2858: Navigating the Generative AI Revolution: A Deep Dive with Rackspace

[00:00:00] In a world where technology and sustainability are becoming increasingly intertwined, how can

[00:00:08] organizations harness the power of things like Genuitive AI to not only revolutionize

[00:00:14] their operations but also spearhead their sustainability initiative?

[00:00:20] Well today I want to dig deep on this question with Serene Koushik, President of Technology

[00:00:26] and Sustainability and Global Head of Foundry for Genuitive AI at Rackspace.

[00:00:32] He's a great guy, he's got over two decades at the helm of tech innovation and he also

[00:00:38] brings with him a wealth of knowledge on the transformative power of AI and its pivotal

[00:00:43] role in the intersection of technology and sustainability.

[00:00:48] So from that rapid evolution of Genuitive AI workloads to the strategic opportunities

[00:00:53] and the challenges of adopting these technologies, today's guest is going to offer his invaluable

[00:01:01] insights and together we'll explore how Genuitive AI is set to reshape industries with the

[00:01:07] same vigor as the mobile revolution but only quicker.

[00:01:12] And also explore the crucial skills for the future workforce, how we ensure that

[00:01:17] nobody gets left behind here and some of the innovative strategies for talent acquisition

[00:01:22] in the age of AI.

[00:01:24] Now before I get today's guest on, quick shout out to the sponsors of Tech Talks daily because

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[00:02:21] But now let's get today's guest on.

[00:02:23] So buckle up and hold on tight because no matter where you're listening in the world

[00:02:28] I'm going to beam your ears all the way to the US where we can talk about all this

[00:02:33] and much more.

[00:02:36] So a massive warm welcome to the show.

[00:02:39] Can you tell everyone listening a little about who you are and what you do?

[00:02:44] I'm Srinni Koushik.

[00:02:47] I'm the president for AI technology and sustainability at Rackspace.

[00:02:52] Wow, it's an incredibly cool job title and two of the biggest words that people are talking

[00:02:57] about at the moment, ALA and sustainability.

[00:03:00] And I also suspect that both of those words businesses know that they need to get

[00:03:04] involved with both of them.

[00:03:06] But equally it can be a little bit daunting on where do they begin?

[00:03:10] Sure, they don't get left behind.

[00:03:12] So to set the scene for our conversation today and I appreciate this is a pretty big question.

[00:03:17] But how can organizations pragmatically integrate AI into their sustainability

[00:03:23] initiatives to create that tangible and measurable impact that they're looking for?

[00:03:28] Yeah, first of all, I think AI, especially generative AI, since it's come in over

[00:03:34] the last year or so, has kind of been pretty much you can't start a conversation

[00:03:40] without talking about AI.

[00:03:42] And the reality is like when you kind of looked at the first six or seven months

[00:03:46] of that whole wave, a lot of people were, you know, I call it they were building

[00:03:51] toys in subconsum.

[00:03:53] Let me convince myself that it's there.

[00:03:55] I think we very quickly moved beyond that to say, how do I industrialize AI

[00:04:00] in their organization?

[00:04:02] Right? Meaning how do I actually embed it into my business processes?

[00:04:06] How do I make sure that it is adding the value that it's reported to add?

[00:04:12] And so like going through that journey has been really interesting.

[00:04:17] And the way we advise people is, first of all, if you're going to implement

[00:04:22] a pragmatically, make sure you understand what responsible AI is for you.

[00:04:27] Right?

[00:04:27] And because I think it's very critical that organizations implement AI

[00:04:32] in a way that's responsible to society and consistent in their values,

[00:04:36] like in their organizations value consistent with that.

[00:04:40] And I think it starts there and it starts establishing that framework

[00:04:45] and the guidance and the governance you actually need to be able to drive AI.

[00:04:50] And what I've seen is like, you know, I've been in this industry for 30 plus years.

[00:04:54] And unlike any other technology, the maturity on this is evolving very,

[00:04:59] very rapidly.

[00:05:00] The regulations are catching up, the guidelines for what you can build

[00:05:05] and what you can't use, all of those things are shaping up.

[00:05:07] So the organizations that are adopting AI have had to move

[00:05:12] very, very rapidly.

[00:05:14] And when you're moving at that speed, a healthy level of pragmatism helps

[00:05:20] because you don't want to rework and redo things.

[00:05:24] 100% with you.

[00:05:25] And it was interesting you mentioned there that the last six, seven months

[00:05:28] or the six, seven months last year when everyone was going crazy over

[00:05:32] generative AI and it felt to me, you said you have almost building toys

[00:05:37] and it reminded me of not the iPhone moment, but the App Store moment.

[00:05:41] When mobile apps first came out, all anyone was building was turn your

[00:05:45] phone into a plant of beer into a chainsaw into a musical instrument.

[00:05:51] It was just toys and then little by little businesses started

[00:05:55] producing things that would make an impact to their business.

[00:05:58] But I'm curious, here we are in 2024.

[00:06:01] What are the most exciting new trends that you're observing in generative AI

[00:06:05] workloads and how are they shaping the future of business technology?

[00:06:10] Because it feels like this is where the magic starts to happen.

[00:06:12] It is a fantastic analogy to compare to the App Store

[00:06:16] because I still remember like, you know, hey, pick up your phone

[00:06:20] and shake it and this happens or like you can it's like, oh, it looks like

[00:06:24] a beer I can drink it.

[00:06:26] You had all kinds of apps coming out.

[00:06:28] And I think we went the only difference with the

[00:06:32] generative AI trend is we went through that very quickly.

[00:06:35] We went through it very quickly because the technology exists

[00:06:38] to be able to go drive that.

[00:06:40] So so I think but but you know, as these new things come out,

[00:06:44] there's still I'll go back to some of the key things that that

[00:06:48] I've learned through this that still apply here.

[00:06:52] Steve Jobs and others like you talk a lot about user centered design

[00:06:55] and user centered design is all about three things like

[00:06:58] desirability, feasibility and viability.

[00:07:01] And when you can move, even you can find the right intersection

[00:07:06] between those three things, you end up with a product that's killer

[00:07:09] or a solution that's killer.

[00:07:11] With AI, what we see is the potential is tremendous.

[00:07:16] So you have the boards at boards of organizations senior

[00:07:20] executives wanting to use AI because they know that it's

[00:07:23] a competitive advantage.

[00:07:24] So the desirability exists today.

[00:07:26] Right now, if I move over the feasibility component of it,

[00:07:31] the hyperscalers that the the bond providers have built tech

[00:07:35] and they are releasing new capabilities every single

[00:07:40] you know, week, I would say, right?

[00:07:41] And then there's new large language models coming out that

[00:07:44] your the feasibility of solutions becomes more and more

[00:07:48] easier to do.

[00:07:50] So from a business standpoint, where we're actually running

[00:07:53] into issues right now is the viability, right?

[00:07:57] Meaning if I if it's desirable, if I can build it,

[00:08:01] can it deliver the the benefits that I expected it to?

[00:08:06] And and that's where a lot of the organizations we work with

[00:08:09] are kind of looking at this going, wait, we built the solution

[00:08:15] if I now put it in, is it going to deliver the productivity

[00:08:18] enhancements that we talked about?

[00:08:20] Is it going to, you know, the standard pitch?

[00:08:23] Generative AI is going to enhance creativity, improve

[00:08:26] productivity, you know, increase like, you know, those things

[00:08:31] you go and say, OK, right.

[00:08:33] Will it enhance creativity?

[00:08:34] We're rolling out something like co-pilot enhance creativity

[00:08:39] because if it doesn't, then it's just an added cost

[00:08:43] in your stop right in the in the shift.

[00:08:45] It's a cool toy and other.

[00:08:47] So a lot of it is now shifting over to how do I get the

[00:08:51] organization to learn and adapt from a technology standpoint?

[00:08:55] What's happening is it well, the costs of these solutions

[00:08:59] are still pretty high, right?

[00:09:00] Nainos, it's evolved very quickly, but the price points

[00:09:04] haven't yet dropped to the level where these business

[00:09:08] cases start making sense for the large organizations who have

[00:09:12] it and for those handful of use cases that the value is delivered,

[00:09:16] we're going ahead and implementing that.

[00:09:18] But a lot of other customers are coming back and looking at it

[00:09:20] and saying, OK, we built this.

[00:09:21] This is good.

[00:09:23] But in order for me to deploy to the production, it's going

[00:09:26] to cost me a lot of dollars or pounds.

[00:09:28] And does it have an ROI in in in 2024?

[00:09:33] Does it have an ROI in 2025?

[00:09:36] Sadly, the answer is for the most cases you look at it

[00:09:38] and you're thinking of, yeah, not yet.

[00:09:40] And the costs have to drop a little bit more on that front

[00:09:43] to be able to do that.

[00:09:44] And the cost will only drop when you start evolving

[00:09:48] from these large language models that people are using

[00:09:51] for generative AI and do more tailored small language

[00:09:54] models because running the inference on a daily basis

[00:09:58] takes time, takes compute power, takes all of those

[00:10:02] those things that require the solution to work.

[00:10:06] I think the shift and the workload shift that we're

[00:10:09] seeing is like, first of all, it's exciting because the things

[00:10:12] that are going through all those gates are the ones that truly

[00:10:15] add value.

[00:10:16] So that's great.

[00:10:17] Like you're not building that app where you're drinking.

[00:10:20] It looks like you're drinking a beer or something.

[00:10:22] You're actually building those valuable solutions for it.

[00:10:26] And as we do that, you see the whole conversation

[00:10:30] around language models and how is a large language model

[00:10:34] better or a smaller language model that's focused on a

[00:10:38] particular domain better for a solution.

[00:10:41] We were mentioned a few moments ago there how generative AI

[00:10:44] has been compared to that swift rise of smartphones

[00:10:47] and mobile apps over the years.

[00:10:49] How do you see generative AI maybe similarly

[00:10:52] revolutionizing industries in the years ahead?

[00:10:55] Is there anything that you see taking shape there

[00:10:57] or any predictions?

[00:11:00] Well, I absolutely do believe that it will change

[00:11:03] and it can get there.

[00:11:05] Not to belabor that the analogy that you used.

[00:11:11] In order for the iPhone and the apps to be valuable,

[00:11:13] you had to go in and embed it into your digital transformation

[00:11:17] efforts.

[00:11:18] You had to embed it into processes

[00:11:20] and it couldn't be something that sat next to it.

[00:11:23] It had to be embedded into it.

[00:11:26] I still remember past the toys,

[00:11:30] like the first wave of digital transformation

[00:11:33] was, hey, we've got a digital solution and I would ask our

[00:11:35] kind of some of the people who work,

[00:11:37] what solution did you put in?

[00:11:39] Well, we've got this thing where we get faxes

[00:11:43] from our branch offices.

[00:11:44] We pick up the fax and then we scan it into a digital thing

[00:11:47] so that it can actually go through that.

[00:11:50] Better but not the solution you want.

[00:11:53] You actually want to embed it into your solution

[00:11:55] and that's kind of where AI and generative AI

[00:11:59] are coming up.

[00:12:00] We are seeing.

[00:12:01] We've got some really forward looking guys

[00:12:04] who are taking a look at it and saying,

[00:12:06] I need to generate an investor memo.

[00:12:08] 80% of the investor memo or 90% of the investor memo

[00:12:11] is the same but it takes us a lot of time

[00:12:13] to do the research to be able to go go that.

[00:12:17] Let me use generative AI to create it

[00:12:19] so that the expert that I've got

[00:12:22] is really adding their value to it.

[00:12:25] So it's a human augmented type of a solution

[00:12:27] that comes up.

[00:12:29] Those are becoming more and more common today

[00:12:31] and what that really means is it actually shifts you away

[00:12:36] from the day to day toil of going out

[00:12:40] and doing that research and do that

[00:12:41] and just to throw an analogy of mine into it.

[00:12:46] I call it generative AI in business

[00:12:49] is gonna help us move up the Maslow's hierarchy

[00:12:52] because most businesses spend a lot of time

[00:12:55] on food, shelter, clothing.

[00:12:57] At the bottom of the Maslow's hierarchy,

[00:13:00] basic needs, right?

[00:13:01] The manual labor thing that has to be done,

[00:13:04] the quality checks that have to be executed

[00:13:08] because the manual intervention in

[00:13:10] and that's a lot of time spent by many organizations.

[00:13:13] Gen AI is gonna move us up.

[00:13:15] So just like human being moving towards

[00:13:17] self actualization, I think businesses

[00:13:20] are going to really start thinking about

[00:13:25] how do I completely change some of the processes?

[00:13:31] 100% with you and I think it's important to remember

[00:13:34] that we have been here before.

[00:13:36] I mean, the last 18 months, generative AI

[00:13:38] is already beginning to reshape the business landscape

[00:13:41] which means we will lose some traditional business roles

[00:13:44] but equally there'll be many, many more jobs

[00:13:46] that come too and if we look back,

[00:13:48] I think I Googled this recently,

[00:13:50] jobs that didn't exist 20 years ago

[00:13:52] and there is a long list of job role

[00:13:54] that we all take for granted now

[00:13:55] from social media managers to cloud engineers,

[00:13:59] data scientists, et cetera.

[00:14:01] So we know the workplace will evolve

[00:14:03] but I suppose for business leaders,

[00:14:05] the big question is what are those key skills

[00:14:07] and competencies that they should be looking for

[00:14:10] from their workforce?

[00:14:11] What should they be focused on developing

[00:14:13] and how important or re-skilling and upskilling

[00:14:17] and then showing that we don't leave people behind here too.

[00:14:20] Yeah, so first of all, I think it's a very good question.

[00:14:25] I'll be very clear and say this is the way

[00:14:29] I look at the skills landscape going forward, right?

[00:14:32] It's maybe something that many people disagree with

[00:14:36] but I think where this is headed

[00:14:39] is number one within technology, right?

[00:14:42] When you kind of think about those roles,

[00:14:45] I think there is a shift away from STEM coming,

[00:14:51] which is, I think if you kind of use that

[00:14:53] Matty's hierarchy food shelter clothing,

[00:14:55] I had to program it, I needed it all to deal with this

[00:14:58] but I'm gonna build an AI model.

[00:15:00] And when I get the data scientists

[00:15:02] who can actually go and build the right type

[00:15:04] of regressive model or a classification model

[00:15:06] and understand what type one and type two errors are,

[00:15:09] there's a ton of things that you had to do

[00:15:12] that was just playing at the bit level

[00:15:14] and so you actually needed a lot more stamina.

[00:15:18] As you move up that Matty's hierarchy,

[00:15:21] you're starting to use higher level cognitive functions

[00:15:24] like creativity, right?

[00:15:25] Problem solving.

[00:15:27] And the ability to kind of understand something,

[00:15:33] comprehend what's being said

[00:15:35] and then move on to that next step.

[00:15:37] And I think those are areas where traditionally

[00:15:40] underutilized areas like the liberal science and arts,

[00:15:46] in the US we call it LSNA,

[00:15:48] but it's English, right?

[00:15:50] How do you communicate?

[00:15:51] Those fields have not participated

[00:15:55] in this technology boom, I believe ya.

[00:15:57] There's an opportunity.

[00:15:58] So it also has implications on technology teams

[00:16:02] and HR organizations because what you're looking for

[00:16:05] should change, right?

[00:16:07] Because it's the thing that's gonna help most people,

[00:16:12] that most people in the space is,

[00:16:13] this technology is moving so quickly

[00:16:16] that I tell my HR leads and others,

[00:16:19] if somebody tells you they're an AI expert,

[00:16:22] run the other direction.

[00:16:23] Because they don't know what they're talking about

[00:16:25] because they cannot,

[00:16:26] I'm in it every day and I can tell you

[00:16:28] I'm barely adequate in this space at the speed

[00:16:31] at which this is moving.

[00:16:33] And so like the reality is then let the technology evolve

[00:16:36] and what can organizations do on top of it?

[00:16:39] You can actually leverage your creativity

[00:16:41] and the things to be able to interact with AI.

[00:16:44] But it also means that if you're gonna bring in people

[00:16:46] back to your re-skilling and retooling,

[00:16:49] you have to raise AI literacy

[00:16:51] amongst everyone in the company.

[00:16:54] When we started this journey back in May of last year,

[00:16:58] I introduced within the Rackspace program

[00:17:00] called fair learn.

[00:17:02] Fair is only for AI by Rackspace

[00:17:04] is our AI business unit out there.

[00:17:08] And as we did that,

[00:17:09] we introduced something called fair learn

[00:17:12] and it was a curriculum that was built

[00:17:14] and with four levels starting with AI aware

[00:17:18] all the way to an AI expert,

[00:17:20] leveraging tools and training

[00:17:25] that was already out there.

[00:17:27] We set ourselves what we thought was a very aggressive goal

[00:17:30] of trying to get 60% of Rackspace

[00:17:33] at least to that first level of awareness

[00:17:35] by the end of the year.

[00:17:37] We got there, we got to about 85%

[00:17:39] and we're knocking on a hundred great though.

[00:17:42] This includes everyone.

[00:17:44] It includes our administrative assistance.

[00:17:47] It includes our CEO.

[00:17:48] It includes me.

[00:17:49] All of us had to go through it.

[00:17:51] Some of us went like higher up in that education

[00:17:53] but everyone was at AI literacy level.

[00:17:56] And the reason we do that is when you industrialize AI,

[00:18:01] AI becomes an employee in your organization.

[00:18:04] And you know, this is very important.

[00:18:07] And if you're gonna bring AI solutions

[00:18:09] into your organization as an employee,

[00:18:11] as a competent employee that can do a task

[00:18:14] or a set of tasks very well,

[00:18:16] you've got to be able to train AI

[00:18:18] how to work with the people.

[00:18:21] But vice versa, you got to train the people

[00:18:23] how to work with AI and collaborate with it

[00:18:25] so that you can raise that level.

[00:18:27] So you'd say it's a fascinating

[00:18:29] but it's just such an exciting area to do it

[00:18:31] because I know we'll talk about sustainability later

[00:18:36] but economic sustainability

[00:18:40] and being able to do it in an equitable way

[00:18:43] requires that you bring everybody along.

[00:18:45] Right, I happen to be one of those really fortunate ones

[00:18:49] that people call either the 10% or 1%

[00:18:54] or whatever it is, right?

[00:18:55] Because I was lucky enough to participate

[00:18:57] in the technology boom.

[00:18:59] But others like that I grew up with

[00:19:02] and others did not have that opportunity

[00:19:03] because they didn't come into the space.

[00:19:07] You can't have AI widening income gaps.

[00:19:11] You can't have AI widen all of the societal issues

[00:19:15] that we already have today.

[00:19:17] And I think it's critical

[00:19:18] that we take the time to bring people along

[00:19:21] whether it's within your organization or outside of that.

[00:19:24] 100% with you.

[00:19:25] And in terms of talent acquisition,

[00:19:28] what shifts are you anticipating

[00:19:30] as companies increasingly adopt generative AI?

[00:19:33] How should they adapt their hiring strategies

[00:19:35] to attract the right talent for these new tech changes too?

[00:19:39] And I agree with you, as you were saying,

[00:19:41] there's skills there.

[00:19:42] There's so many areas that technology can take care of.

[00:19:45] It can remove robotic mundane tasks.

[00:19:47] But it's human skills, strategy, creativity,

[00:19:50] problem-solving, innovation, communication,

[00:19:53] collaboration, all those great things we are as humans.

[00:19:56] That's what we can bring to the table.

[00:19:58] But what do you say here?

[00:20:00] Well, I think that...

[00:20:01] I've talked about it briefly as part of the previous answer,

[00:20:05] but look, I think the near future,

[00:20:10] the workforce is going to be made up of humans and AI.

[00:20:13] Right?

[00:20:15] Some AI solutions you built for your company.

[00:20:17] Some AI solutions you're buying from other partners

[00:20:21] like Salesforce or Microsoft or any of those things.

[00:20:24] But if the workforce is made up of humans and AI,

[00:20:29] the values of the company should be reflected in both of those.

[00:20:33] So you actually interact with one another

[00:20:35] and the collaboration that needs to happen

[00:20:37] happens in that space as well.

[00:20:39] And there's also the whole...

[00:20:43] The wrinkle in this whole thing

[00:20:44] is like with this new hybrid model of work.

[00:20:47] In the past, everybody was coming into work

[00:20:50] and you were able to kind of learn

[00:20:51] talk to each other.

[00:20:52] So there's these days, it's some mixture.

[00:20:56] Either you work completely from home

[00:20:58] or you're coming into work only a couple of days a week.

[00:21:02] It presents some very, very interesting challenges

[00:21:05] because you mentioned those higher level skills.

[00:21:07] That's what we've got to hire.

[00:21:09] But I've got a daughter who's 26 years old.

[00:21:12] She graduated in 2020 right when the pandemic was going on.

[00:21:18] She has never worked in an office.

[00:21:23] And I give her a lot of credit because she said like that,

[00:21:27] I'm going to quit and join some place

[00:21:28] where I'm actually required to come in for three or four days.

[00:21:32] Because they really struggle to make those connections.

[00:21:35] They struggle to...

[00:21:37] People like us who had the benefit of working in both places,

[00:21:42] we can try to adapt.

[00:21:43] But this next generation workforce that's coming in,

[00:21:46] we've got to figure out how we bring them in,

[00:21:51] get them familiar with this.

[00:21:53] Training them on using AI is going to be easy,

[00:21:56] because they're already coming in with it.

[00:21:58] But how do you make sure that you get that human connection

[00:22:02] is a part of it?

[00:22:03] So we...

[00:22:04] Our HR, the chief HR officer like Kelly

[00:22:09] is top notch, right?

[00:22:10] Then she comes in and says like,

[00:22:12] first of all from an AI standpoint,

[00:22:13] she's like, Trini, how do I get to use AI

[00:22:16] tomorrow in my recruiting process?

[00:22:18] So we did the initial things for her,

[00:22:21] which is if you have a job description

[00:22:23] and you have a resume, feed it into our solution

[00:22:27] and it will give you the interview questions you have to ask.

[00:22:30] Right, that version based on your job description

[00:22:34] and the resume of the candidate,

[00:22:36] can I...

[00:22:37] It just asks you the questions

[00:22:40] and you can define the questions.

[00:22:42] It's like, oh, but I need to use...

[00:22:45] This person is going to be joining

[00:22:46] our public cloud organization

[00:22:48] and they are looking for these two or three things.

[00:22:50] The questions get refined.

[00:22:52] And what it does is it allows you to kind of have

[00:22:55] a much better interaction with the thing.

[00:22:58] It's sadist people time,

[00:22:59] because when I get a call saying,

[00:23:01] Trini, can you do an interview?

[00:23:03] Right, I have those questions already there in front of me

[00:23:07] instead of me having to write it down.

[00:23:10] So our HR team has been pretty forward-looking

[00:23:12] in terms of how we do that.

[00:23:13] They have an interactive chat bot called Ask HR

[00:23:17] and others.

[00:23:17] And now what we're trying to do,

[00:23:19] they pioneered this whole AI learn,

[00:23:21] the fair learn component of it taking it through.

[00:23:24] We're starting to say, okay, this future workforce,

[00:23:28] what are the skills and capabilities

[00:23:32] that we have to give them?

[00:23:34] For people who've been here for a long time,

[00:23:38] how do we get them more familiar with the AI?

[00:23:41] For someone who's just out of college and coming in,

[00:23:45] how do we get them to work in this environment

[00:23:49] where it's a true hybrid environment with humans and AI?

[00:23:53] How do we actually go out and build that?

[00:23:56] And just like its early days,

[00:23:58] we've launched a leadership academy

[00:24:01] where we're taking,

[00:24:03] but the first cohort I'm running

[00:24:05] is about 40 people through it.

[00:24:07] And the 40 people have some mix of about 10 or 12 of them

[00:24:12] are new to the company.

[00:24:14] And then there are several that have been here

[00:24:16] for a long time.

[00:24:17] And we're actually taking them

[00:24:19] through these individual things.

[00:24:20] We have a session coming up

[00:24:22] where we'll actually get them to interact with Claude,

[00:24:27] right?

[00:24:28] And we don't use chat GPT,

[00:24:31] but we use Claude for man-thropic.

[00:24:34] We're gonna give them an exercise to go learn.

[00:24:38] Here's an exercise.

[00:24:40] Let me see you use Claude,

[00:24:42] to come up with an answer.

[00:24:44] And it's in the trial runs we've done,

[00:24:47] it's been fascinating because like,

[00:24:50] they all have heard the noise,

[00:24:52] they all heard this,

[00:24:52] but once you get to use it hands on

[00:24:55] and you get the training saying,

[00:24:58] yeah, you could try changing your prompt this way, right?

[00:25:01] And see the answer and what comes out.

[00:25:05] I start lighting up and they're like,

[00:25:06] oh, cool, I can use this in my job, right?

[00:25:09] And it's no longer a fear

[00:25:10] that AI is gonna take over your job,

[00:25:13] I can see how I can evolve my thinking to it.

[00:25:17] And it also gives us an opportunity to come back and say,

[00:25:20] by the way, that last answer you got,

[00:25:23] that's not your final answer.

[00:25:25] That's your first draft, right?

[00:25:27] Like so you'd use that as your first draft

[00:25:29] and then add your human touch to it.

[00:25:31] So it gives them a way to,

[00:25:34] hands on way interact with AI

[00:25:37] in a day-to-day setting

[00:25:39] and get more comfortable with it.

[00:25:43] So many great points there, I'm curious.

[00:25:46] For any business leader listening

[00:25:47] that are dipping their toes in the water

[00:25:49] or trying to navigate these uncharted digital waters

[00:25:52] for the first time,

[00:25:53] do you see any other strategic opportunities

[00:25:56] and challenges that those businesses might face

[00:25:59] when they're adopting generative AI

[00:26:01] and any tips or advice on how they should be navigating it?

[00:26:07] I do believe that any business leader

[00:26:12] adopting AI should not take a technology first approach.

[00:26:16] They should take, and I think,

[00:26:18] first of all, I'd say AI is real.

[00:26:21] Like the world, it's not hype, right?

[00:26:24] All the positive aspects of AI are absolutely true

[00:26:29] and all the negative side results are true.

[00:26:30] So it's kind of like,

[00:26:32] it can be, it can go either way.

[00:26:35] The only way we make sure that the good AI

[00:26:38] or the responsible AI wins

[00:26:40] is by getting the organization aligned to those values.

[00:26:44] And to do that, it's just like anything else.

[00:26:48] It's a habit that has to be built

[00:26:50] and the way we, I told, but people,

[00:26:53] you work for a company, we also act based,

[00:26:55] our values are very clear, right?

[00:26:57] We're a customer first company.

[00:26:58] We are, like we have technology in our DNA,

[00:27:02] like, sorry, our values are clear.

[00:27:04] So our approach to responsible AI was shaped by our values.

[00:27:10] And so what that means is,

[00:27:13] if I have a solution that doesn't meet our values,

[00:27:18] we're going to say no, we're gonna walk away, right?

[00:27:21] It's if we can't, if the large language model

[00:27:26] of a particular company that we're using

[00:27:28] and you look at that company and you see their values

[00:27:31] and it doesn't align with yours,

[00:27:33] probably not a good idea to use that and bring it in, right?

[00:27:37] And in your company.

[00:27:38] So business leaders taking that approach

[00:27:42] and being very pragmatic about it,

[00:27:44] like love the pragmatic word you used at the start,

[00:27:47] pragmatic about it so that you're balancing

[00:27:49] that desirability, feasibility and viability

[00:27:52] will allow you to kind of bring AI in a very land

[00:27:58] and in a way that the organization can embrace the change

[00:28:04] as opposed to resist it.

[00:28:05] So that's kind of what my advice would be.

[00:28:09] I would also say most business users

[00:28:12] should get their AI literacy up, right?

[00:28:14] You know, don't lie on others to be able to tell you that.

[00:28:17] You need to do that.

[00:28:19] If not for your business, do it for your personal life

[00:28:22] because this is everywhere these days, right?

[00:28:26] And it is so important that people get up to speed on this

[00:28:32] because you need to be able to discern what's right

[00:28:35] and what's wrong, right?

[00:28:37] And that all critical thinking,

[00:28:39] if you just accept what AI is selling at face value

[00:28:43] you're going to kind of create these bubbles

[00:28:47] or things like that just increase the deviance, right?

[00:28:50] And so I think we use this term

[00:28:55] in every one of my presentation.

[00:28:56] Let's say we're doing AI

[00:28:58] because we want machines to be better machines

[00:29:01] so that humans can be better humans.

[00:29:05] That's the core of why we wanna do that

[00:29:08] and I think that's good advice for most business owners

[00:29:13] considering AI.

[00:29:15] And I must admit as the over cautious XIT guy,

[00:29:19] I do find myself saying sometimes,

[00:29:21] hey, let's call our jets.

[00:29:23] We've seen what happened when you move fast and break things.

[00:29:26] We need to start thinking about ethical considerations,

[00:29:29] governance and all those boring IT kind of stuff

[00:29:31] which is so important.

[00:29:33] So how should organizations approach

[00:29:35] those ethical considerations and governance needed

[00:29:38] to ensure that responsible use?

[00:29:41] Yeah, so I'll tell you how we are advising

[00:29:44] our customers to do it, right?

[00:29:45] And so first of all for us,

[00:29:48] responsible AI comes down to three things.

[00:29:51] You'll see me use this three all the time, right?

[00:29:54] And then because it comes out to three things.

[00:29:58] For AI to be responsible,

[00:30:00] number one, it has to be symbiotic with human beings.

[00:30:03] Number two, it has to be secure.

[00:30:05] And number three, it has to be sustainable, right?

[00:30:07] And those three S's are informed

[00:30:12] by the values of the company, right?

[00:30:14] For us as an example at Rackspace,

[00:30:16] symbiotic means we're gonna use AI

[00:30:19] to augment our rackers and the capabilities,

[00:30:23] not replace them, right?

[00:30:25] Again, it may prevent me from,

[00:30:29] it may give me the opportunity

[00:30:31] to not hire additional folks, right?

[00:30:34] Because the productivity improvements are there.

[00:30:36] But if we're creating something,

[00:30:39] we have to make sure that if it's replacing somebody's job,

[00:30:42] how do you get that person moving upwards, right?

[00:30:44] Into that piece.

[00:30:45] So the symbiotic component is important to us.

[00:30:48] Secure is really at the core of it.

[00:30:52] Who has access to what information?

[00:30:54] Is personal information protected?

[00:30:57] All of those things.

[00:30:58] And not just that, are we meeting the rules

[00:31:01] and guidelines established by the EU, right?

[00:31:03] And by the various regulatory agencies coming out,

[00:31:07] that's where the secure component comes in.

[00:31:09] And then the sustainable piece of it has two parts.

[00:31:13] Sustainable is like it's AI for sustainability

[00:31:17] and the sustainability of AI, right?

[00:31:19] The AI for sustainability is where you're using AI

[00:31:23] to kind of help you go through all of the reporting

[00:31:29] and the accuracy work that you have to have

[00:31:32] in terms of carbon reporting.

[00:31:34] The new for the reporting.

[00:31:36] It's a ton of data coming in from multiple sources.

[00:31:39] It's a very labor intensive approach,

[00:31:42] but if I can use AI to kind of guide that

[00:31:45] and how we collect information, process it,

[00:31:48] aggregate it and report on it,

[00:31:51] that's the AI for sustainability component of it.

[00:31:53] Again, clearly there's many use cases

[00:31:55] if I was working in the weather meteorological department

[00:32:01] then I'd be using it to understand the data better

[00:32:03] and start doing better predictions.

[00:32:06] But that's AI for sustainability.

[00:32:09] But the sustainability of AI part of it is,

[00:32:12] today it's an area that's a gap

[00:32:14] because any AI solution that you put in

[00:32:17] consumes a lot of energy, right?

[00:32:19] Then the accident works against what you're doing.

[00:32:23] But if you're cautious about what applications

[00:32:28] you're building, what solutions are you building

[00:32:30] and do it in a way that meets those other

[00:32:34] responsible AI components,

[00:32:36] then you can make the best of a bad situation.

[00:32:40] That's kind of the way I put it.

[00:32:42] And then what's happening though is what's exciting

[00:32:44] about the technology developments in this space

[00:32:47] is we've been interacting with a couple of different,

[00:32:49] like you had the biggest GPU maker

[00:32:52] had their conference like a couple of days ago.

[00:32:56] But when you have this type of an opportunity

[00:32:59] there are so many people I spent time

[00:33:01] with the company a couple of days ago

[00:33:03] where they were talking about running these instances

[00:33:06] with 40% less, 40% of the power used by today's top.

[00:33:11] So there's work going on to say,

[00:33:13] how can I deliver the same or better,

[00:33:17] a sync car with more efficient chips?

[00:33:20] That really more sip electricity and chi-heating

[00:33:23] and cooling is supposed to do that.

[00:33:25] So I think that technology is gonna evolve very rapidly.

[00:33:30] Again, you see the size of the market.

[00:33:31] So there's a lot of investment

[00:33:33] that's gone into getting that.

[00:33:35] So I think responsible AI for us again

[00:33:38] is back to symbiotic, secure and sustainable.

[00:33:42] And then when we go into organizations

[00:33:46] the way we handle the ethical considerations

[00:33:49] like ethics are tied to your values, right?

[00:33:52] I think ethics, like it's almost like I'm going to law school

[00:33:56] ethics is not, it's always a gray area.

[00:33:58] It's driven by what your values are

[00:34:00] and what you're driving.

[00:34:02] So for an organization if you're consistent

[00:34:06] with their values and you live your daily life

[00:34:09] based on that piece, that's great.

[00:34:11] But how do we actually implement that?

[00:34:14] We actually say governance.

[00:34:18] Governes these areas that I told you about

[00:34:20] like in terms of responsible AI

[00:34:23] and the way we implement governance

[00:34:26] in organizations where technology is moving so quickly

[00:34:29] is first of all, you need to give people guidance

[00:34:33] as to what you can and what you can and chat throughs.

[00:34:37] And given that technology is that advanced

[00:34:40] I can actually put in guardrails, right?

[00:34:42] I can automate some of the things like so I can tell you

[00:34:45] don't use solution A, use solution B, right?

[00:34:49] That could be a guidance, right?

[00:34:51] The governance rule is we're not gonna

[00:34:54] if our company's data be used by one of these outside

[00:34:59] large language model providers, right?

[00:35:01] And so that's the guidance.

[00:35:05] So the guidance is given where these solutions are

[00:35:08] don't use solution A, use solution B

[00:35:10] that's the specific guidance that we've given

[00:35:13] but that's not enough.

[00:35:15] Then what then the guardrails that we've actually put in

[00:35:17] is from our machines, from our laptops

[00:35:20] some are within our environment

[00:35:24] we block solution A, right?

[00:35:27] In terms of you don't, you don't like yeah

[00:35:29] we told you what you do in your personal time

[00:35:32] on your personal devices that's up to you

[00:35:34] but if you're gonna be using corporate device

[00:35:36] I'm gonna block this one, right?

[00:35:37] And so that try out of have the right governance

[00:35:41] establish the guidance so that people know

[00:35:44] that this is not us coming in like

[00:35:46] I'm also one of those old IT guys

[00:35:48] like us coming in and say no to everything.

[00:35:50] No, we've given you guidance

[00:35:53] but then here's your, and we'll just make sure

[00:35:56] we're putting the guardrails in place

[00:35:58] so that knowingly or unknowingly

[00:36:01] you don't kind of rear away from the guidance we've given you.

[00:36:06] 100% with you.

[00:36:07] I'm glad you mentioned the chip maker

[00:36:09] about a couple of days ago

[00:36:11] because it really struck me this intersection

[00:36:14] between AI and sustainability

[00:36:16] because the big headlines from that big event

[00:36:19] were that the chips were 30 times faster

[00:36:22] but what didn't make all the headlines

[00:36:23] was that they were 25 times more energy efficient

[00:36:27] which is huge.

[00:36:28] So looking ahead, are there any other predictions

[00:36:31] for the evolving intersection of AI

[00:36:34] and sustainability and how that synergy

[00:36:37] might better shape the future of technology

[00:36:40] both in business and society too?

[00:36:43] Well I do think again

[00:36:47] unfortunately or fortunately

[00:36:48] the innovation follows where the money is.

[00:36:52] So part of the reason why

[00:36:57] the current state is where it is

[00:36:58] is this all started with graphics processing units.

[00:37:03] To be able to do what we're doing with Zoom

[00:37:05] and others on a screen, your GPUs

[00:37:08] you had to manipulate a lot of data very, very quickly

[00:37:11] a lot of mathematical data,

[00:37:13] my matrix calculations very quickly

[00:37:15] that's kind of how this old GPU thing got formed saying

[00:37:19] yeah as center processing unit is not that good at doing this

[00:37:22] so we need to do something specialized.

[00:37:25] What started as a specialized chip on motherboards

[00:37:28] about 15, 20 years ago

[00:37:30] people started to say when the whole

[00:37:32] blockchain cryptocurrency thing was a big deal

[00:37:35] they started saying oh I can now throw GPU farms

[00:37:37] to go solve this thing right?

[00:37:39] And then when that starts crashing

[00:37:41] like you start to see the market waver again

[00:37:43] and now AI comes over

[00:37:45] and say oh wait I found a new use for GPUs in AI

[00:37:48] because you need to process this much information

[00:37:51] and that's kind of the way I look at it.

[00:37:54] They had the right technology for the problem

[00:37:58] but it was not a technology that was built for the problem

[00:38:02] it's almost like in the medical field

[00:38:04] at least in the US

[00:38:06] people were told to prescribe aspirin

[00:38:09] for anyone over 40 years old

[00:38:10] because it helps in the blood

[00:38:13] and reduces stroke and things like that

[00:38:15] now they've reversed it

[00:38:16] but it was not built for that purpose

[00:38:19] but it's an off-labeled use that you found for it

[00:38:23] and that's kind of what's happened with the GPU thing.

[00:38:27] What's changing is people realize

[00:38:30] that there's a different way to do this extensive map

[00:38:33] and the speed at which you can do it

[00:38:34] and how much compute power

[00:38:37] you don't have to solve it

[00:38:38] the same way we solve graphic search

[00:38:40] there's a different way to do it

[00:38:41] whether it's tensor units or different places

[00:38:43] and so you're starting to see a lot of investment

[00:38:47] but four years, four or five years ago

[00:38:48] a lot of VC money was going into this

[00:38:50] because they saw it ahead of time

[00:38:53] and so I expect to see some really innovative tips

[00:38:57] come out here very very soon in the market

[00:39:00] that's not going to unseat the leading players

[00:39:04] but it's going to give people alternatives

[00:39:07] and especially people who do care about sustainability

[00:39:11] and want to take the benefits of the AI

[00:39:14] they'll have choices to make

[00:39:16] saying yeah I can do it this way

[00:39:17] or I can do it this other way

[00:39:20] and we drive that

[00:39:21] and by the way, like the minute

[00:39:24] that sustainability thing becomes very big

[00:39:27] all the leading chip makers are also going to pivot

[00:39:30] because they don't want that

[00:39:31] they're not going to sit back

[00:39:32] and they are doing some pretty old research

[00:39:34] in that space to drive it

[00:39:36] but today it's just

[00:39:40] you can sell GPUs to pretty much anyone

[00:39:44] whether they know what they want it for

[00:39:46] or not they want a GPU

[00:39:47] right in a sense

[00:39:48] that's the deal

[00:39:51] and so like they're playing to the market

[00:39:53] and more part of that is fantastic

[00:39:55] like now I've got so many friends who work

[00:39:58] at all of these guys

[00:40:00] NDE, AMD, SuperMicro and others

[00:40:05] are seeing the benefits of the boom

[00:40:08] which is fantastic

[00:40:09] and I know that companies like NVIDIA

[00:40:11] got such a great value

[00:40:13] Assistant Jensen is just one of the better CEOs

[00:40:17] I've ever had the pleasure to meet

[00:40:19] he's making those investments in sustainability

[00:40:23] but it's like he got this on the back of my track

[00:40:25] I should be able to sell it out

[00:40:26] but let me make sure I get the next generation ready

[00:40:29] as well

[00:40:31] Absolutely love it

[00:40:32] and I'm quite conscious on behalf of business leaders

[00:40:34] listening all around the world

[00:40:36] keeping up to speed with the pace of technological change

[00:40:39] and everything that we've talked about today

[00:40:41] will be quite daunting for many people

[00:40:43] and I'm conscious

[00:40:46] still right in the heart of the eye of the storm here

[00:40:50] where or how do you self educate

[00:40:52] to keep up to speed with everything

[00:40:55] I leverage the tools like it

[00:40:57] so I am the AI augmented execsers

[00:41:02] as an example

[00:41:04] for the last three or four years

[00:41:06] I use Grammarly

[00:41:09] I have used Grammarly

[00:41:10] and it's been on my desktop

[00:41:12] every desktop that I've had

[00:41:14] as someone who

[00:41:15] where English is not my first language

[00:41:18] I spent a lot of time

[00:41:20] creating my first draft

[00:41:21] and second draft and third draft

[00:41:23] even if it was not an email

[00:41:24] because you want to get it right

[00:41:26] I don't have to worry about it

[00:41:27] because that's the

[00:41:29] that buys me some time back

[00:41:30] raising out of things that I used to do before that

[00:41:33] it has bought me some time back

[00:41:35] as technology is evolved

[00:41:37] I've stopped using traditional search engines

[00:41:40] and I go to places like

[00:41:42] perplexity.ai

[00:41:43] right and perplexity does a lot more detailed

[00:41:46] search with references and others

[00:41:48] and I'm not going to get

[00:41:50] ads popping up

[00:41:51] where you have to pay the 20 bucks

[00:41:52] and that 20 bucks per month

[00:41:53] is well worth it

[00:41:55] because when I need a topic

[00:41:58] research

[00:41:59] I go there and put my question

[00:42:01] enough for the next five days

[00:42:03] so like it's really

[00:42:05] these tools have allowed you to

[00:42:08] buy back time in your day

[00:42:10] right in your work

[00:42:13] and same thing with

[00:42:15] with a lot of these things

[00:42:16] like whether it's Claude or chat

[00:42:17] chat GPT or any of those functions

[00:42:21] you know my wife loves the fact that

[00:42:23] she can plan our trip

[00:42:25] and get a nightmare

[00:42:26] by just sitting in front

[00:42:27] and doing some prompts with her

[00:42:29] and yeah we're

[00:42:31] headed out to Malta in Sicily

[00:42:33] here in the next month or so

[00:42:36] and she's got the agenda already planned

[00:42:37] right and that took

[00:42:40] about 30-45 minutes to

[00:42:42] interact with chat GPT

[00:42:44] do it

[00:42:45] so what it does is if you're smart

[00:42:47] if you're literate

[00:42:48] and you're smart about it

[00:42:49] you're buying back time in your day

[00:42:51] and then it's a question of

[00:42:53] what do you do with that time

[00:42:55] I spend about half of it

[00:42:57] with my family

[00:42:58] because you don't want to be aware

[00:42:59] but the other half

[00:43:01] I actually have between 6 and 7 p.m.

[00:43:03] every day time set aside to learn

[00:43:06] right so whenever I see something

[00:43:07] come through I'll throw it into my inbox

[00:43:09] right and

[00:43:11] and like 6 to 7

[00:43:13] you open it up

[00:43:13] you go do the detail

[00:43:15] at research

[00:43:16] oh what's this person say

[00:43:17] right there's

[00:43:18] there's a few really thoughtful leaders

[00:43:21] out there who actually do

[00:43:22] some phenomenal blog posts

[00:43:24] you go read up on them

[00:43:25] or they think about it

[00:43:27] right and then

[00:43:28] you combine that with your 30 plus years of experience

[00:43:30] you start to kind of stay current

[00:43:33] with with things going in

[00:43:35] and but but back to the question

[00:43:37] if I had to learn the tech

[00:43:40] that's changing every day

[00:43:42] might as well give up

[00:43:43] right

[00:43:44] might as well

[00:43:45] because it's

[00:43:46] the tech has become so vast

[00:43:48] and so broad

[00:43:50] that all you have these days are specialists

[00:43:53] somebody who can do spark

[00:43:55] and even within spark

[00:43:56] they know Apache spark

[00:43:57] very very well

[00:43:58] and like

[00:44:00] because of these

[00:44:01] breadth has increased

[00:44:03] the only way people start

[00:44:05] being experts is to

[00:44:07] is to kind of be more silent

[00:44:09] right and that's

[00:44:10] I think AI reverses that

[00:44:13] AI starts to reverse that trend

[00:44:15] that we went down

[00:44:16] like the last 15 years

[00:44:17] right where it's like

[00:44:18] more and more specialization

[00:44:20] you're going to need some of them

[00:44:21] but not in the numbers we've needed

[00:44:23] when you kind of pull it back

[00:44:24] and you actually embed AI into this

[00:44:27] I can do with

[00:44:28] far fewer of those

[00:44:29] but far more generalists

[00:44:31] who know how to navigate

[00:44:33] the broad spectrum of tech

[00:44:36] well I could chat with you

[00:44:38] for hours about this stuff

[00:44:39] but I think that's a beautiful moment

[00:44:41] to end on

[00:44:41] but before I let you go

[00:44:44] for anyone listening

[00:44:45] just want to find out more information

[00:44:46] about Rackspace

[00:44:47] maybe explore some of the

[00:44:50] topics we discussed today

[00:44:51] is there any way in particularly

[00:44:52] you would like to point everyone listening

[00:44:54] and also how they can connect with you

[00:44:56] so first of all at Rackspace

[00:44:59] we are a pure play

[00:45:02] about an AI company

[00:45:03] right and what that really means is

[00:45:06] we help our customers

[00:45:08] embrace cloud technologies

[00:45:10] many times it is the public cloud

[00:45:13] with AWS and Azure and Google

[00:45:15] other times it's our own private cloud

[00:45:17] because our heritage as a company

[00:45:19] has been managed whole state

[00:45:22] right and then we

[00:45:24] when the internet was new

[00:45:25] we were the first to introduce managed whole state

[00:45:27] right when

[00:45:28] when virtualization was big

[00:45:31] we invented OpenStack with NASA

[00:45:34] so like this is a company

[00:45:35] that's got that innovative piece of it

[00:45:36] so we have a really good private cloud operations

[00:45:39] so that's all we do

[00:45:40] we do public and private cloud

[00:45:41] and we help customers get there

[00:45:44] the other piece that's unique about us

[00:45:46] is we spend a lot of time

[00:45:49] operating the application

[00:45:51] and operating the data piece

[00:45:52] so you gain some very good insights

[00:45:54] into how to use AI and others

[00:45:56] when you see things operate

[00:45:57] on a day in and day out basis

[00:45:59] because if you just have one or two instances of it

[00:46:01] it's not a pattern

[00:46:02] you can't automate it

[00:46:04] but if you can see these things every single day

[00:46:06] you can do that

[00:46:07] which is kind of why we launched our

[00:46:09] their units to focus on AI

[00:46:13] so where that AI and cloud company

[00:46:16] and

[00:46:18] with the underpinning

[00:46:21] that technology DNA

[00:46:22] that's kind of kept us company

[00:46:24] that's who we are

[00:46:26] or

[00:46:27] if you kind of ask any rack

[00:46:29] or who's been here or me

[00:46:30] but our customers I'll say we are a

[00:46:32] we're known for our fanatical sport

[00:46:35] and fanatical sport to us

[00:46:37] is put the customer first

[00:46:39] put the customer first

[00:46:41] and try to solve the problems

[00:46:43] like when they have it

[00:46:45] and even if they don't have a problem

[00:46:47] if there's things that you can do to assist

[00:46:50] try to do that

[00:46:51] and if you take care of your customer

[00:46:54] then the business gets taken care of

[00:46:55] right that's in a nutshell who racks faces

[00:46:59] as I said I run

[00:47:01] AI and sustainability for rack space

[00:47:03] I mean their CTO

[00:47:04] so I have

[00:47:06] our internal IT

[00:47:07] and

[00:47:08] everything else

[00:47:09] I'm on LinkedIn

[00:47:10] I'd say anyone wanting to reach out

[00:47:13] please do reach out

[00:47:15] and connect with me

[00:47:16] and if you want to find out more about rack space

[00:47:19] go to rackspace.com

[00:47:22] or fair.rackspace.com for our AI initiative

[00:47:26] so that's

[00:47:27] that's who we are

[00:47:28] right we'd love to kind of

[00:47:30] if you've got a

[00:47:31] challenges adopting the cloud

[00:47:33] or you have

[00:47:35] an opportunity where you're looking to leverage AI

[00:47:38] for competitive advantage

[00:47:40] and talk to us

[00:47:41] and

[00:47:42] we'll put you first

[00:47:44] because that's what we do

[00:47:46] well so I'll get those links added to the show notes

[00:47:49] so people can find you

[00:47:50] nice and easily

[00:47:51] we covered so much there in a short amount of time

[00:47:54] from how organizations

[00:47:55] could start to leverage AI

[00:47:57] to aid sustainability initiatives

[00:47:59] explore some of those new trends emerging

[00:48:01] when it comes to gen AI workloads

[00:48:03] and also the strategic opportunities

[00:48:05] and a few challenges that arise

[00:48:07] with the adoption of gen AI

[00:48:09] and as I said a few moments ago

[00:48:10] we could chat for hours on this stuff

[00:48:12] but thank you so much

[00:48:13] for taking the time to sit down

[00:48:15] and share some of your insights for now

[00:48:17] no worries at all Neil

[00:48:18] it was a pleasure

[00:48:19] thank you

[00:48:20] I think it's evident that the landscape of technology

[00:48:23] and sustainability is on the cusp

[00:48:26] of a significant transformation

[00:48:28] and the adoption of gen AI

[00:48:30] offers a promising avenue for organizations

[00:48:33] to not only enhance their operation and efficiency

[00:48:36] but also to advance their sustainability goals too

[00:48:41] but this is a journey

[00:48:43] accompanied by a unique set of challenges

[00:48:46] from navigating the ethical considerations of AI

[00:48:49] to fostering a culture of continuous learning

[00:48:52] and adaptation within the workforce

[00:48:55] all to ensure that nobody gets left behind

[00:48:58] I think Serene's insights remind me

[00:49:00] that the path forward requires that delicate balance

[00:49:03] between leveraging cutting edge technology

[00:49:06] and remaining steadfast in our commitment

[00:49:08] to sustainability

[00:49:11] so as we ponder this future of AI

[00:49:13] and its impact on business and society

[00:49:16] one question remains though

[00:49:19] how will we as individuals

[00:49:21] as organizations

[00:49:22] how will we embrace and adapt

[00:49:25] to these technological advancements

[00:49:27] and ensure a sustainable

[00:49:30] and inclusive future

[00:49:32] that's right

[00:49:33] this is a dialogue

[00:49:35] not a monologue

[00:49:36] so I invite you to share your thoughts

[00:49:39] I want you to join the conversation

[00:49:40] on how AI can serve as a catalyst for positive change

[00:49:44] we've seen the bad stuff

[00:49:45] it's all over our news feeds

[00:49:47] but let's restore the balance

[00:49:48] and look how we can find a better way forward

[00:49:51] be the change we want to see in the world

[00:49:53] so where do you see the biggest opportunities?

[00:49:55] where do you see the biggest challenges

[00:49:57] in integrating AI with sustainability initiatives?

[00:50:01] let's keep this dialogue going

[00:50:02] and explore together the myriad ways

[00:50:05] in which technology can foster that better tomorrow

[00:50:07] that we all won

[00:50:09] as always email me

[00:50:10] techblogwriteroutlook.com

[00:50:12] Twitter, LinkedIn, Instagram

[00:50:14] just out Neil C Hughes

[00:50:15] send me a quick message

[00:50:16] don't just hit the connect button

[00:50:18] tell me you listen to the podcast

[00:50:20] it'd be great to meaningfully connect

[00:50:22] with each and every one of you out there

[00:50:24] but that's it for today

[00:50:25] so please

[00:50:26] join me again tomorrow

[00:50:27] we'll have another topic

[00:50:28] that we'll explore together

[00:50:30] but thank you for listening today

[00:50:31] and until next time

[00:50:35] don't be a stranger