Copilot Cowork: The Future of AI Collaboration in Microsoft 365 with Vesa "Vesku" Nopanen [MVP]

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>> Yeah, welcome to another edition of the MC65FM podcast.

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In this episode, we work with Visa.

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We go to Nopan about how Microsoft Copa.

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Let's do a IAgent group and Copa.

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It pages,

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cool work,

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changing the way we collaborate in MC65 from

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practical addictions, lessons to future AI workers.

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This conservation, this is consenit.

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>> Yeah. Well, okay.

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This conversation explores what modern work called

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like over the next few years.

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So welcome, WestBah. How are you?

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>> Hey, thank you, Mirko.

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I am fine. Yes, we have a quite

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packed agenda there.

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>> Yeah. It's a really good topic,

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I think, and that comes a lot of new stuff with Copa.

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I think, but before we start,

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will you a little bit introduce you for,

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I don't know, it could be that someone didn't know you.

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>> Well, I'm sure there's plenty of people who don't know me.

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Yeah, and thank you for introducing me to

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the show or inviting me to the show.

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Yes, my name is Wes Anokane and everybody calls me Beskom.

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I'm a principal consultant for future work at Solava Mia,

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and yes, I work with AI,

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a lot of Microsoft 365 Copa.

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And everything related to that.

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And of course, Microsoft AI is on my desk during the daily work.

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And I live in Finland in Turku.

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So, and it's now late spring here,

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so it's getting warm even in Finland.

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So, that's a chance.

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This is the best period of time,

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like in the year, of course,

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when it's getting warmer, getting greener, so there's light.

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So after the dark and cold,

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by a winter, it is kind of a summer is coming finally.

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>> Awesome.

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You've been talking about AI and collaboration

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long before Copa pilot became mainstream.

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What fascinating you are early on on this topic.

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>> Well, yes, I have been talking about those for quite some time,

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because AI has been always there.

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It's been there a long, long time as we know.

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It's been there since '50s as a term.

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So, AI is not a new thing,

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but of course, how we are able to utilize AI in our everyday work,

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like everybody can utilize it.

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That's the new thing.

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And of course, these capabilities,

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these new models have been giving to TA.

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They're just expanding on the possibilities what we can be doing.

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And yes, it has fascinated me for since I was a kid, probably,

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because I love sci-fi and science fiction and stories,

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and seeing what AI can do in bad cases,

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and of course, in good cases.

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So, of course, I'm focusing on those good use cases.

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And on the work side, and that's how we are seeing the AI today.

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But it's still a tool.

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People can use it for back then.

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It could be bad, as we know.

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But it's our, of course, what we do is we are

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teaching and coaching people how to use AI at work, of course.

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And yeah, it's, I've been always fascinated with the AI,

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and then how it has been, how is, I'm not saying,

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I'm going to say just okay, how it started to appear

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in Microsoft 365, as has been quite a interesting road.

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You had first the little things.

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Of course, we've had AI embedded in applications for a long time.

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We've seen AI in Word, like, okay, here we have the spelling checkers and so on.

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And it has evolved from simple AI to very, very complex AI in just kind of a few years.

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But which natural language models appearing,

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and it started to really get fractions.

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And use cases kind of a view on what we were.

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Or it's an eye perhaps even thinking.

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Yeah, you say sci-fi, start record start was.

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Yeah, start track of course.

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What do you think?

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I've been always a, I've been always a tricky.

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But I do love Star Wars as well.

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Yeah, it's as well as Gold.

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Yeah, I think I'm also more tricky Star Wars.

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It's okay.

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But I love all Babylon 5 and all these stuff.

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Yeah, we have gone from a team first calibration to AI first calibration.

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I think very quick.

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What change from your perspective?

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Well, of course, what enabled this has been the capabilities of AI

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that it can do these things.

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It can do these things quickly as well.

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So we don't have to kind of put the task to the AI.

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And then it's working behind the scenes and comes back next day with the answer.

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So that would not be AI first approach.

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But instead we can utilize AI quickly all the time in our work.

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But also that it's affordable as well.

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So it's available for us.

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You may have a co-pilot license and hey, there you are.

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You have lots of fantastic use cases available for you.

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And it uses how you can utilize AI in the daily world.

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Of course, well, since I working with Microsoft ecosystem,

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it's very easy for me to kind of talk about how you are using AI

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when using Microsoft 365.

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And so in there, AI has been embedded in applications.

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But now it's becoming more and more aware of what you have been working on.

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So it has this general understanding of what you are working with.

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So the new technology names work like you.

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It has access to your, of course, to the data you have in Microsoft 365.

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And can utilize them.

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And with that, it's easier to use AI,

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or as I'll go AI first because hey, it already knows more or less what I know or what I do.

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What I'm working on, what I, why am I messaging with,

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what meetings I've had or what's upcoming.

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So it kind of, you can very easily spar with the AI on that.

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And of course, it's there all the time.

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It doesn't have other meetings.

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It doesn't have a lunch breaks or a, or a, or a downtime I'd use of, I guess, as well.

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So you can have that conversation with the AI and ask it helps help any time.

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But what's really also changing now is just not asking.

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So when we are working with the AI, we are expecting AI to do things as well.

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So instead of being your spot, just your sparring partner, it can still be that it's,

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it's of course, what we use it for.

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We want to brainstorm ideas.

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But then when you want to start taking action out of those brainstorms, the AI can help you.

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So it can generate, start to generate, of course, those presentations that match your company style.

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It can start creating those accelerates or perhaps you need it to start creating

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hopefully in the, in the near future tasks and so on.

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But then depending on how you are using a new between which application,

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it's able to utilize those applications and create those things as well.

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And it's starting to see more and more picture about what we are doing.

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So it can better answer the needs.

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And yeah, I think at the start, a lot of people wasn't so happy with their launch co-pilot.

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What was your first reaction when Microsoft announced or launched co-pilot?

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Now you are going to ancient history part.

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All right, it's not that many years, but it feels like that.

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And there's a lot has changed since those days.

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My first impressions, whenever it was launched, of course, I was excited about that.

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And then we have already seen by that time what GPT models can kind of do.

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And it was just a very, very early beginning in that.

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Now when we look at those capabilities, those had those were really,

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they were not that like a good or a very limited when we have when we compare to what we have now.

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So first impressions, I was really kind of fascinated and curious,

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interested about that and then seeing hopefully the potential there as well.

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And then then hoping, okay, how this will answer the promises.

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Yes, we know it struggled, co-pilot when you get the start to use it, it was very limited

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to what we were probably expecting.

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But now what we have today, this is starting to show,

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okay, these are the capabilities, okay.

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This is like what we were kind of promised back then and even more as well.

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And you already said the magic work, work, co-work is changing a lot of these things and for the better.

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Yeah, before we deep dive into co-pilot, did you think organization still underestimated how

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disruptive AI inside MC6-5 will become?

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underestimating those. Yes and no, some organizations may not be that kind of convinced you,

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okay, what the AI can do. But then I also see organizations that are probably, or at least,

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individual people who are overestimating, okay, what AI can do. And typically, I would say some

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of the business people are the, that's kind of when they have been kind of a, they've gotten an

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impression, AI can do everything and then when you go talk to business people who think AI can do

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everything and there's really no limits on what they think. But the organization is typically,

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yeah, okay, what's going to be the change? But I think the more kind of a, the very big,

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or kind of a big, I'm not saying issue, but the thing is that organizations underestimate how much

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change management is needs. Because some people can think, okay, just give them AI and tables

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start utilizing it and hey, everybody is very productive with AI. That's not going to happen.

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So people need chase management and organizations need chase management and change.

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They are not going to jump from traditional working together or ways of working to AI first,

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ways of working without change management. Because they need coaching, they need training,

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they need use cases, they need kind of examples and how do you utilize AI because otherwise,

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it will be just, hey, I don't know what I'm doing there or if they are interested, they might learn,

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learn a lot of ways how to use it. But if they are busy filled up with ordinary work,

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they don't have time or perhaps they don't have motivation to go and discover their use cases and

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how to use it, then AI will be just another tool they would have to use and they never have time for

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it. I think they have these micro methods, passwords, co-pilot champions, I think. I think that this is

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one of the concepts I think they use. But I really understand that a lot of people,

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not so, I don't know, 10-1 hours with AI and they think it's take my job and so on and don't see it

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as a productivity tool. I think that's a risk. But you have a condition co-pilot, co-work.

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Is this the new AI teammate or what this concept means to you?

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Well, co-work can't be called by many names, of course, but it's an agent in co-pilot.

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Of course, it's based on anthropic co-work. That's practically the same tool, but pro to the

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Microsoft 365 environment. But yes, I would be calling co-work as your AI teammate because it can

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do actions. So while co-pilot was quite simple and he still meant for more simple tasks, it's not

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kind of a planning through tasks and executing them unlike what co-work is doing. So when you give

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it more discipline instructions and give background information, your goals and what you need,

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you can really describe that quite lengthy. You don't have to start splitting your, okay,

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what I needed to do to the little tasks, but then that you instead can just tell it about your goals

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and your needs and then what it should be doing, perhaps you're explaining the process.

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And just like you would do again for the intern or our new employee,

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and then it can go ahead and start doing its work. So it will be able to have

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reason over the data it will plan how it's going to progress and finally it will then start

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taking actions. And it's not limited to seem like a, to seem like application, like perhaps

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to like co-pilot in PowerPoint. You can utilize co-pilot there, but when you are usually utilizing

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co-pilot co-work, it can generate and understand PowerPoints. It can generate and understand

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Excel files, Word documents, PDFs, your messages, or through Teams and Exchange and so on.

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And so it has access to the wide wide area of tools as well. And then it will be take,

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it's able to take multiple kind of numerous actions into tools as well. So

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it's really up to us what we are taking, okay, what it should be doing. But it will need instructions.

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It's still an AI, it's tool, but it's better on working through these instructions.

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And one thing I think co-pilot is different from our generic co-pilot. So co-work is different

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from ordinary co-pilot is that it can understand those instructions and constraints you have to read.

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It will follow them much better than what, for example, co-pilot is to at the moment at least.

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There are also, I think, there's co-work, then I think worker IQ and what's also new,

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I have a lot of new passwords. What's the co-pilot skills? What are the difference

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both these three concepts?

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Well, yeah, there's a lot of buzzwords. You will get the, when we are recording this, it's still

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end of May and we'll be still ahead of us. So there's probably going to be new buzzwords at

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field as well. And then again at the ignite. So yeah, we will have buzzwords and basically things

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are renamed and reorganized at the much faster speed and avert before. So that's one reason we are

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getting it, it's quite hectic. And also, because there is this one more buzzword from the

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program that people can join. So we are, people who are in the frontier will be getting these

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changes first. So in front there are a lot of things are living back and forth, like there will be

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new tools and new names and name changes more than the normal end user or an all its user would

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be receiving and seeing. But yeah, so the work like you is it's the all let's say,

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playing or or platform or I would just say describe it where you can, where these AI can discover

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information that's relevant to you, that's your work intelligence. It has access to them.

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To do everything like through Microsoft Graph. And we had, we learned earlier from Copa

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a lot that he's using Microsoft Graph to kind of fix information and we've been at a

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crab has been there for a very long time. But the work like you is building on top of that. So it can

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basically reason out of the data better than just playing what Copa was doing. And it was doing

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a pretty good job there to be honest. So, so work like you is just going to be the layer

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that was the word I was looking earlier. So the layer between your requests when AI is starting to

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get information from Microsoft 365. And humans and skill, a mission skills as well. Well,

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that's more human oriented. We had the people, people, partners, skills and that's that has been

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living quite a lot recently. But it's basically the way you can start telling your organization and

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of course AI will kind of skills you have. So it can provide those some or suggest those

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automatically. And then you can confirm and edit your skills. So, so your professional profile is

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going to be more complete. So when it perhaps AI started to look people who could be helping you out

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with something, take it can utilize the skills. Again, that's not nothing new for organizations

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generally because they are always usually at some kind of skills matrix about people, but what

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people can do. And that this is going to be just within the Microsoft 365 and how AI will be able to

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utilize that information as well. And I think you did mention third,

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and named there as well, that I that slipped my mind. Can you remind me?

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What I think as company, I have all I don't know all these options, but I think that we have a new

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era of how we thinking governance and the co-pilot, co-work area.

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Well, how you want to think about that of course you want to make sure that your data is secure.

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So you need to go through the Microsoft 365 security and data protection, but so you will

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be needing the data plus prevention sensitivity labels, rules there. What should be what should be

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happening. So you can protect the most distance of data. Okay, these are some of the data probably

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maybe something that you don't want AI to even handle or have access to. And so you need to go

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through that. Of course, organizations should have done that already seven hundred several years ago.

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But now with the age of AI, they are realizing perhaps okay, this is something that needs to be done.

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So there's still quite traditional ways what you are when you are working with organizations,

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because you have to just use these tools and start classifying your data and taking about okay,

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how we are going to be managing what's allowed, what should be done there. So we can govern

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where co-pilot or AI has access to. So that's one important topic. And when organizations are

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starting to leverage AI and moving towards the AI first work, they will need that they need to

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do checkings on on well IT level as well. So okay, what's our readiness, what we should be configuring,

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what we should be changing and every change requires usually some change management for

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men for end users. So people know how to utilize these options and tools when they are working. So

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it always goes to the people and how you are prepping up people to change the way they are working

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and not just to repeat what they've been doing 10 years and then start working in a ways okay,

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now what time when I'm doing something, AI can take benefit of the information and help me out

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when I'm working on something. So instead of putting your files to your hard drive, you are putting

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them to the cloud, we are co-pilot can access them. And thus of course co-work as well.

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So there's a lot of let's say traditional IT work still involved there.

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That was interesting. I think a little bit about

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there I think, or have we tested that should always stay humans and what kind of task

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are perfect for AI delegation right now? Well, there's, well I think every organization should think

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about the responsible AI part and then and and generate those guidelines and also help people

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to understand where and when or at least where they should not be applying AI. So what are

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good tasks for the AI? What tasks are not good for AI? And but generally I would say that kind of

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decision making is basically human child. AI is there to assist you. I'm not saying that every minor

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decision would not be AI or like would be human only but when we think about okay, we need to make

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larger decisions. We need to make decisions that require empathy or you have to have some

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soft skills there and an understanding of the bigger picture. We still have to remember AI can

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make mistakes. It's a lot better and it was a few years ago in that puppet, but it still can

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hallucinate information and then it can still misinterpret that information as well. So they don't

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necessarily understand the full context because they can get confused if they are getting information

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of the similar, like out of the context, but it still feels like okay, this could be in this context

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they get confused after result and especially it will affect how they are making decisions.

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But however, you can still use AI of course to assist you with the decision making. And we know

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every organization is different one. So we know that banks are and financially are doing these

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loan decisions automatically. So that's AI and so they need to have quite a good and hopefully they

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have responsible AI guidelines for what they are following and then following the responsible AI

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there so they need to be transparent about how this happened where the AI was used and I think

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remember the responsible usage in there. So sorry you are not getting a clear answer there because

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there isn't like a line that you can cross but there are things that are definitely on that human

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side when you are making those certain interpretations of the data. Perhaps because AI is always working

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on the data, if it doesn't have all the data, it doesn't know it doesn't have all the data.

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Unless that has been somehow included in the process so it would have a chance of knowing

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it's missing update or not but perhaps something has happened in the world just overnight

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and AI doesn't have any idea about human when it goes to humans this and okay we need to be

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side on this and they can relate okay we just heard about a lot of things changing at

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during the last night and we have to take a look at that and how it's got to affect so

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so yeah so there's got to be more and more decision making by AI of course

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but there's going to be still decisions a lot of those decisions that will go through humans

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and I think that's a good positioning on AI that's it's going to assist us make better decisions

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faster and then making sure that we have to relevant data when we are doing the decision.

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So we have we also rethink how we handle knowledge management and companies

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to get the results or to well and this is changing a lot of or should be changing a lot of

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the organizers as well well we every every one of us is going to be an agent boss we will have

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AI teammates that we guide so that's wanting and and then are we going to be managed by AI?

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I don't well not directly at least but AI may be collecting information about

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based based on whatever matrix and usage and whatever we utilize and then

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10 providing that information to our superiors and then they might take a guide us of course

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how to how to work better there so the pace is going to be faster of course and

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that everybody needs to utilize AI so we can well keep up the pace we won't be able to

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walk through it again we need to fly and the AI is going to be our rocket there so

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enable us to collect and manage and handle information in much more faster pace than before

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and for management it's it's called to bring challenges and perhaps some organizations will be

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less hierarchical in the future we don't know we we at Sula where we are changing our

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organization as well to become better suited for AI first and AI native work what we are doing

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so perhaps not just replacing everything but the but more every organization needs to think

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do they need to restructure the way they are doing things so they can fully utilize AI in more

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phases than before and and that's a big change and that change is going to affect a lot of people

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and 10 organizations need to be prepared for another yes change management

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there they need to adapt in these new ways of working and there people are going to need help

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but at this they will need to people

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there are I think when I train AI and I have so many options in the Microsoft space I have

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one node loop co-pilot page that I think it's something new I don't know notebooks

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SharePoint where should be stored information and and how we can get a good oversight

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where we find what or how co-pilot should use information

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okay yeah that's that's a question a lot of people are struggling but I think it's also up to the

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organization a bit for some people I keep people in the organization should be aware about

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these all new tools and then products that are available and what are their capabilities

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and they could be instructing people again we are back to the change management there

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is is how what is the which of these tools should be used and when or at least provide some

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guidelines for employees so not every employee has to go through making those diseases

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then if that happens then information will be scattered all around

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at the max of 365 if we are lucky if we are unlucky they are using their shadow IT tools

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about that but let's stick to the max 365 and then tools you mentioned so Microsoft is creating new

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tools and and some of the tools are going to be and and more and more AI needed as well like

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the way they are constructed how they are storing information is making it also easier for co-pilot

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to utilize the device as well so one of those these new capabilities are co-pilot pages and not

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loose and they've been there for some time well you mentioned loop while pages and notebooks are

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based on loop that they are using the loop framework there and not the platform and you

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did utilizing the same resources so the co-pilot pages is something that you can use to materialize

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your conversation result with when you have it with co-pilot so you can generate the page

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page copy information there and enter it's just a loop page in that sense you have the same

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capability as loop so that's the place okay I'm having this conversation so instead of me copying

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everything manually to somewhere I'm just putting it to the pages I can ask co-pilot to create

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do something and create a page already about that so I don't have to even tell it to move that

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the information to pages but it's just hey I need you to create a page about this so I can

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me and my colleagues can start editing so instead of for example I have the results I go there

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co-pilot create a word document paste everything the word and whenever something changes which

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co-pilot when I'm talking of again copy-pasting that the word well that's something you can do

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but I think ten and ten you save your word somewhere and invite your colleagues to

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collaborate with the results but it's kind of feels like okay you have some extra steps there

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so that's where co-pilot pages kind of jump in when you can hey I'm going to put this information

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here invite my colleagues already I don't have to copy based information and I can still work with

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co-pilot ask if I had content there edit content for example it could be asked okay restructure this

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document or my page so that okay it's rewritten in certain tone totally and and when you have

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in R in a certain level of the result ten you continue working there any word by asking

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the tool to convert the page to word document so so I think that's that's kind of a spot where it

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hits on but yeah you can think about okay what about I could be doing that in one note well yes

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but you would be copying that information to the one note page and doing it there so

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and co-pilot in one note doesn't have all those capabilities like what you can get through the co-pilot

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itself and then when using co-pilot pages but then ten the notebooks are the newest of these

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and notebooks is used to kind of collect information to the let's say to the scrapbook or folder

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so I have this scrapbook about something a topic and then I collect their information that's

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relevant to that topic perhaps I perhaps it's a project and I result going through some planning

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on okay how we are going to what kind of configuration we need to do for our max 365 environment so

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we can utilize co-pilot safely and securely and and so on so that would be IT for a notebook or IT

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people and then they could be having color conversations with co-pilot generating pages to the

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notebook or adding existing pages to the notebook then perhaps adding some external links there

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and documents and so on so you get all that information to the one place and then use

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co-pilot to a regional work at data so it would be similar like you have yes you could do this in one

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note mostly so you have one notebook where you have sections you have pages and then you

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collect that information there fine and that's that's the same thing but the next step is that when

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you start to use AI the reason over your notebooks and and or the data in your notebook

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or you are getting that summary automatically you can generate even audio brief of that notebook

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what is this all about and talk with co-pilot about that contents of the notebook they're adding new pages

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so that's when when you start to realize hopefully that you are using AI all the time when you're

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working there with note one note you are working like human first approach you are creating those

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pages there you are copying the links there yes it's good for some it has a very good structure

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it has the sections and you can put pages there and so so you can have a good notebook there

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and and collect the information and the sharing is to external users is easier users is easier than

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with co-pilot notebooks and but then but it's still a page it's a very old way of working and nowadays

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we have started to see the one note application you can find the co-pilot notebooks there so

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they are coming closer in that sense and supporting both ways of working one note hasn't really

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long history so I don't so I would be surprised if they kind of removed the product

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and it has it has a tools and capabilities that the notebook doesn't have so that's when you

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have to kind of a thing okay which tool to use when in in what kind of scenarios and have

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those clear but I got a lot of organizations are using both because they can have different

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usage even when it feels at first question that they are overlapping and back and kind of they are

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overlapping but they are not overlapping fully so so you can't think about okay what is the need

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and then of course it's making it using one note doesn't mean that you won't be able to utilize

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information everywhere because co-pilot can understand one note pages at least to be

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understood and remember right now can you can understand the one note notebook concept and everything

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there but at least the pages were there I think loop are yeah a long time there was loop and now loop

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gets a little bit more famous through co-pilot and you are an MVP I don't know if you

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you probably be willing to speak about one do you think loop becomes the new center of collaboration

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in the future and loop is going to be basis for for different tools definitely like co-pilot pages

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is based on loop co-pilot notebooks are based on basically look workspaces they're getting new

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features there but the technology behind the scenes is there so and and the loop has the benefit

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because it's based on on the loop framework is that you can when you are updating information it

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can be simultaneous so it's really truly synchronized work like when when you are working with

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much work it's it's fast to think or if you have 1080 torsters it's fast to think but it's not as fast

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as loop because it's the loop is instantaneous and the way you are sharing loop come you can

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share those pages as components directly to teams chat you can drop them to the whiteboard you

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can put them to the email and then working the same but the same content from everywhere so

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that's the power of loop so loop has these capabilities with co-pilot pages can then

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leverage on it and if you are working with one node or you have been working with shared one nodes

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and one node typically we at least I have noticed that there there has been a lot of synchronization

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issues with one node so the syncing one node that's not as fast it's slower and so on so loop is

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loop going to be the new collaboration tool no and not directly but things based on loop will be

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there I would not be sure if for example word would get loop capabilities there it's a different

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way of they are storing things so I'm not sure that would happen but as the idea why not there

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would be a word that's going to be utilizing the power loop when it's generating information

398
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or when you are adding documents and so on so just kind of an example of where it could be utilized

399
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while we have seen the loop components in planner plans so AI can generate those

400
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they can have the planner agent can create task results generate loop content to the loop component

401
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and then you can take it further and edit it or you can ask it for to generate a weekly summary

402
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and it could be a loop component as well so embedding this content management kind of while

403
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not saying content management but this collaboration capabilities into different applications where

404
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you can work with AI and you can look at humans at the same time at the same context and then

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in the same time so that's where we will be seeing loop and more and more but it's going to be

406
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probably while before it's kind of changing any of the bigger the applications but using loop as kind of

407
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the powering framework there that's or platform that's that's what I would kind of I don't know if I

408
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well that's I would say okay that might happen but so let's see if that happens

409
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but yeah but then we work a little bit from an I say classic documental document thinking to

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an dynamic knowledge space thinking and this is the future for your person.

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Yeah yeah of course let's say if the loop capabilities would be in word

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then a lot of word capabilities would still have to be available or basically all these capabilities

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that are currently in word and so that's probably not going to be the first application that's

414
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going to get that update or change and so yes we need still traditional document management we

415
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still need that those kind of refined processes for for for for this we need to have the

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version controls while loop has those as well but we need to be able to manage in many many

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different ways so and when we are creating that content and of course there's co-pilot in word as

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well that can co-create information with us they edit with co-pilot at a earlier known as

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agent mode that's of course it's able to generate and change content in word directly and it can

420
00:44:52,320 --> 00:44:58,480
also do a lot of things like you can talk ask it to change headers and fooders so you are getting

421
00:44:58,480 --> 00:45:06,240
more and more AI capabilities directly into these applications as well but that that so

422
00:45:06,240 --> 00:45:10,240
it AI can be there but then it's not just going to be the loop

423
00:45:10,240 --> 00:45:21,920
um okay when when I let it think about what all change so can you give

424
00:45:21,920 --> 00:45:27,120
view how do you personally use co-pilot in your daily work

425
00:45:29,840 --> 00:45:39,840
well how I use co-pilot in my daily work for for for a lot of things like of course I use it to

426
00:45:39,840 --> 00:45:49,040
collect and discover ideas like when I'm creating something or updating something I need to get up

427
00:45:49,040 --> 00:45:57,680
to date about information ESI I'm using co-pilot and then co-work of especially as well nowadays to kind of

428
00:45:58,720 --> 00:46:05,520
to get me to information I like co-work because it can generate the small details as that tasks

429
00:46:05,520 --> 00:46:11,840
and I can just put it running there and I can't do something else all right and I'll open another

430
00:46:11,840 --> 00:46:17,680
co-work session and start ask it to do something else as well so so they would be running parallel

431
00:46:17,680 --> 00:46:22,480
when I'm doing something else so I don't have to kind of accore through questions and answers all

432
00:46:22,480 --> 00:46:31,920
the time or ask smaller things but then co-pilot is a is there to help me out okay I may want to

433
00:46:31,920 --> 00:46:40,400
start and go through the customer requirements or or checking out okay how out this would be

434
00:46:40,400 --> 00:46:47,920
matching my thinking or of course asking to generate the first sort of those results but

435
00:46:47,920 --> 00:46:56,480
in what do we talk about co-pilot it's it there are different co-pilots so so when I'm talking about

436
00:46:56,480 --> 00:47:02,320
with co-pilot chat I'm just having this conversation there I can have these questions and answers

437
00:47:02,320 --> 00:47:09,520
with the expiring partner and and checking through documents summarizing information or giving me

438
00:47:09,520 --> 00:47:16,720
information throughout different m3.65 so that's that's where I use it quite a lot to kind of

439
00:47:17,360 --> 00:47:22,480
to stay up to date about things and then making sure that I have the reason to question or

440
00:47:22,480 --> 00:47:30,000
when I'm discovering information I need that to but then I'm using when I'm working with a

441
00:47:30,000 --> 00:47:39,280
bird document or PowerPoint I'm of course using co-pilot in those but but they usually so when I'm

442
00:47:39,280 --> 00:47:44,480
starting to work about a new presentation for example then when I pull

443
00:47:45,600 --> 00:47:54,160
this they score the co-work directly so I will I use co-work to gather the information the the

444
00:47:54,160 --> 00:48:00,240
spark to have with the information to get all the information I need for the presentation

445
00:48:00,240 --> 00:48:08,000
discover perhaps some existing presentations or so on and then I will ask you to generate the first draft

446
00:48:08,000 --> 00:48:15,280
using our Solavamiya templates so and and it's getting a lot better there all the time so

447
00:48:15,280 --> 00:48:22,880
you will need to create some personal skills there I use it to stay up to date so I have for

448
00:48:22,880 --> 00:48:29,360
example this collect information about what's happening in the world of AI and deliver that to my

449
00:48:29,360 --> 00:48:36,560
email every day and yeah it's coming to email not to teams but we still still need email for something

450
00:48:36,560 --> 00:48:42,160
and it's really easy to read it from the phone then when you have just the email there I don't have to

451
00:48:42,160 --> 00:48:48,320
go through my team's message history be read it and it's just something okay what has happened

452
00:48:48,320 --> 00:48:56,080
and I have another agent for that as well and that's collecting information from my 365 road maps

453
00:48:56,080 --> 00:49:03,120
and message chander together and giving me a summary about what's happening so I can stay up to date

454
00:49:03,120 --> 00:49:09,760
more or less and because there's a lot of changes going you would have been a summarize about what's

455
00:49:09,760 --> 00:49:17,520
going on so those are the couple of examples but and one more I want to emphasize is that

456
00:49:17,520 --> 00:49:23,760
because I'm doing a lot of demos for customers and and we all know how difficult it is to come with

457
00:49:23,760 --> 00:49:32,480
a demo scenario or those prompts or or documents that are required for example hey I need a new

458
00:49:32,480 --> 00:49:42,720
industry I have now let's say I'm getting a and well let's use the oil industry or that's a

459
00:49:42,720 --> 00:49:51,360
finance where I'm talking to and last time I was talking to so IT for example and I create use case

460
00:49:51,360 --> 00:49:57,840
examples so the easiest way to get started is okay this is what we already know so we can again

461
00:49:57,840 --> 00:50:04,960
generate customer specific demos quite fast so I can ask you to generate documents

462
00:50:04,960 --> 00:50:13,120
access, power coins, PDFs that support this I've used it to generate my conversations to the teams

463
00:50:13,120 --> 00:50:20,480
so I can just in that case I have to use copy because I wanted that to be a demo environment

464
00:50:20,480 --> 00:50:27,200
but in which code work I could ask you to start sending messages directly to teams as well

465
00:50:27,760 --> 00:50:34,080
but then so if I used code work in the demo environment I would probably post at least some of those

466
00:50:34,080 --> 00:50:40,640
directly through the code work but since I want to have a conversation in teams I'm using a

467
00:50:40,640 --> 00:50:47,680
couple of demo accounts and so on but point this and code work can generate those tricks for me

468
00:50:47,680 --> 00:50:56,000
so it can generate okay post these things there's a there's now a guideline like a something

469
00:50:56,000 --> 00:51:02,400
reasonable about the demos some code some tasks that I can go through and it was such as some prompts

470
00:51:02,400 --> 00:51:09,440
for me and that I can use with those documents create it has really changed the way I'm doing demos

471
00:51:09,440 --> 00:51:17,200
because earlier I had like a usually you just can generate it the bare minimum for demos

472
00:51:17,200 --> 00:51:24,960
but now you can you can have like multiple documents you can have kind of conversations there and

473
00:51:24,960 --> 00:51:30,720
just copy-pasted information to the demo and then I'm basically ready to go

474
00:51:30,720 --> 00:51:37,840
test run it first of course but it's still kind of that quite quickly ready to go

475
00:51:37,840 --> 00:51:44,480
and it's and it's can suggest kind of a for example okay what you are asking from those

476
00:51:44,480 --> 00:51:50,800
documents because code work and understand why very very large concepts so the context and

477
00:51:50,800 --> 00:51:57,440
understanding is a lot better so and then of course it applies the other way around the why I do those

478
00:51:57,440 --> 00:52:04,400
is that customer can't see okay this is how you could be using code work so it could analyze okay we

479
00:52:04,400 --> 00:52:09,200
have this have you ever tried to generate a demo document with 20,000 lines

480
00:52:09,200 --> 00:52:19,440
but you can do it at easily with code work okay so you can then you can answer questions like okay we

481
00:52:19,440 --> 00:52:26,080
have a lot of information in our excursion and this managing yes there's 20,000 lines in that

482
00:52:26,080 --> 00:52:36,160
excel and I can ask for it to provide the information from there and then of course how you want to do

483
00:52:36,160 --> 00:52:41,360
it or you want to demonstrate edit with excel there they are and edit with code while at the

484
00:52:41,360 --> 00:52:48,080
excel and 10 you can get a similar experience okay yes it can reason over that data and then

485
00:52:48,080 --> 00:52:54,000
provide the results the cloud models have changed and some big cloud models have changed this

486
00:52:54,000 --> 00:53:02,720
very very much yeah thank you this was was an awesome session thank you for your time can you

487
00:53:02,720 --> 00:53:08,000
what is the one thing the people should take away from from our session today

488
00:53:10,480 --> 00:53:18,400
wanting try code work I think that's the biggest thing at some moment and

489
00:53:18,400 --> 00:53:28,400
try true code work and but anyway hopefully true code work and because yeah it's just

490
00:53:28,400 --> 00:53:34,800
it can provide fantastic results and it can feel in the promise it's starting to feel in the

491
00:53:34,800 --> 00:53:42,240
promises I co-pulled it in the minds of people for a few years back and and it can get a lot

492
00:53:42,240 --> 00:53:48,960
of luck done so that's why I would say yeah use it to organize your inbox or organize your

493
00:53:48,960 --> 00:53:57,040
fives on your one drive like I had the screensatz folder and I wanted to organize it so that I can

494
00:53:57,040 --> 00:54:01,600
still find some of the older screensatz so I wanted to be in the monthly

495
00:54:02,800 --> 00:54:09,280
a monthly folder so thank thank you so much for the session this was really great so bye

496
00:54:09,280 --> 00:54:13,600
thank you bye bye