Speaker 1: This is Bloomberg Business Week with Carol Messer and Tim
Speaker 1: Stenebek on Bloomberg Radio. All right, Zoom was certainly an
Speaker 1: indication of how we were working during the pandemic. But
Speaker 1: we've really leaned on the team over at Microsoft three
Speaker 1: sixty five for how we are working, yes, then, but
Speaker 1: also today, and they've got a new report out that
Speaker 1: finds that there's not necessarily any need to be worried
Speaker 1: about AI. Of course, to be fair, Microsoft is deep
Speaker 1: into AI, really awakening the world earlier this year with
Speaker 1: its ten billion dollar investment into Open AI's chat GBT.
Speaker 1: So even so, our next guest is here to help
Speaker 1: answer the question will AI fix work? And great to
Speaker 1: have back with us. Jared's Pataro. He is Corporate VP
Speaker 1: of Modern Work and Business Applications at Microsoft three sixty five.
Speaker 1: Once again on Zoom in Redmand Washington. Jared, how are you.
Speaker 2: Oh, I'm doing great. Great to be back with you, Carol.
Speaker 1: Yeah, great to have you here with us. So tell
Speaker 1: us about this inquiry into AI? What you guys?
Speaker 2: I mean?
Speaker 1: The question is I've got the report in front of me,
Speaker 1: Will AI fix work? And I think everybody's trying to
Speaker 1: figure it out. I kind of can't wait because I
Speaker 1: think it can be an assist in my job. But
Speaker 1: tell us about what you looked into, questions you asked,
Speaker 1: and who you talk to.
Speaker 2: Maybe let's look at what's broken first. So this particular
Speaker 2: survey is our annual survey thirty one thousand people across
Speaker 2: thirty one countries, and the first number that popped out
Speaker 2: to me is exactly that fix that's needed. Sixty four
Speaker 2: percent of people who responded told us that they just
Speaker 2: don't have the time or energy to get their jobs done.
Speaker 2: And we thought that that was really interesting. Coming out
Speaker 2: of the pandemic. People are tired, but it seemed to
Speaker 2: be more than that. So we combine that with our
Speaker 2: telemetry data. This is the cloud data where we see
Speaker 2: how people are working, what they're up to. We found
Speaker 2: that up to about sixty percent of the average day,
Speaker 2: average workers day is spent communicating and coordinating. Only forty
Speaker 2: percent is kind of spent on that day job, the
Speaker 2: thing that they're supposed to provide to the organization. So
Speaker 2: really interesting setup right now as people are feeling tired
Speaker 2: and for good reason.
Speaker 3: And Jery something that strikes me anytime I talk to
Speaker 3: anyone they're always concerned about when it comes to AI,
Speaker 3: maybe they could attenduly be replaced when it comes to
Speaker 3: their job. Looking at your study, it's interesting as far
Speaker 3: as how AI is poised to create this whole new
Speaker 3: way of working, what would be the counter to that,
Speaker 3: and the benefits of AI were you might not necessarily
Speaker 3: be losing your job, but it can actually assist you.
Speaker 2: Well, we'll start with the fear. There's still a little
Speaker 2: bit of fear there. Almost fifty percent, it was forty
Speaker 2: nine percent of people who responded told us that they
Speaker 2: were afraid that AI would come and take their job,
Speaker 2: but that was overshadowed by another number, a whopping seventy
Speaker 2: percent told us that despite that fear, they actually would
Speaker 2: outsource everything they could to an AI assistant just to
Speaker 2: help them relieve the burden. So there's this sense that
Speaker 2: their optimism, or at least their need for help for
Speaker 2: AI based help, really outweighs their fears. And that's a
Speaker 2: pretty interesting nuance on many the headlines that we've been
Speaker 2: hearing for the last couple of months.
Speaker 1: Well, I'm thinking about email alone. I mean, I'm going
Speaker 1: to be quite honest with you. There's a ton of
Speaker 1: email that I never even get to read because it's
Speaker 1: just a ton of stuff that people are either pitching
Speaker 1: or research. And I definitely have figured out ways to
Speaker 1: kind of weed through do certain searches so that I
Speaker 1: really make sure I don't miss some of the important stuff.
Speaker 1: But how could AI ultimately help us in filtering through
Speaker 1: what is dumped into our email boxes on a regular basis.
Speaker 2: Well, many of your your listeners are probably familiar with
Speaker 2: chat GPT, introduced last year, and it's particularly good, it's summarizing,
Speaker 2: and so I've been using a product that we call
Speaker 2: Copilot Microsoft through sixty five copil it essentially takes the
Speaker 2: models behind chat GPT, these large language models and integrates
Speaker 2: it directly into your email into Outlook. And this does
Speaker 2: amazing things. It allows you, for instance, get a long
Speaker 2: those long email threads where you're supposed to go read
Speaker 2: from the bottom up, and it can summarize that just
Speaker 2: in one click. And then once it's summarized, it actually
Speaker 2: gives you a couple of different prompts or those are
Speaker 2: different things you can choose from to answer, so it
Speaker 2: will author an answer, allow you to make it longer, shorter,
Speaker 2: more formal, more casual, it is changed the way I
Speaker 2: do email. I never want to do email without it again,
Speaker 2: so it definitely changes work habits and practices.
Speaker 1: Well, so just just share with me, because, like I
Speaker 1: said at the top, I mean to be fair. You
Speaker 1: guys are all in on AI, no doubt about it.
Speaker 1: And in many ways that news of the Microsoft investment
Speaker 1: really did kind of wake up the world in terms
Speaker 1: of what you folks were doing. Specifically, Now everybody's talking
Speaker 1: about it. As you guys have been playing around with it,
Speaker 1: what are you finding are the great capabilities? What are
Speaker 1: still the things that need to be worked out?
Speaker 2: The five seconds to wow type demo I do with
Speaker 2: customers is in a meeting. So in a meeting like
Speaker 2: this that would be just a normal business meeting, we're
Speaker 2: trading kind of conversation back and forward. And what it
Speaker 2: can do there is it can literally listen in as
Speaker 2: if it were an assistant to the meeting and summarize.
Speaker 2: That means it can write notes. It can respond when
Speaker 2: I ask questions like what did Carol say again? Or
Speaker 2: how did Jared answer this question? It can allow me,
Speaker 2: for instance, to identify, you know, what are the two
Speaker 2: sides of this argument and who's in favor of which
Speaker 2: one it actually is incredibly valuable in a meeting. And
Speaker 2: then even better than that, Carol, the thing that I
Speaker 2: love is it allows me to attend meetings, so I
Speaker 2: can not attend a meeting and then using that same
Speaker 2: GPT larg language model, query the meeting after the fact,
Speaker 2: did they ever mention my name or any decisions made?
Speaker 2: What decisions? Why did they make them? So it opens
Speaker 2: up these brand new possibilities for work because it kind
Speaker 2: of blurs time and space. You know, it's as if
Speaker 2: you could be there, but you're not there, and you're
Speaker 2: able to use the power of AI here to kind
Speaker 2: of get into the dynamics of people even just having
Speaker 2: regular conversations. So just one example, but it's integrated across
Speaker 2: all of our products. We talked about email or PowerPoint,
Speaker 2: all of those things.
Speaker 1: What's the thing though, that is still tricky because we
Speaker 1: talk about AI kind of working alongside of us and
Speaker 1: we don't have to go to the meeting Yahoo. But
Speaker 1: I do wonder what are the things that you know,
Speaker 1: people say you can't really you know, duplicate a human
Speaker 1: in terms of their perception of things and so on
Speaker 1: and so forth. So what do would you say that
Speaker 1: we still need to be cautious about or we're still
Speaker 1: figuring out, or you guys are still figuring out when
Speaker 1: it comes to this.
Speaker 2: Very stud question, because it turns out while these things
Speaker 2: are incredibly useful, they do make mistakes. And these things,
Speaker 2: I mean the AI assistance that we have, so they
Speaker 2: get it wrong sometimes. In fact, the technical term is hallucination.
Speaker 2: If you believe that, that literally is the term they
Speaker 2: make stuff up. So the reason that we use copilot
Speaker 2: as a name for our product is really the signal
Speaker 2: to the user, hey, this is an autopilot. You can't
Speaker 2: just take the answers and say there you go, I'm
Speaker 2: going to fire this off as an email. You really
Speaker 2: have to be in the driver's seat. You have to
Speaker 2: make the decisions. But the great news is my experience
Speaker 2: has been when it is wrong, it's what we call
Speaker 2: usefully wrong. So it doesn't just make things up. To
Speaker 2: make things up. Sometimes we'll feel in details where it
Speaker 2: didn't have all the data. You can go in and
Speaker 2: correct that, tweak that, and then it's put you ahead
Speaker 2: of the game anyway.
Speaker 3: So how long do you think this could take? But
Speaker 3: before it's more widespread with users that could potentially use
Speaker 3: this type of things in meetings when you do have
Speaker 3: still some of these hiccups and glitches that could happen
Speaker 3: with AI.
Speaker 2: We just introduced a couple of weeks ago that we're
Speaker 2: expanding what we call our Preview program to six hundred
Speaker 2: enterprises around the world, so we'll have hundreds of thousands
Speaker 2: of users here in the coming months. So that's kind
Speaker 2: of the scale that it's out right at right now.
Speaker 2: But it's moving very quickly. My team, we talk about
Speaker 2: AI time, the cycle time of the industry has really
Speaker 2: increased as we're able to build on top of these
Speaker 2: technologies really quickly. So I don't think it'll be a
Speaker 2: matter of years. I do think it'll be a matter
Speaker 2: of months until you start to see these tools being
Speaker 2: used all over the place.
Speaker 1: You know, for someone who has been you know, focusing
Speaker 1: on workplace trends and coming off a really crazy period,
Speaker 1: you know, meaning the pandemic specifically, and we're able to
Speaker 1: track a lot of things. How are you kind of
Speaker 1: placing generative AI machine learning in kind of I don't know,
Speaker 1: is it akin to some other great or interesting development
Speaker 1: in terms of how we work, Like, how do you
Speaker 1: position it historically or technologically for that matter.
Speaker 2: We think it's as big as the PC revolution or
Speaker 2: as big as the Internet. We think it's that big.
Speaker 2: You know, if I again frame it, we would say, Wow,
Speaker 2: you couldn't write a script like this if you were trying. Really,
Speaker 2: what the pandemic did is is rewire the where and
Speaker 2: the when of work, So it changed entirely around the world.
Speaker 2: You know, those two mentions of work. All of a sudden,
Speaker 2: AI is changing the how of work. By the time
Speaker 2: we get kind of roughly four years out from the pandemic,
Speaker 2: the combination of those two things will have really just
Speaker 2: changed patterns practices associated with work. My kids, as they
Speaker 2: go to work, they're not going to enter a work
Speaker 2: environment anything like I did you know twenty five years ago?
Speaker 1: Is that good or bad? Bodily because you know, things
Speaker 1: are never right black and white like it's it's that's right.
Speaker 1: We're worried about people not really talking to each other.
Speaker 1: I have a colleague, Matt Miller, who laughs that when
Speaker 1: we all get on a zoom call and we're literally
Speaker 1: like right next to each other, but I'm sitting there typing,
Speaker 1: you know, notes, and you know, it's just interesting.
Speaker 2: My response to that is I would say, you know,
Speaker 2: AI giveth an, AI taketh away, Like, we have this
Speaker 2: moment and the way we think about it is what
Speaker 2: have we gained and what have we lost? And how
Speaker 2: do we lose as little as possible and how do
Speaker 2: we gain as much as possible? But you're exactly right,
Speaker 2: these big if it's as big as the PC, you know,
Speaker 2: if you really believe that it's that type of shift,
Speaker 2: then you do have to recognize, Wow, this is probably
Speaker 2: the beginning of an era, a new era, which is
Speaker 2: be really thoughtful about what we want to make sure
Speaker 2: we don't lose in that process. But that will take
Speaker 2: all of us, you know, we're all learning as we go. Yeah.
Speaker 1: Right, And the more we use it though, right, the
Speaker 1: smarter or more specific it becomes. Jared, Nice to check
Speaker 1: in with you again. Jared's Pataro. He's corporate vice president,
Speaker 1: head of Modern Work at Microsoft three sixty five on
Speaker 1: Zoom from Redman, Washington. Yeah, I feel like.
Speaker 3: I have that same email problem as you, Carol.
Speaker 1: It's crazy. Now. I've said to this though a million times,
Speaker 1: like I've thought about AI the ability to you know,
Speaker 1: I like to write kind of intros into our guests
Speaker 1: and stuff, and just the ability to maybe shoot some information,
Speaker 1: say here, just draft something, I'll edit it. I'll go
Speaker 1: through it and make sure it's But to kind of
Speaker 1: have that framework to try to kick off with would
Speaker 1: be really cool. Yeah.
Speaker 3: Yeah, all my distribution lists that I'm on for banks,
Speaker 3: I
Speaker 1: Just like to filter through staff like, would be really
Speaker 1: kind of cool.