Latest / The DEX Show: A Show for IT Change Makers / 🎉 200 EPISODE ANNIVERSARY SPECIAL! PEDRO BADOS RETURNS!

Transcript

🎉 200 EPISODE ANNIVERSARY SPECIAL! PEDRO BADOS RETURNS! · The DEX Show: A Show for IT Change Makers

• 0:01
  Speaker 1: Welcome it, change Makers to the Deck Show with Tim
• 0:05
  Speaker 1: Flower and Tom McGrath. Let's get into it.
• 0:09
  Speaker 2: For the two hundredth time, change Makers to the two
• 0:12
  Speaker 2: hundredth time. Hello, Hello, and welcome to this very very
• 0:16
  Speaker 2: special episode of the Deck Show. I'm Tom McGrath. I'm
• 0:19
  Speaker 2: joined as ever as ever as ever by Tim Flower.
• 0:22
  Speaker 2: How are you doing, Tim, Happy two hundredth anniversary.
• 0:24
  Speaker 3: You never would have imagined, Tom, that we'd get two
• 0:27
  Speaker 3: hundred episodes.
• 0:29
  Speaker 2: When I first approached you. I bet you know, I said,
• 0:31
  Speaker 2: do you want to do a podcast? I bet you
• 0:32
  Speaker 2: didn't think, oh yeah, in two hundred episodes, we'll still
• 0:35
  Speaker 2: be running.
• 0:36
  Speaker 3: And the idea of the podcast has been floating around
• 0:38
  Speaker 3: for a little while, and it was always kind of this,
• 0:40
  Speaker 3: would anybody really listen? But it's cool. We got an
• 0:43
  Speaker 3: audience and the reason to keep doing.
• 0:44
  Speaker 2: It, and we said in last week's episode, but we
• 0:48
  Speaker 2: had all this kind of all of these like momentous
• 0:50
  Speaker 2: anniversary milestones flying about it. Once we had your your
• 0:55
  Speaker 2: recent big birthday, you know, as you said, as a
• 0:58
  Speaker 2: zero involved, we actually take your anniversary. We've got a
• 1:01
  Speaker 2: two hundred episode. And then of course we had this
• 1:04
  Speaker 2: incredible news about the the new majority stake investor in
• 1:09
  Speaker 2: Next Thing. These directity partners coming in really changing the
• 1:12
  Speaker 2: whole nature of the of the Deck sector. And we
• 1:16
  Speaker 2: thought that what better, guest, what better way to mark
• 1:20
  Speaker 2: this momentous period in the show's history and Next Thing's
• 1:22
  Speaker 2: history and the history of Dex and to welcome back
• 1:25
  Speaker 2: onto the show Next Thing co founder and CEO Pedro
• 1:28
  Speaker 2: about us our boss. Welcome back to the show, Pedro,
• 1:31
  Speaker 2: your third or fourth appearance. I think what a time
• 1:33
  Speaker 2: to have you back on set.
• 1:35
  Speaker 4: Thank you very much at Tim and Tom and congratulations
• 1:37
  Speaker 4: two hundred podcast.
• 1:39
  Speaker 5: That's incredible.
• 1:40
  Speaker 4: I remember the first one, you know, and the niche
• 1:44
  Speaker 4: idea right about the Deck show and all that, and
• 1:47
  Speaker 4: here we are two hundred and you are true true
• 1:50
  Speaker 4: celebrities of Dex.
• 1:51
  Speaker 5: On top of that, celebrities that's a relative.
• 1:58
  Speaker 2: Sometimes feel like it. And Petra huge, huge congratulations on
• 2:03
  Speaker 2: the big big news from Next Thing. Just just a
• 2:05
  Speaker 2: about a week hold, isn't it in terms of the announcement.
• 2:08
  Speaker 2: What is the period of time being like to you?
• 2:11
  Speaker 2: I just would have you did mention to me, it's
• 2:13
  Speaker 2: a bit like having a baby. The whole process it
• 2:15
  Speaker 2: resembled it a little bit.
• 2:18
  Speaker 4: Yeah, I mean certainly there are news. I don't know
• 2:20
  Speaker 4: if there are big news. This part of the cycle
• 2:23
  Speaker 4: of every company. So we are changing shareholders every four
• 2:27
  Speaker 4: or five years. So we had tremendous shareholders, really great
• 2:32
  Speaker 4: people that they were with ask for sometimes ten years,
• 2:36
  Speaker 4: sometimes five years, and they did their they did their job,
• 2:41
  Speaker 4: and you know, the company grew and we got to
• 2:43
  Speaker 4: a point which we're going to we want to go to.
• 2:46
  Speaker 5: The next step.
• 2:47
  Speaker 4: We're going to grow, We're going to accelerate, and we
• 2:51
  Speaker 4: thought that Vista Partners are the best partners out there
• 2:54
  Speaker 4: to really take the company to the next level. So
• 2:58
  Speaker 4: we are really excited. We thought that we were not
• 3:00
  Speaker 4: ready right now for an IPO. We see the you
• 3:03
  Speaker 4: know the i PO window and you know, still not
• 3:07
  Speaker 4: great for tech companies. And we're gonna stay private for
• 3:11
  Speaker 4: a few more years. We're going to make sure the
• 3:13
  Speaker 4: management team is fully committed and we are all here,
• 3:16
  Speaker 4: and yeah, with the right partner, I think they still
• 3:18
  Speaker 4: will see more acceleration in the in the next thing lascape.
• 3:23
  Speaker 4: So that's that's overall very good news for everybody.
• 3:26
  Speaker 2: Phenomenon, and you know, we're going to focus predominantly on
• 3:29
  Speaker 2: the future of decks, the future of Next Thing in
• 3:32
  Speaker 2: the in this discussion. But obviously we have a lot
• 3:34
  Speaker 2: of customers partners Next Thing is tune into this show.
• 3:38
  Speaker 2: If you had to give them a message about what
• 3:41
  Speaker 2: this news means for the company of a community to
• 3:44
  Speaker 2: tech the future of the technology in miniature, what would
• 3:46
  Speaker 2: that message be.
• 3:48
  Speaker 4: Look, I mean new investors they invest for different reasons.
• 3:51
  Speaker 4: In this particular case, their investment is really based on growth,
• 3:56
  Speaker 4: It's based on innovation, It's based on category leadership, what.
• 3:59
  Speaker 5: They want to do.
• 4:00
  Speaker 4: Uh, you know, with the management team and me personally,
• 4:04
  Speaker 4: still I'm a very important investor in Next Thing. It's
• 4:08
  Speaker 4: really to take it to the next level. I think
• 4:09
  Speaker 4: we are they already fined company, as we will discuss today.
• 4:14
  Speaker 4: AI is just an accelerator of companies with data. I
• 4:17
  Speaker 4: think there are some processes in it and and some
• 4:22
  Speaker 4: things that they're gonna change in the in the years
• 4:24
  Speaker 4: to common. We believe Next Thing is going to play
• 4:27
  Speaker 4: a very important role. And I think these investors they
• 4:29
  Speaker 4: saw the opportunity. Uh you know, it's really interesting because
• 4:34
  Speaker 4: a lot of people internally the Next Thing they are
• 4:36
  Speaker 4: telling me, oh, we want to invest more, can we investigate,
• 4:39
  Speaker 4: you know, alongside these new investors because they see the
• 4:42
  Speaker 4: opportunity from the customer and partner standpoint. Honestly, Uh, there's
• 4:47
  Speaker 4: not gonna be a big change when I continue innovating. Uh,
• 4:51
  Speaker 4: They're gonna be Uh, They're gonna engage with the same
• 4:54
  Speaker 4: teams that they engage within the past. As I said,
• 4:58
  Speaker 4: you know, most of the team this is going to
• 5:00
  Speaker 4: stay here for the next few years or maybe all
• 5:02
  Speaker 4: the team. So we are really not much changed from
• 5:05
  Speaker 4: that perspective.
• 5:07
  Speaker 2: And you just alluded to it, you know, the testament
• 5:10
  Speaker 2: to how much opportunity people who know people who invest
• 5:15
  Speaker 2: ce in decks at the moment and just before this
• 5:17
  Speaker 2: is a springboard really to tim leading us into a
• 5:19
  Speaker 2: discussion about the future of the technology and the future
• 5:22
  Speaker 2: of innovation. Here to what extent do you see AI
• 5:26
  Speaker 2: as having impacted the potentiality around decks as it's perceived
• 5:31
  Speaker 2: by investors, is perceived by people who kind of try
• 5:35
  Speaker 2: and measure the future of technology.
• 5:39
  Speaker 5: Look AI.
• 5:41
  Speaker 4: My perspective on AI is AI is a way to
• 5:43
  Speaker 4: automate more and better and probably quicker many areas right
• 5:49
  Speaker 4: in our daily lives, especially digital areas with LMS and
• 5:53
  Speaker 4: all that. But this has happened throughout the years with
• 5:56
  Speaker 4: the induce straight revolution, with computing with uters, it was
• 6:01
  Speaker 4: all about automation, and obviously for the first time we
• 6:04
  Speaker 4: see that we can automate a lot of things. Right
• 6:06
  Speaker 4: when we can automate or of search and of decide,
• 6:10
  Speaker 4: we have a coach with chupt which is giving us
• 6:13
  Speaker 4: the result. We can automate probably service desk. We can
• 6:16
  Speaker 4: automate probably a customer service.
• 6:19
  Speaker 2: Right.
• 6:19
  Speaker 4: There are things like that that we see really the
• 6:22
  Speaker 4: potential for automation. When it comes to the XX the
• 6:29
  Speaker 4: there is a tremendous opportunity because first we are a
• 6:32
  Speaker 4: data company and secondly we are a company that the
• 6:35
  Speaker 4: mission is really a data reception between people and technology
• 6:38
  Speaker 4: and to make things more effectively, to automate how people
• 6:42
  Speaker 4: they work with digital applications. So obviously there are immediately
• 6:47
  Speaker 4: there are two opportunities. One is really to democratize dex
• 6:52
  Speaker 4: and to give it to people that maybe before it
• 6:54
  Speaker 4: was too difficult for them, like HR, like network, like security.
• 7:00
  Speaker 4: There are lot of people now, for instance, that they're
• 7:02
  Speaker 4: in charge of AI adoption in companies that of the
• 7:06
  Speaker 4: sudden they start using next thing because we put AI
• 7:08
  Speaker 4: top and they therefore they can really use it. Many
• 7:13
  Speaker 4: you know, many teams in the past they couldn't use
• 7:15
  Speaker 4: next thing data or dex data. Now they can use it.
• 7:18
  Speaker 4: But the second big opportunity or tail tailwind here in
• 7:25
  Speaker 4: dex and plus AI is really the opportunity to give
• 7:28
  Speaker 4: an dex agent to every single employee.
• 7:31
  Speaker 5: And what we call what we talk about.
• 7:33
  Speaker 4: Dex agent is more like an IT agent. So imagine
• 7:36
  Speaker 4: every person in front of a computer has a personal
• 7:40
  Speaker 4: IT manager sitting next to next to them, which is
• 7:43
  Speaker 4: able to answer any question about anything that is going
• 7:46
  Speaker 4: on in any application that they are using, in any
• 7:49
  Speaker 4: device that they are using.
• 7:50
  Speaker 5: Therefore, they don't need a the iity department anymore.
• 7:52
  Speaker 4: Right, they're able to First of all, they're able to
• 7:56
  Speaker 4: not have problems because these systems that will see them
• 7:59
  Speaker 4: and they will fix them for their users they noticed them.
• 8:01
  Speaker 4: But also if there is something they want to ask
• 8:04
  Speaker 4: or if there is any issue, they can ask this
• 8:07
  Speaker 4: agent and they can get it fixed right away. And
• 8:10
  Speaker 4: these are two tremendous opportunities that they are opening up
• 8:12
  Speaker 4: right now with TEX plus AI.
• 8:16
  Speaker 3: So Pedro I like to frame things in kind of
• 8:20
  Speaker 3: a past, present and future context. So I got a
• 8:24
  Speaker 3: couple of topics for us to hit on. When I
• 8:27
  Speaker 3: was I started here ten years ago, back in twenty fifteen.
• 8:31
  Speaker 3: My first all company meeting was in twenty sixteen. I
• 8:33
  Speaker 3: think we were in a couple of conference rooms at
• 8:36
  Speaker 3: the Alpha pamiers. In those on the product was very
• 8:39
  Speaker 3: much AI based and machine learning, but it felt kind
• 8:42
  Speaker 3: of hidden underneath the covers as part of the core
• 8:44
  Speaker 3: of what we did as a product, but it wasn't
• 8:46
  Speaker 3: really exposed to it and certainly not to employees. But
• 8:51
  Speaker 3: let's go back even further. Let's go back another ten years,
• 8:54
  Speaker 3: back to when you were at the EPFL. You fashioned it,
• 8:57
  Speaker 3: and a lot of people talk about the EPFL as
• 8:59
  Speaker 3: the MIT of Switzerland. You were studying AI. Many listeners
• 9:03
  Speaker 3: know how that research evolved into the prototype that became
• 9:06
  Speaker 3: next thing. I know, it feels like AI is new
• 9:11
  Speaker 3: to many people in many ways. But what was your
• 9:13
  Speaker 3: perception of AI at that time, more than twenty years ago,
• 9:16
  Speaker 3: especially in the terms of how you felt it could
• 9:19
  Speaker 3: impact what we call the digital workforce? What was AI?
• 9:22
  Speaker 3: Was your perception of AI twenty plus years ago?
• 9:26
  Speaker 4: Yeah, it's a very interesting question because back in the
• 9:29
  Speaker 4: days twenty years ago to AI researchers, we were playing
• 9:34
  Speaker 4: with other type of technologies. You know, back in the days,
• 9:39
  Speaker 4: the Asian networks, hidden Markov models, reasoning systems, case based reasoning,
• 9:45
  Speaker 4: things like that, they were very popular. Neural networks not
• 9:48
  Speaker 4: so much. And actually neural networks, which is basically the
• 9:52
  Speaker 4: underlying technology of trasformers, which are the main component of lamps,
• 10:00
  Speaker 4: they were somehow mysterious. They were trying to mimic a
• 10:04
  Speaker 4: little bit how the brain works, but obviously computing power
• 10:07
  Speaker 4: was not there. They were, you know, able to do
• 10:11
  Speaker 4: some computer vision use cases and things like that, very
• 10:15
  Speaker 4: primitive type of use cases. But people thought that putting
• 10:19
  Speaker 4: more intelligence into the way that systems are reasoning was
• 10:24
  Speaker 4: really the way to go, while we we just realized
• 10:27
  Speaker 4: with transformers that is not at all the approach.
• 10:31
  Speaker 5: The approach is.
• 10:32
  Speaker 4: Really brute force, you know, to scale with huge amount
• 10:35
  Speaker 4: of data and a huge amount of uh you know, uh power,
• 10:40
  Speaker 4: computing power, that's really the way to go. And you know,
• 10:43
  Speaker 4: in all fairness, transformers there were more a discovery than
• 10:48
  Speaker 4: really an inventure. Right now, what I expected them to
• 10:52
  Speaker 4: really behave in the way that they ended up behaving,
• 10:55
  Speaker 4: and you know, making sense out of you know, prompt
• 10:59
  Speaker 4: and and all these type of things. So I guess
• 11:02
  Speaker 4: nobody twenty years ago in the AI community was expecting
• 11:05
  Speaker 4: that really neural networks, at least the people that they
• 11:08
  Speaker 4: were in our al app at the PFL where you know,
• 11:14
  Speaker 4: we're going to get to the point that they are
• 11:16
  Speaker 4: there today. In the case of next thing, we were
• 11:19
  Speaker 4: using technologies to model and user behavior. They were more
• 11:24
  Speaker 4: hidden Markov models to basically model the task that a
• 11:28
  Speaker 4: person is doing, which is called a hidden model, and
• 11:30
  Speaker 4: then you have observable states. So basically you say, okay,
• 11:35
  Speaker 4: I'm now serving the web, I'm right now working on
• 11:38
  Speaker 4: my emails, I'm now maybe working on a project. These
• 11:42
  Speaker 4: are your healing states, and based on these hiding states
• 11:45
  Speaker 4: that the model is trying to figure out, they are
• 11:47
  Speaker 4: observable observable things that you are doing. Okay, I'm doing
• 11:50
  Speaker 4: this connection, I'm doing this execution, I'm looking at this screen.
• 11:54
  Speaker 4: And therefore you are able to model the normal behavior
• 11:57
  Speaker 4: of people in front of those computers. It's the typical
• 12:00
  Speaker 4: model that you use, for instance and credit card for detection.
• 12:04
  Speaker 4: They emulate if the person is on holidays or here
• 12:07
  Speaker 4: or there, and therefore they're able to predict very different
• 12:11
  Speaker 4: type of models, but also very useful to understand how
• 12:15
  Speaker 4: people they use computers and what is normal and abnormal.
• 12:18
  Speaker 4: So it has changed a lot, and still some of
• 12:21
  Speaker 4: these concepts they are they at the I would say,
• 12:25
  Speaker 4: at the base of the platform of next sic and
• 12:29
  Speaker 4: it's used and it's the way we model data and
• 12:32
  Speaker 4: solve This is still very very important for us.
• 12:36
  Speaker 3: So Nextick as a company has evolved tremendously over the
• 12:40
  Speaker 3: last twenty years. Our product has evolved over twenty years.
• 12:44
  Speaker 3: Has AI evolved the way you anticipated back then? What
• 12:48
  Speaker 3: surprised or impressed you the most about AI's recent rise
• 12:52
  Speaker 3: over the last couple of years, both in general and
• 12:55
  Speaker 3: in terms of its impact to digital workplace and digital workers.
• 12:58
  Speaker 3: What's your common tarry on the evolution of AI.
• 13:05
  Speaker 4: Well, I think, as I said, everybody was surprised with
• 13:11
  Speaker 4: you know, the first EPT three point zero because you
• 13:15
  Speaker 4: know two point two point five, we saw this, Oh wow,
• 13:19
  Speaker 4: this is really a step change, right, this is really
• 13:22
  Speaker 4: something different from everything that we saw before, and now
• 13:26
  Speaker 4: that they was predicting that formers with brute force and
• 13:31
  Speaker 4: at least you know a few years ago it was
• 13:32
  Speaker 4: kind of a discovery for them, for our of people
• 13:36
  Speaker 4: around the world, so obviously I was very surprised. Very quickly,
• 13:40
  Speaker 4: we put a team of people the next thing to
• 13:43
  Speaker 4: really make sure because we thought that this is going
• 13:46
  Speaker 4: to change fundamentally the way people they interact with applications.
• 13:52
  Speaker 4: So they don't need to do a dashboard, they don't
• 13:54
  Speaker 4: need to do a query. They're going to just talk
• 13:56
  Speaker 4: to the system and the system is going to be
• 13:58
  Speaker 4: able to do it. So that's why we were the
• 14:01
  Speaker 4: first solution actually in DX that was able to release Assist.
• 14:06
  Speaker 4: And the first version of assist actually was not very
• 14:08
  Speaker 4: good if you look at the best parts, was actually
• 14:10
  Speaker 4: pretty bad. The second version was already pretty good, and
• 14:14
  Speaker 4: now the third version, I think we are eighty percent
• 14:16
  Speaker 4: and actually they just told me yesterday that actually assists
• 14:19
  Speaker 4: is able to pass all the certifications that we have
• 14:22
  Speaker 4: on the website. We're able to actually get ten out
• 14:25
  Speaker 4: of ten in the MQL coding, so it's really advanced.
• 14:30
  Speaker 4: So I think we did that. We did a good
• 14:32
  Speaker 4: job there in mixing decks and AI, but we continue
• 14:36
  Speaker 4: working a lot on the possibilities. I think again coming
• 14:41
  Speaker 4: back to our new Agents Park, that we're going to
• 14:44
  Speaker 4: give to every single employee. We are just trying to understand,
• 14:48
  Speaker 4: you know, how we're going to make it more personable,
• 14:52
  Speaker 4: more personalized, with other sources of information we need to
• 14:55
  Speaker 4: pull to make sure that we're able to solve every
• 14:59
  Speaker 4: single question that an employee will have in the future.
• 15:02
  Speaker 5: So that's that's that's important. We're very excited about it, honestly.
• 15:09
  Speaker 3: So one thing that science tells us is that evolution
• 15:12
  Speaker 3: never stops. Right NEXTNIK is now evolving into its next age,
• 15:16
  Speaker 3: a new and exciting chapter AI. You could also say
• 15:20
  Speaker 3: that AI maybe is that the birth of the or
• 15:22
  Speaker 3: the dawn of a new age of AI as it
• 15:24
  Speaker 3: continues to evolve. Where do you see AI headed in
• 15:27
  Speaker 3: the future. What's your vision of AI shaping the world
• 15:31
  Speaker 3: of not only enterprise IT employees, but all employees that
• 15:35
  Speaker 3: are interacting with the digital workplace. What are things going
• 15:38
  Speaker 3: to look like for them in the future.
• 15:40
  Speaker 4: Look, and I'm part of the group of people that
• 15:44
  Speaker 4: you know, we're I'm quite optimistic about AI. I'm quite
• 15:47
  Speaker 4: optimistic about the capabilities and the potential of AI. Like
• 15:52
  Speaker 4: any other technology, there is a bad side. We can,
• 15:55
  Speaker 4: you know, kind of saggerate this bad side but at
• 15:58
  Speaker 4: the end of the day is a super power, powerful tool,
• 16:01
  Speaker 4: you know, which is able to do wonderful things in education,
• 16:05
  Speaker 4: in healthcare, in obviously in it. You know, that's what
• 16:09
  Speaker 4: we do at next thing, I'm you know, almost everybody
• 16:15
  Speaker 4: now with all these AI technologists can really have a
• 16:18
  Speaker 4: very personalized coach on anything. That's that's incredible. When you know,
• 16:26
  Speaker 4: we compare where we were twenty years ago to now
• 16:30
  Speaker 4: that we're able to ask a question about anything and
• 16:33
  Speaker 4: coming back with a pretty good advice and you know,
• 16:36
  Speaker 4: pretty good pointers on how to do things. I think
• 16:40
  Speaker 4: that's that's fantastic. It's much more there's much more goodness
• 16:45
  Speaker 4: than bad things there. There is certainly a danger in
• 16:49
  Speaker 4: the future how much we're going to automate. But I
• 16:52
  Speaker 4: always say the following. I think in every revolution, productivity
• 16:56
  Speaker 4: brought some sort of prosperity. And you know the companies
• 17:01
  Speaker 4: that they are using AI today, they are hiring a
• 17:03
  Speaker 4: lot of people. Next think is you know, getting twenty
• 17:08
  Speaker 4: thirty percent productivity in the R and D and still
• 17:11
  Speaker 4: we are hiring a lot of developers.
• 17:13
  Speaker 5: We are not eliminating jobs.
• 17:15
  Speaker 4: Is the opposite, because you have many more ideas and
• 17:18
  Speaker 4: the number of ideas are really limitless. So the more
• 17:22
  Speaker 4: you can get productivity, the more you can you can
• 17:25
  Speaker 4: get new ideas done right. And that's the approach of
• 17:29
  Speaker 4: many companies really investing in AI. So I'm really positive
• 17:32
  Speaker 4: about it.
• 17:33
  Speaker 3: That's great to hear. So let's bring it all together
• 17:36
  Speaker 3: with next think as a company and a platform, Decks
• 17:39
  Speaker 3: as a as an IT discipline and a market a segment,
• 17:44
  Speaker 3: and it's intersection with AI. There's barely an industry in
• 17:48
  Speaker 3: the world that we don't expect to be transformed by
• 17:51
  Speaker 3: AI in some way over the next few years. But
• 17:54
  Speaker 3: what is distinct for you about des What makes these
• 17:58
  Speaker 3: two forces of AI and deck especially complimentary? Why can't
• 18:02
  Speaker 3: you do a digital employee experience capability without AI? Why
• 18:07
  Speaker 3: do they What's what makes them so necessarily complimentary to
• 18:11
  Speaker 3: each other.
• 18:12
  Speaker 4: I think what has changed fundamentally is if we take
• 18:17
  Speaker 4: decks digital employee experience and again we go back to
• 18:21
  Speaker 4: what is it is to really look at the world
• 18:23
  Speaker 4: from the employee's I it's.
• 18:25
  Speaker 5: Really is this.
• 18:29
  Speaker 4: The reason why Decks was created is because we said, look,
• 18:33
  Speaker 4: we need to understand how employees are consuming digital services,
• 18:38
  Speaker 4: how employees they are experiencing all these technologies, what is
• 18:42
  Speaker 4: hindering their productivity? How we can make them better professionals
• 18:46
  Speaker 4: with digital applications? All these type of questions, right, So
• 18:49
  Speaker 4: really the true interception between people and technology. So with AI,
• 18:56
  Speaker 4: the fact that now we have llms, that they also
• 18:59
  Speaker 4: can create this bridge between people and technology, right, because
• 19:04
  Speaker 4: you can ask questions with natural language, which is people,
• 19:07
  Speaker 4: and they can tap into databases of very technical data
• 19:12
  Speaker 4: and give answers to that. So this next use, this
• 19:14
  Speaker 4: link between people and technology is very similar to the
• 19:18
  Speaker 4: text link. So if you put them together, you can
• 19:22
  Speaker 4: create fantastic new technologies. Like what I just said, right,
• 19:26
  Speaker 4: is man the ability to really solve any IT problem
• 19:30
  Speaker 4: right in a personalized way for every single employee. You
• 19:33
  Speaker 4: don't need to apprenticate. Why do you even need an
• 19:36
  Speaker 4: ITSM solution? If this works, right, why do you even
• 19:40
  Speaker 4: need to call the service desk? Maybe the one percent case,
• 19:43
  Speaker 4: right is something very exceptional. But these models today they
• 19:47
  Speaker 4: are able to you know, to solve questions at PhD level.
• 19:52
  Speaker 4: Of course, they're able to solve questions on an IT
• 19:54
  Speaker 4: level and digital application level. And I think it's a
• 19:58
  Speaker 4: tremendous opportunity for for Dismay.
• 20:03
  Speaker 2: Thinking Pedro about AI transformation company by company, What do
• 20:09
  Speaker 2: you think is going to separate those companies who thrive
• 20:12
  Speaker 2: in this new era with those that struggle, with those
• 20:14
  Speaker 2: that perhaps even't ultimately fail to adapt and grow.
• 20:20
  Speaker 4: I think, in my opinion, like any other change, we
• 20:26
  Speaker 4: need to embrace, we need to be open minded. I
• 20:29
  Speaker 4: think sometimes there is a little bit of skepticism because
• 20:33
  Speaker 4: they the challenge with AI, like the challenge with any
• 20:37
  Speaker 4: new technology, is you need to invest for a few
• 20:40
  Speaker 4: years before you get there. Or and we see a
• 20:43
  Speaker 4: lot of companies that they're saying, ah, I gave Copilot
• 20:46
  Speaker 4: to all my employees and I'm not seeing the productivity improvements. Well,
• 20:51
  Speaker 4: wait a couple of years. Make sure that people they
• 20:54
  Speaker 4: adopt AI, make sure they understand, you know, they make
• 20:58
  Speaker 4: their decisions with you know, the power of AI coaching them,
• 21:02
  Speaker 4: Or get a little bit of time so you know,
• 21:06
  Speaker 4: AI can be automated with APIs and all that, so
• 21:10
  Speaker 4: you can really improve processes. I think they're looking for
• 21:14
  Speaker 4: short term AROI. That's a mistake. There are other companies
• 21:18
  Speaker 4: that they are looking at AI as an investment for
• 21:20
  Speaker 4: the next two three years, and I think they're approaching
• 21:23
  Speaker 4: that in the right way. I'm a little bit worried
• 21:26
  Speaker 4: about the overregulation. I think there are some countries less
• 21:30
  Speaker 4: companies that they are over regulating AI before even having AI.
• 21:34
  Speaker 4: They are worried about the impact of AI. Okay, let's
• 21:37
  Speaker 4: first have AI. Let's see if there is some danger,
• 21:40
  Speaker 4: and then then we can't regulate. So you know, these
• 21:46
  Speaker 4: are some of the mistakes that I'm seeing. I do
• 21:50
  Speaker 4: think there is also a little bit of AI is here,
• 21:54
  Speaker 4: and there is a lot of jobs they're going to
• 21:55
  Speaker 4: be eliminated. Look, the there is auto pilots in planes
• 22:02
  Speaker 4: that still would and still would have pilots right that
• 22:05
  Speaker 4: they are able to oversee many of these planes. Somebody
• 22:11
  Speaker 4: told me the Earthy about radiologists, Right, one of the
• 22:15
  Speaker 4: first use cases of AI was really about eliminating the
• 22:19
  Speaker 4: need for radiologists. So you know, AI would be able
• 22:24
  Speaker 4: to diagnose all these things with computer vision. Well that's
• 22:28
  Speaker 4: not really true. I mean AI is a tool for
• 22:31
  Speaker 4: a rodeologists. But still they are the same number of
• 22:34
  Speaker 4: radiologists in the in the hospital. So I think we
• 22:38
  Speaker 4: need to be a little bit and there will be
• 22:40
  Speaker 4: some jobs that it would change, and maybe you know,
• 22:42
  Speaker 4: jobs that they are more repetitive, more busy work that
• 22:46
  Speaker 4: probably they are not jobs with a lot of fulfillment
• 22:49
  Speaker 4: right for those who who would do them. But I
• 22:53
  Speaker 4: think overall and very optimistic, it would be an excellent
• 22:56
  Speaker 4: tool to do a job much better.
• 22:59
  Speaker 2: And when we think think about the transformation over the
• 23:02
  Speaker 2: next year or two, in particular at individual companies, it
• 23:05
  Speaker 2: arguably finds itself in a uniquely powerful influential position. How
• 23:11
  Speaker 2: should it leaders be approaching this challenge, in this opportunity,
• 23:16
  Speaker 2: and what principles should they have to help their companies
• 23:19
  Speaker 2: be as successful as possible?
• 23:22
  Speaker 4: Yeah, I think, as I said before, I think it's
• 23:26
  Speaker 4: really important for leaders to understand that they need to
• 23:29
  Speaker 4: invest and they need to put any investment, any transformation
• 23:36
  Speaker 4: and investment in three to five years horizon and understanding
• 23:41
  Speaker 4: really how you know they would transform and their how
• 23:46
  Speaker 4: their I will we materialize in three to five years
• 23:50
  Speaker 4: ninety six months? Right, That's one thing. The second really
• 23:53
  Speaker 4: is maybe the mystifying a little bit AI is really
• 23:57
  Speaker 4: a great way to automate next right there is you know,
• 24:01
  Speaker 4: there are factories that they are automating a lot of things, computers,
• 24:05
  Speaker 4: they were automating a lot of things. So I think
• 24:08
  Speaker 4: they have to use it as a tool, and they
• 24:10
  Speaker 4: need to understand where are the processes that they are
• 24:13
  Speaker 4: very repetitive again, customer service, probably service desk, KI service desks.
• 24:20
  Speaker 4: They are excellent candidates because they are very repetitive processes,
• 24:24
  Speaker 4: right and get these maybe quick wins in these processes
• 24:28
  Speaker 4: that they are great candidates for you know AI. And
• 24:33
  Speaker 4: then from there they can they can go to the
• 24:36
  Speaker 4: next level. That's the two things that I'm seeing you
• 24:39
  Speaker 4: know best leaders do in this area.
• 24:42
  Speaker 2: One thing I've heard you talk about a lot down
• 24:45
  Speaker 2: the years, pedro is is about the importance of like
• 24:49
  Speaker 2: there being a harmonization between technology and employees, right and
• 24:53
  Speaker 2: with an emphasis on technology serving the employee, not overwhelming
• 24:57
  Speaker 2: the employee as a it becomes more powerful, more embedded.
• 25:02
  Speaker 2: How do we ensure that that balance continues to be
• 25:05
  Speaker 2: a player and how important is that balance in the
• 25:08
  Speaker 2: ultimate success of AI transformation in businesses?
• 25:12
  Speaker 4: I think for me, people and AI are two different things.
• 25:18
  Speaker 4: I think we need to understand that the motivations of
• 25:21
  Speaker 4: AI AI AI agents are not workers. Some people they
• 25:29
  Speaker 4: mix them AI agents. They don't have feelings, they don't
• 25:32
  Speaker 4: have motivations, they don't have a career dreams.
• 25:37
  Speaker 5: They don't have ski in the game.
• 25:39
  Speaker 4: Autely, it's absolutely no ski in the game for an
• 25:42
  Speaker 4: AA agent, you know. So obviously they can do things
• 25:47
  Speaker 4: in processes, they can automate a lot of things, but
• 25:51
  Speaker 4: it's still humans. We have a lot of SKI in
• 25:53
  Speaker 4: the game, right. We have emotions, we have creativity, We
• 25:56
  Speaker 4: are able to link things from one place to another,
• 26:00
  Speaker 4: to bring up you know, maybe to take risks, and
• 26:04
  Speaker 4: that's that's a complete different skill. So this balance, I
• 26:08
  Speaker 4: think it starts by understanding that humans and AI workers
• 26:15
  Speaker 4: or AI agents as they say today, are two different things,
• 26:19
  Speaker 4: very different. I think one is really a tool, the
• 26:22
  Speaker 4: other is really humans, right, which we are at the
• 26:25
  Speaker 4: core of any business.
• 26:28
  Speaker 2: That's a really cool way of putting it. And final
• 26:31
  Speaker 2: question for you, Pedro, final question about two hundred episodes.
• 26:34
  Speaker 2: What's the most exciting thing as we head into twenty
• 26:36
  Speaker 2: twenty six about being next things? CEO? They and I
• 26:42
  Speaker 2: actually wrote on my question cee io, which is incorrect,
• 26:46
  Speaker 2: devoted them.
• 26:47
  Speaker 3: Pedri got demoted. Sorry to tell you.
• 26:54
  Speaker 5: There are so many things.
• 26:56
  Speaker 4: I mean, I'm really excited about, you know, this new
• 27:00
  Speaker 4: possibility to give a you know, an IT agent to
• 27:04
  Speaker 4: every single employee. I mean employees when they have proms today,
• 27:09
  Speaker 4: their opening tickets waiting for two days. This is the
• 27:12
  Speaker 4: you know, there are teams that are coming back two
• 27:14
  Speaker 4: days later, two days, two days later, and they're saying, oh,
• 27:17
  Speaker 4: I don't have the problem anymore. And and you know this,
• 27:20
  Speaker 4: this couldn't really cannot continue for for more years. I
• 27:24
  Speaker 4: think we can really revolutionize and change the game there,
• 27:28
  Speaker 4: so finally expose all the power of techs to every
• 27:31
  Speaker 4: single employee. So that's really you know, a mission that
• 27:35
  Speaker 4: is very close to our hearts. Uh, democratizing decks so
• 27:39
  Speaker 4: using dex information to many other departments HR, network security.
• 27:43
  Speaker 4: I think that's something is going to be really big.
• 27:47
  Speaker 4: I'm always very excited about, you know, working with my
• 27:50
  Speaker 4: team and obviously everyone inside the company. I will have
• 27:54
  Speaker 4: the I have the privilege to really have a very
• 27:57
  Speaker 4: talented team in every single area, including you guys. Now,
• 28:04
  Speaker 4: I learned a lot from you and and I learned
• 28:07
  Speaker 4: from I learned a lot a lot from everybody at
• 28:09
  Speaker 4: next NICK and this is really a true plasure every morning.
• 28:11
  Speaker 4: So I'm really excited about that as well. So, yeah,
• 28:15
  Speaker 4: and a lot of innovation also that we are planning
• 28:18
  Speaker 4: for the next couple of years. The team in Switzerland
• 28:21
  Speaker 4: actually are arstopable and unestopable in terms of innovation. That's
• 28:25
  Speaker 4: that's really amazing. And not only in India, right, not
• 28:28
  Speaker 4: only in those and by the way, also in India
• 28:30
  Speaker 4: and Spain across the board they are We're seeing all
• 28:33
  Speaker 4: this innovation, mixing decks, AI feedback from customer is really unbelievable. Now,
• 28:41
  Speaker 4: the hard job is really to prioritize, you know, some
• 28:43
  Speaker 4: of these ideas because we want to be really impactful.
• 28:46
  Speaker 4: So yeah, we we are really excited about the next
• 28:49
  Speaker 4: three years.
• 28:51
  Speaker 2: Absolutely, and hopefully we'll showing too, you know. And look,
• 28:56
  Speaker 2: I just want to say, if the listeners right, this
• 28:59
  Speaker 2: is I think only episode has been late in those
• 29:02
  Speaker 2: two hundred days, in those two hundred episodes, so we're
• 29:05
  Speaker 2: really sorry about that, but we hope you feel it
• 29:07
  Speaker 2: was worth the wait. And I'm going to say a
• 29:09
  Speaker 2: very very short Oscar speech here and just thank everybody,
• 29:13
  Speaker 2: obviously customers and partners for supporting the show, for coming
• 29:17
  Speaker 2: on the show, every guest, every influencer.
• 29:18
  Speaker 3: Who's come on.
• 29:19
  Speaker 2: We're hugually grateful, everybody who listens to the show, all
• 29:22
  Speaker 2: the people in the community who support them, people like
• 29:25
  Speaker 2: Stuart and Danik Gartner. We really really appreciate everybody's support.
• 29:30
  Speaker 2: Of course, to the show team itself, Catherine Shay, Alan
• 29:33
  Speaker 2: Drymer in particular, phenomenal producers over so many years, as
• 29:37
  Speaker 2: well as a reality bite its team Megan, Oreanna, Diana, Sean,
• 29:40
  Speaker 2: Sam Holsman. I'm sure people remember Sam, and I want
• 29:44
  Speaker 2: to thank some Next thingers past and present who who
• 29:46
  Speaker 2: also helped to sort of establish the show, who had
• 29:48
  Speaker 2: the idea for the show, not least Eba Calderan, Yes,
• 29:52
  Speaker 2: scenes I Eid, Heather Moses, and of course our guest today, yourself,
• 29:56
  Speaker 2: Pedro about us. We're so grateful to everybody hoping we
• 29:59
  Speaker 2: can do another two hundred episodes and it's real. It's
• 30:02
  Speaker 2: really out pleasure and thanks for coming on, Pedra.
• 30:04
  Speaker 5: Thank you very much. Big names you just mentioned there,
• 30:07
  Speaker 5: great unders.
• 30:08
  Speaker 3: Yeah, a lot of all stars there. I couldn't have
• 30:10
  Speaker 3: said it any better time. You wrapped it up really well.
• 30:12
  Speaker 3: And thanks to all the listeners, to the ones that
• 30:14
  Speaker 3: come up to us at the events and want to
• 30:15
  Speaker 3: not only talk about decks and talk about Next Thing,
• 30:17
  Speaker 3: but I've even had listeners come up and want to
• 30:20
  Speaker 3: talk about the episode where we talked about music, and
• 30:22
  Speaker 3: we talk about music trends and favorites for twenty minutes.
• 30:25
  Speaker 3: And it's really great to be able to have this
• 30:28
  Speaker 3: platform to reach out to the audiences. So thanks for
• 30:31
  Speaker 3: thanks for listening.
• 30:32
  Speaker 2: Thank you so much.
• 30:33
  Speaker 3: Man. Yeah, great pleasure.
• 30:35
  Speaker 5: Bye.
• 30:37
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• 30:39
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• 30:53
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• 31:00
  Speaker 1: Next time,