Artificial Intelligence has ceased to be a project of the tech department and has become a matter of corporate governance. According to the new global study by IBM Institute for Business Value, CEOs are beginning to redesign their executive committees, decision-making processes, and the distribution of power within the company to adapt to a stage where AI not only enhances tasks but also changes how work is done, decisions are made, and competition occurs.
The report, developed alongside Oxford Economics based on a survey of 2,000 CEOs and senior leaders across 33 geographies and 21 sectors between February and April 2026, points to a clear shift: companies aiming to derive real value from AI are not just adding tools to old structures. They are modifying workflows, responsibilities, incentives, and operational models.
The Rise of the Chief AI Officer
One of the most striking data points from the study is the growth of the Chief AI Officer role. 76% of surveyed organizations report having a CAIO in 2026, up from 26% the previous year. This jump reflects how much AI has become a strategic function, not just a technical one.
The emergence of this role does not mean that other executives can delegate AI entirely to one person. IBM emphasizes a more complex idea: the CAIO should have the authority to coordinate priorities, standards, and adoption criteria, but business results remain the responsibility of operational units. In other words, the AI leader can accelerate and organize transformation but does not replace CFOs, COOs, CHROs, or Business Leaders.
Pressure also extends to other senior leaders. 85% of CEOs believe all functional leaders will need to become tech-savvy within their areas. It is no longer enough for CIOs or CTOs to understand models, data, automation, and agents. Marketing, finance, HR, operations, legal, and customer service will need to understand how AI modifies their daily decisions.
The role of the HR Director also gains importance. 59% of surveyed CEOs believe the influence of the CHRO will increase over the coming years. This makes sense: as AI changes roles, tasks, productivity, training, and performance evaluation, people management is no longer a separate function from technology. IBM also notes that 77% of CEOs see a convergence between talent leadership and technological leadership.
Faster Decisions, but with More Controls
AI is also entering the decision-making arena. 64% of CEOs feel comfortable using AI-generated information to support major strategic decisions. This does not mean algorithms will replace leadership committees, but executive judgment will increasingly rely on analysis, simulations, recommendations, and agents capable of processing information in real-time.
The report indicates an even more pronounced evolution in operational decisions. Currently, CEOs estimate that 25% of operational decisions are made using AI without human intervention. By 2030, they expect this to rise to 48%. IBM highlights areas with clear rules and controls, such as price updates, inventory allocation, redirection of shipments, or automatic incident resolution.
The key will be to distinguish where autonomy adds value and where it could be risky. AI can be useful for repetitive, rapid, and measurable decisions. But in regulatory, legal, reputational, or ethical matters, human judgment will remain necessary. The challenge for companies will be to define clear boundaries: what the system can decide, when cases should be escalated, who is responsible for the outcome, and how the process is audited.
IBM also observes a decentralization of decision-making authority. 79% of surveyed executives confirm they are distributing decision-making within their organization. This trend aligns with AI adoption: if information arrives sooner and models can analyze it in real-time, companies try to enable teams closest to the problem to act without always waiting for multiple approval layers.
The Gap Between Enthusiasm and Actual Use
Despite strong interest from CEOs, workforce adoption still lags behind. The study shows only 25% of employees regularly use AI in their roles, though 86% of CEOs believe their employees have the skills needed to collaborate with these tools.
This gap is significant because it suggests the issue isn’t just training. Many companies have purchased tools, launched pilots, or created internal policies, but have not redesigned processes to give AI a real role in daily work. If an individual has access to an AI assistant but their approval flows, metrics, and responsibilities remain unchanged, it’s likely the tool will be underused or misused.
IBM summarizes this simply: the success of AI depends more on people’s adoption than on the technology itself. 83% of CEOs share this view. Between 2026 and 2028, respondents expect 29% of employees to need retraining for new roles, and 53% to require additional training to perform their current jobs better.
Therefore, transformation is not only about deploying models. It’s about how teams change. Organizations that have redesigned five key areas—technology, finance, HR, operations, and cross-functional collaboration—are four times more likely to have achieved their defined business objectives in their use cases, according to the report.
From Large Models to a Hybrid Strategy
Another important point is the shift in model strategies. IBM argues that competitive advantage will not simply come from using the largest available model but from selecting the right combination. In 2026, 39% of CEOs state that their organization mainly uses pre-trained foundational models. By 2030, this figure would drop to 13%, with half of organizations adopting a hybrid strategy combining foundational models, custom models, and smaller specialized models.
This aligns with an industry evolution. Large language models are useful for general reasoning, content generation, or open-ended tasks. However, many business functions can be better served by smaller, cheaper, faster models trained on proprietary data. In areas like customer service, predictive maintenance, finance, procurement, HR, or quality control, specialization may outweigh size.
The sovereignty of AI also emerges as a priority. 83% of CEOs see the importance of developing and maintaining AI sovereignty within their overall strategy. This includes control over data, models, infrastructure, compliance, intellectual property, and the ability to change providers when necessary. In regulated sectors, this issue will become increasingly relevant.
Quantum Computing Enters the Agenda
While the study focuses on AI, IBM also issues a warning regarding quantum computing. Only 46% of CEOs say they have a dedicated team to identify quantum use cases and their business value. However, among the most advanced AI organizations, 82% are already participating in one or more quantum ecosystems for access to knowledge, risk reduction, and learning before the technology reaches greater maturity.
This reflects a blend of technological strategy and long-term preparation. Quantum computing has not yet delivered broad commercial advantages but could impact materials, pharmaceuticals, simulation, logistics, optimization, and cybersecurity. The message for CEOs is that becoming an “AI-first” company will not be the final goal but a foundation for adapting to the next wave of technology.
The report concludes clearly for leadership teams: AI can no longer be managed as an isolated initiative. It requires authority, data management, governance, process redesign, training, and new ways to measure results. Companies focused solely on immediate efficiency gains may achieve savings, but those who redesign how they work will have more options to turn AI into growth opportunities.
The question for CEOs is no longer whether to adopt AI but which parts of their organization they are willing to change so that adoption makes sense.
Frequently Asked Questions
What is a Chief AI Officer?
A senior executive responsible for coordinating an organization’s AI strategy, setting priorities, standards, controls, and adoption criteria. Their role does not replace business leaders but helps organize the transformation.
Why does IBM say AI is changing senior management?
Because AI affects decisions, processes, talent, operations, and business models. According to the study, CEOs are redesigning roles, authority, and incentives to integrate AI into the enterprise, not just within the tech department.
Will AI make decisions without humans in companies?
Yes, in certain operational areas. Surveyed CEOs estimate that currently 25% of operational decisions are made with AI without human intervention, expected to rise to 48% by 2030, mainly in areas with clear rules and controls.
What should companies do to better leverage AI?
They should redesign workflows, train teams, define responsibilities, use the right mix of models, protect their data, and establish clear controls before expanding system autonomy.