Pilot Purgatory: Breaking Free From AI Implementation Gridlock

The gap between AI investment and measurable returns has become a critical business challenge. While organizations pour billions into artificial intelligence technologies, a mere 25% of these initiatives deliver their expected ROI, creating what experts call "pilot purgatory" – where promising AI experiments fail to scale into enterprise-wide value.

TLDR:

• The Chief AI Officer (CAIO) role is emerging rapidly
• Organizations with CAIOs see 10% greater ROI on AI investments 
• Successful CAIOs focus on three key areas: measurement of business impact, teamwork with diverse skills, and authority with clear C-suite mandate
• AI transformation requires "10,000 small shifts" across culture, institutions and habits throughout the enterprise

Drawing from comprehensive research spanning 600 Chief AI Officers across 22 geographies and 21 industries, we explore the rapidly emerging CAIO role that bridges the technical-business divide. This pivotal position has grown from just 11% adoption in 2023 to 26% today, with two-thirds of organizations expecting to have one within two years. The impact is clear: companies with dedicated AI leadership see 10% greater returns on investment and are 24% more likely to outperform competitors on innovation metrics.

The complexity facing these leaders is substantial. A typical organization juggles 11 different AI models today (expanding to 16 by 2026) alongside tens of thousands of AI assets across fragmented data environments. Successful CAIOs navigate this landscape through three critical factors: measurement that captures broad business impact beyond project-specific ROI, diverse teams blending technical and strategic expertise, and clear authority with C-suite support. Organizations adopting more centralized AI governance move twice as many pilots into production with 36% higher returns.

We (Google NotebookLM AI) unpack the crucial C-suite partnerships required, from CEO sponsorship to CTO implementation support, while highlighting surprising tensions – like the 32% of CAIOs who view HR leaders as potential obstacles rather than enablers. For organizations still struggling to translate AI potential into business value, this exploration offers a strategic framework for bridging the investment-returns gap through dedicated leadership focused on embedding AI as a fundamental capability throughout the enterprise.

Chapters

• 0:00 The AI Adoption Paradox
• 2:10 The Emergence of the Chief AI Officer
• 5:40 When Organizations Need a CAIO
• 7:20 Managing AI Complexity and Models
• 9:33 C-Suite Collaboration for AI Success
• 14:12 Three Keys: Measurement, Teamwork, Authority
• 18:42 Action Steps for the C-Suite
• 21:23 Conclusion: 10,000 Small Shifts

Transcript

Speaker 1: 0:00

Welcome to the Deep Dive. Today we're plunging headfirst into, well, a fascinating paradox right at the heart of AI adoption Organizations. Everywhere, they've poured billions I mean truly staggering amounts of capital into artificial intelligence.

Speaker 2: 0:17

Huge sums.

Speaker 1: 0:19

They have the technology, they have the talent, but for so many that crucial leap from a promising proof of concept to full-scale measurable deployment just isn't happening.

Speaker 2: 0:29

Right, I think it's stuck.

Speaker 1: 0:31

Yeah, they're stuck in what people are calling pilot purgatory.

Speaker 2: 0:33

It's a significant challenge. You know, the foundational elements are there the tech, the people. But that ability to translate experimental success into real enterprise-wide value, that's proving to be a persistent hurdle for a lot of companies.

Speaker 1: 0:47

And this, for us, points directly to a really pivotal emerging role yeah, the chief AI officer, CAIO.

Speaker 3: 0:54

Yeah.

Speaker 1: 0:54

And this isn't just another tech executive. Think of them more as a vital translator, bridging that gap between, say, the strategic vision and the technical execution. They're like the stewards of AI value across the whole enterprise.

Speaker 2: 1:06

That's a good way to put it and our deep dive today. It's built on some really solid ground A comprehensive report from the IBM Institute for Business Value. They collaborated with the Dubai Future Foundation and Oxford Economics. And this isn't just theory they actually surveyed over 600 CAIOs.

Speaker 1: 1:25

Wow, 600.

Speaker 2: 1:26

Yeah, across 22 geographies, 21 industries, all in the first quarter of 2025. So it gives us this truly global and incredibly current snapshot of the role.

Speaker 1: 1:37

Okay, so our mission then, for you, our listener, is to really unpack what's central to this emerging pivotal role. Listener is to really unpack what's central to this emerging, pivotal role We'll explore. You know, when does an organization hit that tipping point where a CIO becomes well indispensable, Right? When is it really needed Exactly, and what do these CIOs need to actually succeed?

Speaker 2: 1:57

It sounds like an incredibly multifaceted job.

Speaker 1: 1:58

It definitely is and, maybe most importantly, the concrete steps they can take to drive higher AI ROI and, you know, get those AI initiatives out of pilot purgatory and measurable scaled success, ready to dive in.

Speaker 2: 2:09

Absolutely. Let's get into it.

Speaker 1: 2:10

Okay, so billions poured into AI, but the report says only a quarter of initiatives are actually delivering the results.

Speaker 2: 2:18

Yeah.

Speaker 1: 2:18

That's not just a gap, it's a chasm, it is stark. What do you think is the single biggest reason for this pilot purgatory? Is it just a lack of unified vision or something deeper, systemic maybe?

Speaker 2: 2:31

That's a critical question and our research shows well. Expectations for enterprise AI are sky high. Right Executives want scaled savings and growth fast, like within 18 months.

Speaker 1: 2:41

Yeah, that's ambitious.

Speaker 2: 2:42

Very, but the disconnect it often stems from just a fundamental inability to scale these things 60% of organizations still primarily investing in pilots.

Speaker 1: 2:52

Still.

Speaker 2: 2:52

Still, and since 2023, only 25% of AI initiatives delivered their expected ROI, so it's not just about throwing money at it.

Speaker 1: 2:59

Right.

Speaker 2: 3:00

Seems to be more of a systemic failure to connect that vision with the actual execution. It really highlights a profound need for dedicated leadership, Someone to guide AI from just experiments to you know, tangible value.

Speaker 1: 3:11

And the spending isn't slowing down either, which makes that ROI figure even more jarring.

Speaker 2: 3:17

Oh, far from it. Ai spending. As a percentage of IT spend, it increased a staggering 62% between 2022 and 2025.

Speaker 1: 3:25

62%.

Speaker 2: 3:26

Yeah, and CEOs? They're projecting annual increases of 31% over the next two years. Wow, so to actually unlock value from this massive investment, a growing number of organizations are now explicitly creating the CAIO role, specifically to accelerate and direct AI business outcomes.

Speaker 1: 3:44

Okay so the CAIO really emerges as a direct response, a solution to this ROI puzzle. Role specifically to accelerate and direct AI business outcomes. Ok, so the CAIO really emerges as a direct response, a solution to this ROI puzzle.

Speaker 2: 3:50

It seems so.

Speaker 1: 3:50

It sounds like this role is gaining traction fast. Then you said only 26% of organizations have CAIOs today.

Speaker 2: 3:56

That's right today, but that's already a big jump from just 11% back in 2023.

Speaker 1: 4:01

OK, so significant growth.

Speaker 2: 4:03

It's a rapid adoption trend and get this 66% of the people surveyed expect most organizations will have a CIO within the next two years.

Speaker 1: 4:10

Two years, okay, so it's becoming mainstream quickly.

Speaker 2: 4:12

Exactly, and the impact is already clear for those who have one Organizations with CIOs they see 10% greater ROI on their AI spend 10%, that's not insignificant. And they're 24% more likely to say they outperform their peers on innovation.

Speaker 1: 4:26

Okay, so real, measurable benefits.

Speaker 2: 4:29

Definitely and their core mandate. It's broad. It covers defining the AI strategy, directing implementation, managing the AI budgets and, importantly, developing change management strategies for AI adoption.

Speaker 1: 4:43

It's a clear, results-driven mandate, then I like that quote from Daniel Hall in the CAIO at WPP. He said my job is not just to tell a good AI story. My job is to make sure we are objectively measurably better than our competitors.

Speaker 2: 4:57

That really cuts to the chase, doesn't it?

Speaker 1: 4:58

It does High bar, but exactly what's needed.

Speaker 2: 5:01

It is. And this brings us to a crucial question for a lot of organizations listening when does this kind of dedicated AI leadership truly become? You know, indispensable Right, when do you need one? Well, the CIOs we surveyed. They pointed to two main triggers for their roles creation First, driving the AI strategy. Second, accelerating AI adoption. So they're the visionaries directing that AI powered change, but they're also effectively the glue holding these often disparate AI portfolios together.

Speaker 1: 5:28

Ah, the glue. So maybe that glue isn't as critical during the initial exploratory AI piloting phase. Perhaps less, so yeah, but it becomes absolutely essential when an organization needs to turn those you know promising pilots into actual enterprise wide programs.

Speaker 2: 5:44

Precisely.

Speaker 1: 5:45

Defining that clear direction, making sure all the teams are focused on shared, measurable goals.

Speaker 2: 5:50

Exactly, and to do that, the ideal CIO needs a pretty unique skill set. They have to speak the language of both business and technology.

Speaker 1: 5:58

A translator, like you said. Yeah.

Speaker 2: 6:00

And possess that deep AI expertise to really orchestrate transformation at scale. It's fascinating. Actually, 73% of the CIOs surveyed focused on data in their careers.

Speaker 1: 6:10

Data first makes sense.

Speaker 2: 6:11

But their backgrounds are also incredibly multifaceted. Most also have strong experience in business strategy. That's 57% innovation, 56% enterprise tech, 54% even operations, 38%.

Speaker 1: 6:24

So a real mix.

Speaker 2: 6:26

And that deep industry expertise, too, that's crucial for spotting those really high value AI opportunities specific to their sector.

Speaker 1: 6:33

Okay, let's talk about complexity, for a second AI introduces a lot of it. How many different AI models were organizations typically juggling today, because it feels like new ones are popping up constantly?

Speaker 2: 6:45

You're absolutely right. It's a rapidly expanding landscape, almost overwhelming sometimes. Yeah. So a typical organization today uses on average 11 generative AI models. There are them already. Yep and they plan to use at least 16 by the end of 2026.

Speaker 1: 7:01

16, okay.

Speaker 2: 7:02

And this creates massive integration and interoperability challenges, especially when you layer on top. You know potentially tens of thousands of different AI assets.

Speaker 1: 7:11

Tens of thousands.

Speaker 2: 7:12

That often disconnected data spread across the whole enterprise. It's a very fragmented ecosystem.

Speaker 1: 7:17

Wow 11 models now 16 soon, tens of thousands of assets. It sounds like trying to conduct an orchestra where every musician has different sheet music.

Speaker 2: 7:25

That's a great analogy. Exactly, and this is where a dedicated CIO operating from a more centralized position can be a real game changer. Well, they can identify those strategic opportunities across the board, they can invest in AI models and tools more strategically, avoiding duplication, and they can measure the broad business value, not just project by project.

Speaker 1: 7:45

Right, see the bigger picture.

Speaker 2: 7:46

This helps find crucial cost efficiencies, it helps prevent lock-in to specific vendors or models and it optimizes the entire AI portfolio for what the business actually needs. And it optimizes the entire AI portfolio for what the business actually needs. And, it's worth noting here, 61% of CAIOs actually control their organization's AI budget 61% control the budget.

Speaker 1: 8:05

That's significant authority.

Speaker 2: 8:06

It is.

Speaker 1: 8:08

It shows real influence that WPP CAIO Daniel Holm. He summed it up well again. He said when its industry is being disrupted by AI, a company needs someone with their finger on the pulse to make sure they place the right bets.

Speaker 2: 8:20

Strategic foresight.

Speaker 1: 8:22

That really speaks to the foresight needed to navigate this accelerating change, doesn't it?

Speaker 2: 8:26

Absolutely so. Given all this complexity and the strategic importance, what exactly do these CAIOs need to succeed?

Speaker 1: 8:34

Yeah, what does success look like and what do they need to get there?

Speaker 2: 8:36

Well, it's clear right off the bat the CIO is not an army of one.

Speaker 1: 8:40

No, definitely not.

Speaker 2: 8:41

Their whole mandate bridging business and tech, delivering value with AI. It inherently requires strong partnerships right across the C-suite. They can't possibly deliver on that broad mandate alone.

Speaker 1: 8:53

It's interesting, though, because the report mentions that, while CIOs prioritize things like defining strategy, directing implementation, managing budgets, the core stuff, but some of those difficult AI-related tasks seem to be lower on their priority list.

Speaker 2: 9:07

Like what.

Speaker 1: 9:08

Things like ensuring compliance with AI ethics and governance, managing staff for AI programs and measuring the success of AI investments, which we just said is crucial.

Speaker 2: 9:20

That is interesting.

Speaker 1: 9:21

It really highlights a need for stronger, maybe more defined collaboration, doesn't it? Perhaps even a clear delineation of who owns what?

Speaker 2: 9:28

It truly does. Let's maybe look at that C-suite alignment and the support that's so crucial for them. Take the CEO, for instance. They serve as the supportive sponsor. In fact, 57% of CIOs report directly to the CEO or the board.

Speaker 1: 9:41

That high up okay.

Speaker 2: 9:43

Yeah, so the CEO defines the CIO's mandate, provides that visible support needed to break down obstacles, drive adoption.

Speaker 1: 9:50

Sets the tone from the top.

Speaker 2: 9:51

Exactly. Then you have roles like the COO and the CSTO, your chief operating officer and chief supply chain officer.

Speaker 1: 9:58

Right the operations folks.

Speaker 2: 9:59

They're vital as transformation scalers, essential partners for actually integrating AI into the operating model, driving those productivity gains. Makes sense and the CDO, the chief data officer, obviously key the data engine, absolutely Collaborating on data strategy, quality governance, making sure data flows to the right places for AI to even work, let alone thrive.

Speaker 1: 10:21

And then the tech leadership CIO, CTO.

Speaker 2: 10:24

Your chief information officer, chief technology officer. They're the technology integrators working on the AI implementation roadmap, ensuring the enterprise IT infrastructure cloud security. All of it is actually AI ready.

Speaker 1: 10:35

Can't do it without them.

Speaker 2: 10:36

Nope and the CISO chief information security officer, also a crucial security and risk manager.

Speaker 1: 10:41

Especially with AI risks.

Speaker 2: 10:43

A very close partner in fostering security by design for AI, and that's critical, given that the report found over 25% of AI initiatives have been stalled or even failed due to security concerns.

Speaker 1: 10:54

A quarter, wow, okay, security is paramount.

Speaker 2: 10:57

Absolutely. And don't forget the CINO and CDIO. Chief innovation officer. Chief digital innovation officer.

Speaker 1: 11:03

The innovation catalyst Right.

Speaker 2: 11:04

Core allies in designing AI-centric solutions for operations products, customer experience, executing that digital transformation piece.

Speaker 1: 11:12

Okay. And then there's the CHRO chief human resources officer the change agent Okay, and then there's the CHRO Chief Human Resources Officer the change agent. This one has an interesting dynamic because the report shows 32% of CIOs actually see CHROs as detractors. Yeah, that figure stood out. Detractors yeah, their alignment on talent strategies, on skills identification, training it seems absolutely crucial for AI adoption. Ai-driven change relies so heavily on employee support and buy-in.

Speaker 2: 11:38

It really does.

Speaker 1: 11:39

That feels like a massive missed opportunity if that partnership isn't strong, a real disconnect.

Speaker 2: 11:43

Indeed it is. And this complexity, this need for collaboration. It brings us to how an organization actually structures itself for scaling AI.

Speaker 1: 11:53

Right. So when an organization decides, ok, we're going beyond pilots, we're scaling AI, what does that mean for its internal structure? Does it lean towards, say, decentralization, or is a more centralized model typically more effective?

Speaker 2: 12:09

That's a key question, and generally organizations scaling AI tend to move from more decentralized approaches towards more centralized or perhaps hub-and-spoke models.

Speaker 1: 12:18

Hub-and-spoke okay.

Speaker 2: 12:19

And this report shows a clear benefit. Caio is leading these more centralized models. They moved twice as many AI pilots into production Twice as many. And they see 36% higher ROI on their AI investments 36% higher ROI.

Speaker 1: 12:32

That's compelling.

Speaker 2: 12:33

It really is. There's a quote from Mohammed Al-Muttarib. He's the executive director and CAIO for the Road and Transport Authority in Dubai government.

Speaker 3: 12:40

Okay.

Speaker 2: 12:40

He stated it very clearly when it comes to the operating model, I am a big believer in centralization because without it there is no clear ownership. Centralization definitely sounds appealing for clarity, for accountability Makes sense, but in a field as dynamic, as fast moving as AI does, a centralized model ever risk, you know, stifling innovation or agility down at the local level. Are there tradeoffs?

Speaker 1: 13:04

That's a fair point and it's a common concern, while peer centralization provides that clear ownership and streamlines resource allocation, which is good Right, the hub and spoke model which is often used, it kind of allows for both. It allows for local experimentation within essentially defined strategy and governance framework.

Speaker 2: 13:22

Ah, so a balance.

Speaker 1: 13:24

Exactly. The key is finding that balance Strong central guidance for strategy, for governance, for standards, coupled with distributed teams who are empowered to implement and innovate within their specific business units or functions. It's really about coordinated action, not rigid top-down control.

Speaker 2: 13:39

That makes a lot of sense. Okay, so structure models. Now, how can CAIOs actually deliver that higher AI ROI we talked about? What are the practical steps, the key levers they need to pull? Well, based on the research, it really points to three key areas where the successful CAIOs consistently focus their attention.

Speaker 1: 13:56

Okay, what are they?

Speaker 2: 13:57

Measurement, teamwork and authority.

Speaker 1: 13:59

Measurement teamwork authority. Okay, let's start with measurement. This seems absolutely fundamental, yet it often gets overlooked or maybe poorly executed in a lot of big strategic initiatives, doesn't it?

Speaker 2: 14:12

It truly is fundamental and, you're right, often not done well. Success has to be clearly defined, upfront, with specific objectives, specific AI, key performance indicators or KPIs, right and, crucially, this needs to go beyond just project specific ROI broader impact yeah, looking at broader business impact things like revenue, profit, customer satisfaction, even employee productivity okay, interestingly, 72% of the CAIOs surveyed say their organizations risk falling behind if they don't measure AI impact 72%.

Speaker 2: 14:45

That's a strong consensus it is Yet nearly the same amount. 68% admit they initiate projects even if they can't measure their effects initially.

Speaker 1: 14:52

Wait, why would they do that?

Speaker 2: 14:54

Well, often because the most promising, the most potentially transformative opportunities, they're also the hardest to quantify, right at the beginning.

Speaker 1: 15:03

Ah, okay, the biggest bets are fuzzy at first.

Speaker 2: 15:06

Exactly so. A visible dashboard with the right KPIs becomes a really central tool, and organizations might need to consider broader, perhaps less traditional metrics, like entirely new revenue streams generated or the speed of innovation itself.

Speaker 1: 15:22

So it's about casting a wider, more strategic net for what success actually means in the AI context. Not just the easy to measure stuff Precisely Okay, that's measurement. Then there's teamwork we already established the CIO is definitely not an army of one.

Speaker 2: 15:36

That's right, and the team structure matters. The average CIO team size, according to the survey, is five people.

Speaker 1: 15:42

Just five. That seems small for such a big mandate.

Speaker 2: 15:45

It does, and the data suggests that smaller teams are actually less successful.

Speaker 1: 15:49

Okay, so size matters to some extent.

Speaker 2: 15:51

It seems so, and successful teams prioritize specific skills AI specialists, machine learning engineers and, importantly, business strategists.

Speaker 1: 16:00

That blend again tech and business.

Speaker 2: 16:02

Right, and the goal here isn't to duplicate what the existing IT department does, it's to complement it.

Speaker 1: 16:08

How.

Speaker 2: 16:08

By embedding these AI experts across the organization people who deeply understand the business needs, the industry specifics, the AI feasibility and the IT enablement required they create those crucial connective tissues between the potential of AI and the reality of the business.

Speaker 1: 16:25

Got it. Bridging the gap from within, okay, measurement, teamwork and, finally, authority. This seems like maybe a non-negotiable prerequisite for leading a transformation of this magnitude, doesn't it?

Speaker 2: 16:37

It absolutely is. Caios need a clear mandate. They need visible, unwavering support from the other. C-suite leaders. No question, ceo support, as you might expect, is the bedrock. That direct reporting line we mentioned helps. Sure but the CTO is also a crucial backer. They lead the teams that actually design, build, implement the AI solutions across the enterprise. That partnership has to be tight.

Speaker 1: 16:58

Makes sense. Yeah, tech implementation relies on the CTO.

Speaker 2: 17:01

Exactly, and then circling back to the CHRO, the potential detractor or potential ally. Right. While, yes, 32% of CIOs perceive them as detractors currently, if they can be engaged effectively, the CHRO can become one of the most powerful advocates for AI adoption Close. By streamlining the process, by showing employees how AI directly benefits their careers, by handling the upskilling and change management aspects that gap that 32% figure it really represents a significant opportunity to unlock further value and smooth the adoption curve.

Speaker 1: 17:36

Turning a perceived obstacle into a key enabler. That's smart.

Speaker 2: 17:40

It is.

Speaker 1: 17:40

You know this whole breakdown, measurement, teamwork, authority and the C-suite roles. It truly feels like a strategic playbook, like actionable guidance for every leader in the C-suite.

Speaker 2: 17:50

It really does. The report actually lays out specific actionable guidance for each key role.

Speaker 1: 17:54

Oh cool. Can you give us a quick sense of that, like for the CEO?

Speaker 2: 17:57

Sure For the CEO. It's fundamentally about empowering the CIO. Give them the authority, the resources they need, but also demand measurable business outcomes. Don't just accept AI projects.

Speaker 1: 18:07

Like demand results.

Speaker 2: 18:14

Exactly Build smart and secure AI partnerships. Inspire the employees with a clear vision for AI, while fostering that growth mindset needed for change Okay.

Speaker 1: 18:18

Clear mission for the CEO for AI. While fostering that growth mindset needed for change Okay. Clear mission for the CEO. What about the CIO?

Speaker 2: 18:22

themselves. What's their action list? For the CIO, number one is seek clarity on your role and mandate. Make sure it's defined. Then create and measure those clearly defined KPIs, tracking the broader value, not just project ROI.

Speaker 1: 18:34

Measure with the get.

Speaker 2: 18:35

Always Actively engage all C-suite colleagues yes, even the perceived detractors. Scale your team's impact by blending those diverse skills we talked about. Spearhead the move towards a more centralized AI operating model and develop a comprehensive roadmap for AI-enabled digital transformation.

Speaker 1: 18:52

That's a full plate it is. What about the COO, the operations leader?

Speaker 2: 18:56

For the COO. The focus is partnership. Partner closely with the CIO to really supercharge enterprise workflows with AI. Build bridges for collaboration between ops and the AI team. Operationalize AI effectively and safely. Establish rigorous quality assurance protocols for AI systems. And proactively spot and mitigate operational risks from AI.

Speaker 1: 19:15

Okay, making it real in the day-to-day operations.

Speaker 2: 19:18

Precisely.

Speaker 1: 19:19

And the tech leaders.

Speaker 2: 19:20

Yeah.

Speaker 1: 19:20

CTO, CIO, CBO, CISO, that group.

Speaker 2: 19:24

For them. It's fundamentally about building that flexible, scalable and secure AI foundation. Actively remove tech bottlenecks holding AI back. Ensure AI is secure by design from the start.

Speaker 1: 19:35

Critical.

Speaker 2: 19:36

Make sure the data is actually AI ready, break down those silos, co-create the AI governance frameworks with the CAIO and others, and foster a culture of innovation across all the tech teams.

Speaker 1: 19:46

Building the engine and keeping it running smoothly and safely.

Speaker 2: 19:49

You got it.

Speaker 1: 19:50

Okay, last one, the CHRO, the human side.

Speaker 2: 19:53

For the CHRO. The guidance really emphasizes bringing that essential human perspective to all AI initiatives.

Speaker 1: 19:59

People first.

Speaker 2: 20:00

Right. Build AI literacy across the entire organization. Co-create new AI-enabled workflows with employees. Proactively look at how AI can elevate current roles or even invent entirely new ones.

Speaker 1: 20:11

Future of work stuff.

Speaker 2: 20:12

Exactly Build a culture that actually embraces AI innovation rather than fearing it, and partner super closely with the CIO to lead those crucial change management efforts. Get the people side right.

Speaker 1: 20:23

Wow, okay, we've really unpacked a lot here. We've explored this pivotal role of the chief AI officer, connecting AI investments to real, tangible ROI. We've seen, when an organization really hit that point of needing a CAIO, the crucial support systems and collaborations they require.

Speaker 2: 20:42

A whole ecosystem around them.

Speaker 1: 20:44

Yeah, and those key areas measurement, teamwork and authority where they absolutely must focus to deliver scaled success. And we just touched on those concrete, actionable steps for every C-suite leader. It's truly an organization-wide journey.

Speaker 2: 20:58

It really is. It's a significant systemic shift in how organizations structure themselves and lead and it really promises to define success in the well the coming years.

Speaker 1: 21:08

Definitely feels that way. So, as we wrap up this deep dive, here's something for you, our listener, to think about. Consider this provocative thought you heard that quote earlier attributed to the UAE Minister of State for AI, saying that AI is not a singular breakthrough. It's 10,000 small shifts. It's cultural, it's institutional, it's a habit 10,000 small shifts.

Speaker 2: 21:29

I like that.

Speaker 3: 21:30

It's powerful, right. So, given this idea, how will organizations ensure that the chief AI officer's influence evolves? How does it go beyond just overseeing strategic initiatives from the top to truly embed AI as a fundamental habit, a cultural shift across every single level of the enterprise? What stands out to why you from this deep dive?