Lula Mohanty, Managing Partner for Middle East & Africa at IBM, explains why the Chief AI Officer is becoming a critical role for businesses worldwide.
Why do you think every organisation needs a Chief AI Officer now, not later?
I think it’s a matter of timing, focus, and attention. Today, almost every organisation has a CIO, CTO, or even a CDO. The CIO and CTO typically oversee information systems, IT architecture, product design, and related functions. The CDO role emerged when focus shifted to data.
A Chief AI Officer is the next natural evolution — someone dedicated to identifying the business processes that would benefit most from AI, ensuring AI is democratised within the organisation, driving adoption, and making sure the envisioned ROI is achieved.
This role won’t exist in isolation — it will be collaborative, working closely with the CIO, CTO, and CDO. It’s a coordinated model, not a competitive one.
In the UAE, for example, 53% of CIOs report directly to the CEO or board, compared to 39% in the broader region. This reflects a shift from viewing IT as purely operational to seeing it as a business driver. At IBM, we saw this first-hand when we ran our “What’s Next Challenge” last year. Across the organisation, we developed 178,000 AI solutions, which business units then evaluated and implemented based on their needs.
Currently, only 26% of organisations have a Chief AI Officer, but in the UAE, it’s already one in three. I expect this number to grow significantly as leadership increasingly sees AI not just as a tool for users but as a national and organisational force multiplier.
Your report suggests the hub-and-spoke AI operating model delivers higher ROI. Do you recommend a centralised or federated model?
Our research shows the hub-and-spoke (centralised) model can deliver up to 36% higher ROI. The key is implementing AI at an enterprise level rather than through siloed experiments.
In this model, there’s a centralised AI strategy, platform, and governance structure, with departments contributing their specific use cases. This ensures cross-functional impact — for example, an AI for supply chain efficiency would cut across procurement, finance, and operations.
At IBM, our own “Client Zero” transformation followed this model, generating $4.5 billion in productivity savings. We had a central team defining AI strategy, evaluating use cases, and designing enterprise architecture, while individual business units implemented AI into their workflows.
Scaling AI from pilot to production is often a major challenge. What’s the bottleneck?
This is the billion-dollar question. In the UAE, 76% of organisations are running AI pilots, but 38–40% say they struggle to scale. It’s rarely a vision problem — it’s an execution problem.
Scaling AI requires more than a working model. Beyond change management and adoption, the technical basics are critical: the right infrastructure, trusted data sources, strong governance, security, and skilled teams.
Often, scaling demands system and hardware rationalisation, new data architectures, and ensuring the surrounding ecosystem is ready. Building the pilot is often the fastest part — scaling it is where complexity emerges.
That’s why, before starting, we assess an organisation’s readiness to scale AI. With our “What’s Next” platform, we embed security, enterprise data architecture, API connectivity, and governance from the start, so AI can move from pilot to production smoothly and effectively.
The report also highlights half of CIOs now have direct ownership of AI budgets. How critical is this financial autonomy for delivering measurable impact?
It’s absolutely critical. If I remember the data correctly, about 79% of Chief AI Officers said they carry budgets — they are empowered with the financial resources to drive AI innovation. This autonomy allows them to allocate resources where they matter most.
AI is all about consistent prioritisation. There’s no shortage of ideas, but to take an idea into execution and scale, you need adequate resources. Successful CIOs spend significant time prioritising and building strong business cases before deploying AI. This also means rallying the organisation to identify the most impactful use cases — and that requires budget.
Change management is another key area. About 40% of CIOs prioritise it because every AI initiative will fail if adoption doesn’t follow. Budget control enables leaders to make architectural choices, bring in the right talent, and fund change management effectively.
With this empowerment also comes accountability. CIOs who report directly to the CEO are often expected to demonstrate ROI. Financial responsibility becomes both a functional and strategic role — driving top-line growth and bottom-line efficiency.
When you control the budget, demonstrating ROI becomes a key SLA. Being financially empowered and measured on outcomes creates a sense of urgency and focus, enabling faster and more impactful execution.
Do you see this remaining as a standalone role in the near future, or will it evolve into broader responsibilities like legal or innovation?
For the next few years, it will remain a central and pivotal role. The CIO role hasn’t gone away, the CTO role hasn’t gone away, and the CDO role hasn’t gone away — and I think you’ll see even more empowerment given to CAIO roles. It will become one of the core business roles, measured on output. This isn’t a “feel-good” or purely advisory role — it will be a full P&L role, with a budget and clear accountability to drive top-line growth and business efficiencies.
And who becomes responsible if an AI project fails?
Ultimately, the buck stops with the Chief AI Officer — or in some cases, the CIO as well. It’s like any other P&L in a company today: if sales don’t perform, sales leaders take primary responsibility, supported by product owners. You’ve touched on an important point — in the UAE, many companies embarking on large-scale AI ambitions are now redrafting their target operating models and incentive schemes for senior executives. This shift reinforces the idea that the role will evolve into a fully fledged P&L responsibility, where you have a budget and are expected to deliver measurable returns on it.
