> 01:02:27,120
will dynamics 365 or power platform power platform remote work or home office remote work or office

669
01:02:28,000 --> 01:02:33,680
oh if I had to choose one it would be office because I love seeing people but ideally it would be

670
01:02:33,680 --> 01:02:42,400
50 50 okay and I don't know I will stress you but I do a conference the NC 65 quant but what's your

671
01:02:42,400 --> 01:02:50,800
failure but Microsoft event oh god I'm oh I'm gonna so I yeah so I obviously run my own user groups

672
01:02:50,800 --> 01:02:57,760
and conferences in the UK but I have to say the one that always has the the biggest place in my

673
01:02:57,760 --> 01:03:02,480
heart and I'm so sorry for all of the other ones that I'm involved in it's not that I love them any

674
01:03:02,480 --> 01:03:09,600
less just that from a location and weather wise the the one conference I love is dynamics mines because

675
01:03:09,600 --> 01:03:15,600
it makes me feel like I'm home almost because it's in it's expressed in Slovenia in May it's always

676
01:03:15,600 --> 01:03:22,880
lovely whether it's sunny it's organized to perfection by by the team behind it and it's a big

677
01:03:22,880 --> 01:03:27,920
conference it's it's great to be part of it and it's it's definitely my favorite one because it's a

678
01:03:27,920 --> 01:03:36,880
conference and the holiday all in one go one thing Microsoft showed published tomorrow oh

679
01:03:36,880 --> 01:03:41,760
a licensing guide that everyone can understand and you straightforward

680
01:03:41,760 --> 01:03:49,120
you're most used AI tool right now co-pilot

681
01:03:50,640 --> 01:03:59,120
one book you recommend to all technology leaders it's an old one but I think particularly relevant

682
01:03:59,120 --> 01:04:06,320
right now it's by Brad Smith from Microsoft he leads the legal teams within Microsoft and it's called

683
01:04:06,320 --> 01:04:12,000
tools and weapons and he was written almost 10 years ago I think from what mistaken and he talks a

684
01:04:12,000 --> 01:04:17,280
lot about artificial intelligence even back then and the fact that any technological advancement

685
01:04:17,280 --> 01:04:22,800
is a tool in the weapon and he talks about the challenges with introducing technology and

686
01:04:22,800 --> 01:04:29,040
from a Microsoft perspective the fact that sometimes they've even had to sue their own government

687
01:04:29,040 --> 01:04:34,240
for the things that they wanted to do with technology or the or the the requests by the government

688
01:04:34,240 --> 01:04:38,880
that went against privacy for example it's a very very interesting book particularly relevant

689
01:04:38,880 --> 01:04:44,640
still now because of where we are with AI and Brad Smith suggested that we should have a

690
01:04:44,640 --> 01:04:49,760
license for AI development and use the same way we do driving licenses for driving a car we don't

691
01:04:49,760 --> 01:04:53,360
allow people to drive a car without the license and that he suggested that perhaps we should

692
01:04:53,360 --> 01:04:58,000
introduce a license for creating developing using a knife so yeah very very good book

693
01:04:58,000 --> 01:05:02,720
your best piece of advice for some entering tech today

694
01:05:02,720 --> 01:05:11,680
you need to give it a try and you won't know everything he won't be perfect but what you need to

695
01:05:11,680 --> 01:05:18,000
do is just give it a go and keep going okay then then my last question if you could back and give

696
01:05:18,000 --> 01:05:25,840
your younger self one one piece of career advice what will it be don't work so hard to have some fun

697
01:05:25,840 --> 01:05:35,520
as well thank you Arti this was so much yeah enjoying it's most been fantastic hearing you

698
01:05:35,520 --> 01:05:41,600
about your journey from enterprise delivering leadership AI community building mentorship

699
01:05:41,600 --> 01:05:51,280
and the future of agente AI yeah for all listeners I put the links from on the show notes so they

700
01:05:51,280 --> 01:06:01,760
can find you so yeah thank you and have a nice day thank you for having a miracle love let's be here