CIOs are expected to guide transformation initiatives—moving to the cloud, embedding intelligence, modernizing systems—and to ensure those changes produce clear results. Yet technology is rarely the biggest obstacle. The real challenge is managing the complexity that comes with multiple systems, fragmented data, and inconsistent decision making.

Research shows the stakes are high: According to Gartner, one of the biggest concerns for CIOs is that many organisations lack data, analytics or AI readiness. Teams with “AI-ready data” see markedly better outcomes, but a large share are either not ready or unsure. McKinsey similarly warns that without clear strategy and strong collaboration across functions, digital and AI transformations often underdeliver. 

THE PROBLEM: COMPLEXITY AND MISALIGNMENT

Too often, digital transformation leads to more dashboards, more platforms, and more data sources—each with its own processes, metrics, and owners. Instead of clarity, organisations get silos. Reporting conflicts. Delays. Low adoption.

McKinsey calls digital transformation “the rewiring of the organization,” which means that alignment across domains—technology, operations, customer experience—is nonnegotiable. Gartner, in its 2025 CIO report, notes that many legacy operating models are overburdened and cannot support strategic new initiatives. CIOs must evolve the operating model to match expectations from the rest of the leadership.

To understand how to reduce IT complexity without adding risk, read our CIO’s guide here.. 

WHAT IT TAKES: FROM DATA TO STRATEGIC ACTION

To turn insight into impact, CIOs need to do more than collect data:

1. Enable AI-ready data and governance. Organisations that treat data readiness seriously tend to avoid many of the pitfalls of failed projects. Gartner expects that, by 2026, those without AI-ready data practices will have over 60% of their AI projects failing to meet business level targets. Companies must establish data governance, ensure data quality, and build pipelines that support real-time decision making. McKinsey emphasises federated models: a central function sets policy and standards, while business units build and maintain data products. Learn more about simplifying compliance and security for CIOs here.
   
   
2. Focus on talent and culture. Even with good data, organisations often lack the skill sets to exploit it. McKinsey found that 77% of companies report gaps in data talent (roles such as data engineers, architects, data scientists), and relatively few have programs designed to attract and retain them. Without culture change, even well-designed systems can be underused.
   
   
3. Simplify environments and reduce friction. Reduce the number of tools, streamline workflows, eliminate duplication. When CIOs organise around platforms and product ownership instead of point-to-point integrations, they reduce complexity and speed up delivery.
   
   
4. Measure what matters. CIOs must tie technology investments to outcomes: cost savings, speed, improved customer experience, risk reduction. Use metrics that reflect business value, not just IT performance. Also, tailor communication to the audience: different stakeholders may care about different outcomes. Gartner notes that many CIOs fail to adapt their message to executive perceptions, missing chances to build buy-in. 

READ MORE: How CIOs Can Build Revenue Resilience

HOW CIOS CAN LEAD CONFIDENT, MEASURED CHANGE

Here are steps CIOs can take to shift from guesswork to a data-led transformation:

• Define outcome goals first. Before selecting technologies or building systems, clarify what success will look like in business terms.
• Build cross-functional alignment early. Involve business unit leaders, operations, finance, customer care, etc. so that data flows, roles, and responsibilities are clear.
• Establish governance structures that balance central oversight and local ownership. Standards must exist, but local teams need enough autonomy to act.
• Invest in capability. Recruit or develop people with the right data skills; offer training; create incentives for insights and evidence based decision-making.
• Streamline toolsets and platforms so that teams aren’t working across dozens of disparate dashboards or reporting systems.
• Keep feedback loops tight. Collect real-world data from users and outcomes, adjust course as needed.
  
  

CONCLUSION

Digital transformation only succeeds when CIOs lead with data, not with assumptions. Organisations that align strategy, culture, governance, and technology are far more likely to deliver true value. 

CIOs who simplify complexity, build trustworthy data, and commit to measurable results help their companies avoid stalled projects and misallocated resources. In doing so, they shift transformation from risky experiment to strategic capability.