The catalog “assembles them all together so [employees] can consume them efficiently,” Ali explains, noting that IBM also evolved its IT infrastructure to ensure employees could take and use the catalogued agents effectively and securely.
The idea, Ali stresses, is to reduce the need to replicate work — which not only wastes hours but slows down enterprise progress.
8. Reduce complexity and silos
According to the State of Digital Transformation 2026 report from TEKsystems, 38% of technology and business decision-makers surveyed said the complexity of their current environment, and its accompanying siloed mindset and behaviors, was a top barrier to transformation, topping the survey’s list of such challenges.
Those two things — complexity and siloes — slow transformation, TEKsystems’ Palaniappan says.
“The current functional structure within some organizations is set up for the large-scale transformation of the past, but you need a leaner, much more cohesive organization for the newer AI-driven transformation,” he explains.
Consider, for example, an organization where the sales department wants to use agentic AI to transform its lead-to-sales process. The sales department has its own data, systems, and workforce ready to work with agents. However, the initiative requires access to systems and data walled off in other parts of the organization. Chiseling away at those barriers, particularly if that work is done ad hoc to meet the needs of each separate project, puts a drag on the pace of transformation.
Palaniappan says CIOs would do well to reduce IT complexity and silos to support transformation in general as well as to boost the speed at which it happens. “Break down the walls between the different functions and make it more end to end, because transformation now is end to end,” he adds.
9. Anticipate user needs and new capabilities
Keeping pace is not enough, says Dan Inbar, senior vice president and CIO at Symbotic, which provides warehouse automation technology.
“As an IT organization, service provider, and transformation leader, we have a responsibility to stay not just current but ahead of both our user community and the rapidly accelerating pace of technological change,” Inbar says.
That means being “proactive in anticipating user needs and enabling new capabilities.” Put another way, Inbar says that “transformation must be intentionally, proactively, and thoughtfully led by IT — not by reacting to pressure, but by anticipating it.”
To do this, he says CIOs must become fully integrated, strategic partners.
“This requires aligning technical roadmaps directly with each business unit’s objectives so that high‑impact initiatives receive executive prioritization,” Inbar explains. “When IT and the business co‑develop goals, technology investments become purpose‑driven and tied to measurable outcomes rather than technical curiosity. This shift reinforces IT’s position as a primary engine of business growth.”
To do so, Inbar advises CIOs to begin by translating the business strategy into the technology capabilities required to achieve its goals.
“I’ve partnered closely with our business units to understand their target states and co‑develop the path to get there,” he adds. “IT isn’t just about technology; it’s about deeply understanding enterprise processes, and documenting and optimizing them — and only then automating them, once they’re truly ready.”
10. Develop an empowered cross-functional governance entity
Atilla Tinic, senior vice president and CIO of Qualcomm, points out that AI transformation differs from earlier digital efforts in significant ways.
“While digital transformation focused on automating processes, AI transformation focuses on intelligence and reasoning. As a result, AI should be more about decision-making, which means we all need to re-examine our workflows, interfaces, cloud workloads, data, and application strategies,” he says.
To bring needed speed to that task, organizations need ready-made oversight capable of quickly making decisions to move initiatives forward.
Tinic says Qualcomm established a cross‑functional governance entity to do just that.
“Bringing together leaders from IT, security, legal, HR, and the business helps organizations address data, privacy, and risk considerations upfront rather than slowing projects later,” he explains. “This kind of structure focuses teams on the highest‑value use cases, reduces duplication, and shortens the path from concept to secure deployment.”
Such cross-functional governance enables agility and speed by removing uncertainty, rework, and downstream risk, he says.
“Teams spend less time navigating approvals, re‑architecting solutions, or managing unexpected risk after deployment, which makes it easier to scale AI with confidence,” he explains.
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