CIOs don’t need to own AI, but they do need to shape how it works across the business.
Despite two decades of effort, many digital transformation initiatives have fallen short. Not because the technology failed, but because of misaligned expectations, fragmented execution and a lack of integration between business and IT.
As companies race to harness AI, the CIO is sometimes viewed as the natural leader, and at other times set aside. No matter who leads, the CIO remains a central player, given that AI depends on data, infrastructure and tools – areas they traditionally manage.
To help reset the conversation, we outline six strategic opportunities for CIOs in the AI adoption race and how to avoid common myths and missteps that undermine progress.
Opportunity 1: Become an enabler of business transformation
The myth: AI is a technology problem, so the CIO should own it entirely.
The reality: While AI relies on data, platforms and tools, technology is only one piece of the puzzle. AI success depends more on organisational design, process change, cultural shifts and new capabilities than on tech deployment alone. When the CIO is expected to own AI without executive alignment, critical changes in how the business works are often overlooked.
The opportunity for a strategic CIO: Step into the role of orchestrator rather than owner. Collaborate with the CEO and business leaders to align AI with strategic objectives and shape the conditions for change across business processes and talent. Be the bridge between vision and execution.
Opportunity 2: Upskill and lead enterprise integration
The myth: The IT function is lagging behind, so companies should sideline the CIO in favour of a new upskilled leader.
The reality: Some companies, frustrated by legacy tech and slow change, create digital roles outside of IT. But separating digital from IT often leads to overlap and disconnected infrastructure. It also weakens cybersecurity and governance. More importantly, it ignores the CIO’s potential to lead if given the mandate and support.
The opportunity for a strategic CIO: Take ownership of harmonising enterprise architecture across infrastructure, data and applications, and upskill yourself and your leadership team. AI capabilities must be developed as a joint enterprise between IT and the business, with cross-functional collaboration embedded from design to deployment.
The CIO must also navigate the trade-offs between standardisation for scalability and flexibility for innovation. Show the C-suite that the CIO can be the enabler of modern business models.
Opportunity 3: Enable responsible innovation at scale
The myth: If we just give teams access to generative AI (GenAI) tools, innovation will take care of itself.
The reality: Uncoordinated access to GenAI tools creates fragmentation, risk, duplicated costs and little enterprise learning. Without guidance, teams run local experiments that rarely scale or align with company goals.
The opportunity for a strategic CIO: Build the infrastructure and policies to support safe experimentation at scale. Provide tools that are secure and compliant, develop internal guidelines for prompting and usage and create enablement programmes to upskill users. The CIO becomes the guardian of coherence, not the blocker of innovation.
Opportunity 4: Move from pilot projects to scalable AI portfolio delivery
The myth: Let’s run a few proofs of concept (PoCs) and figure out what works.
The reality: This approach often leads to “PoC purgatory”: disconnected trials that fail to scale or generate ROI. Without a long-term roadmap and platform readiness, early efforts stall or become isolated successes with no enterprise traction.
The opportunity for a strategic CIO: Create a scalable foundation: enterprise data platforms, integration capabilities and MLOps (machine learning operations) pipelines. Introduce portfolio thinking, prioritise use cases with strategic relevance, define success criteria early and plan for industrialisation from the start. Guide the organisation from experimentation to execution.
Opportunity 5: Build enterprise-wide data readiness and governance
The myth: If we hire data scientists, we’ll become an AI-driven organisation.
The reality: Even the best data scientists are limited by poor data access and unclear business context. Data readiness does not come from technology alone. It requires strong data governance, and governance starts when business units take ownership of their data as a strategic asset.
The opportunity for a strategic CIO: Lead the development of an end-to-end data supply chain, from ingestion to consumption. Standardise data flows, improve quality and define cross-functional ownership. Embed data talent in business domains and establish a culture where data is seen as a shared responsibility, not just an IT asset.
Opportunity 6: Inspire business reinvention and shape the AI agenda
The myth: The CIO should just execute what the business decides.
The reality: AI is not a tool to plug in – it is a transformation that impacts governance, operations, risk, ethics and organisational behaviour. Expecting the CIO to just execute ignores their unique enterprise-wide perspective and underuses their strategic insight.
The opportunity for a strategic CIO: Take a seat at the table as a co-leader of transformation. Partner with the CEO and C-suite to shape AI priorities and build governance that supports responsible scaling. Use deep understanding of technology and business interdependencies to inspire reinvention across the company, and within the IT function itself. By deploying AI internally, the CIO can also demonstrate AI’s value firsthand and set the tone for adoption across the enterprise.
A company-wide effort, led from the top
AI is not a side project or a new toolset. It is a strategic transformation. Compared to earlier waves of digital transformation, AI has the potential to go deeper and deliver far greater impact.
Yes, the CIO plays a central role in enabling this shift. But AI adoption cannot be a CIO-only mission. Without CEO sponsorship, business ownership and enterprise-wide collaboration, even the most technically sound initiatives will struggle to scale.
