Artificial intelligence is not another cycle of change. It is a structural shift in how organizations think, decide, and compete.
Every era has underestimated the leaders who moved early. From industrialization to digitization, the winners were not those who waited for certainty, but those who recognized inflection points and acted with intent. AI is such a moment—one that rewards decisiveness and penalizes hesitation. (View Highlight)
The CEO’s role has always been to lead through disruption. What AI changes is the velocity and consequence of leadership. Enterprises that succeed will operate AI-first—not as a layer of technology, but as a new operating model. Decision cycles will compress. Boundaries between functions will dissolve. Advantage will accrue to those who can learn, adapt, and execute faster than their competitors.
AI’s first dividend is productivity—freeing time, talent, and capital once consumed by friction. But productivity alone does not create advantage.
The real differentiator is how leaders redeploy that capacity. Growth will favor CEOs who reinvest aggressively, reimagine roles and workflows, and channel AI-driven insight toward new products, new markets, and new sources of value. (View Highlight)
This is where leadership becomes catalytic. CEOs are no longer just stewards of performance; they are architects of intelligence. As AI expands what organizations can see and know, leaders must decide what matters, align the enterprise around it, and move with speed and coherence. Strategy becomes continuous. Execution becomes inseparable from insight.
This is not reinvention for its own sake. It is evolution with purpose. AI does not replace sound leadership—it raises the standard. The shift is from managing activity to engineering outcomes; from protecting legacy advantage to building the next one. Organizations that embrace this mindset early will not just adopt AI—they will compound its impact over time.
History rewards leaders who recognize when the environment has changed and respond with focus, discipline, and intent. AI is not a distant promise.
It is here, it is moving fast, and it is redefining what effective leadership looks like. The future will belong to those prepared to lead at its speed. (View Highlight)
The C-suite could focus less on AI-powered productivity gains and more on business model transformation, led by executives who operate as a united front, not in siloed functions.
That’s why 2026 is the year CEOs must rewire the C-suite—redesigning how decisions are made, how authority is distributed, and how AI reshapes influence—while preserving the decisiveness and clarity enterprises need to move fast. Getting there takes proactive leadership. CEOs will need to work with their C-suite leaders to build execution mechanisms, incentives, and operating models all focused on driving these outcomes. (View Highlight)
That’s the clear message of new proprietary data gathered by the IBM Institute for Business Value (IBM IBV). Our research shows that CEOs who have the greatest success with AI are actively rethinking cross-functional collaboration and embedding AI across end-to-end workflows. They’re building organizations designed to thrive in uncertainty, where productive debate sharpens strategy and smart risk-taking is rewarded.
“Trying to take AI tools and squeeze them into the existing organization is extremely likely to be the wrong approach.” (View Highlight)
The reality of enterprise AI lags CEO expectations Percentages show that CEOs were overly optimistic about the pace of AI adoption in 2024, when nearly half expected advanced AI (defined as generative AI) to primarily drive growth by 2026. In 2026, only 10% say advanced AI (defined as agentic AI) is primarily driving growth. (View Highlight)
Still, CEOs anticipate rapid progress Percentages show that CEOs are even more optimistic about the results agentic AI will deliver in 2030, with nearly three-quarters expecting it will primarily drive growth. (View Highlight)
AI-first transformation starts at the top. CEOs know what to do. Consistency is what sets the best CEOs apart.
The CEOs who are rewiring the C-suite share key characteristics. They’ve created environments where work flows organically across functions by identifying and directing workflows that need to be transformed. They are actively rethinking who should have authority over what area of the business—then giving those leaders, especially their COOs and business line leaders, the power to change how work is done.
They’re also prioritizing AI-first operations by appointing a Chief AI Officer (CAIO) with real authority to orchestrate transformation enterprise wide.
And they’re creating new roles at every level to take advantage of AI. These leaders have already scaled 10% more AI initiatives enterprise wide than all other organizations—and they’re quickly building the foundation needed to extend their lead. (View Highlight)
The CEO still sets strategy, drives focus, and makes the final call. But the pace and stakes of that evolution are prompting CEOs to intentionally redesign the organization, with the goal of increasing speed, responsiveness, and collabora (View Highlight)
ation. When AI-first operations are the target, the lines between business units blur.
As strategic objectives become increasingly interdependent, C-suite roles are evolving. In fact, the CEOs we surveyed say they expect the influence of every member of the C-suite to increase between today and 2030. In functions such as marketing and HR where AI transformation started first and has impacted many teams and tools already, the expected increase is lower than other tech-centric areas, where AI integration may still be ramping up. (View Highlight)
In this context, the role of the CAIO has become critical. In 2026, 76% of organizations have someone in this position, up from just 26% in 2025.3 And 100% of these CEOs expect the influence of CAIOs to increase by 2030.
When they have real authority, CAIOs can enable calculated risk-taking across the organization. These leaders typically have a strong background in both data and business strategy, according to our 2025 CAIO Study, which means they can be the voice that sets clear AI transformation targets and provides guidelines that let teams accelerate without spinning out of control.4 The Chief Human Resource Officer (CHRO) role will also become more important, with 59% of CEOs saying the CHRO’s influence will increase over the next few years. This reflects that, in an AI-first enterprise, people must be managed in a more integrated way. Instead of limiting people management to the realm of HR, it becomes part of virtually every technological, operational, and financial initiative.
As AI continues to play a larger role in managing employees, breaking down the walls between IT and HR will become mission critical. Already, 77% of CEOs say talent and technology leadership roles are converging. Across the board, CEOs expect their C-suite leaders to reinvent themselves as cross-enterprise orchestrators rather than functional specialists. (View Highlight)
The C-suite of 2030 will need to be upskilled to become more AI-native, more technology-centric, more operationally integrated, and more inclined to work across ecosystems. That’s why 85% of CEOs say all functional leaders must become technology experts in their domain. The real difference won’t be the titles on the org chart but how those leaders work together—and how willing they are to challenge one another to evolve. Speed is the result of productive friction, not the absence of it.
In the rewired C-suite, every leader is expected to own outcomes, not just manage tasks. They’re accountable for identifying opportunities, making bets, and driving change—whether or not it falls neatly within their functional domain. The CEO’s role is to make that accountability explicit: who owns what outcome, who can decide without consensus, and what risks each leader is expected to take.
The rewired C-suite distributes decision-making authority so that leaders closest to the problem can act, within clear guardrails but without waiting for permission. This means designing decision architectures where authority is explicit, accountability is clear, and AI provides real-time intelligence. (View Highlight)
