Shorter Tenures, Higher Stakes: AI Forces a C-Suite Reinvention

The C-suite is being rewritten by AI

The classic exec playbook is expiring. Decision-making, strategy visualisation and operational oversight are being refactored by AI and automation. Over the next decade, many traditional C-suite skills will fade. What replaces them: AI literacy, orchestration and human leadership at scale.

From chief executive to chief orchestrator

Boards want faster results with fewer missteps. The top job will tilt from "vision + delegation" to "orchestration + scenario design," where leaders frame problems, run AI-driven simulations and guide execution. As technical tasks shift to machines, demand will rise for roles that fuse people and systems - think chief human-AI collaboration officer - to ensure augmentation, not friction.

"C-suite executives are facing a sharp rise in uncertainty, with many realising their current way of operating has reached its expiry date," said Michael Bikard, associate professor of strategy at Insead. Reinvention moves from choice to requirement.

Shorter tenures, higher stakes

CEO turnover is climbing. The average tenure for outgoing chief executives fell to 6.8 years this year, the lowest on record, according to Russell Reynolds Associates. Leaders are told to deliver long-term reform and short-term wins - a near-impossible balance.

Generative AI adds pressure. PwC's CEO Survey found 56% of global CEOs report efficiency gains, and nearly half expect profitability to rise within a year. Yet an MIT-linked study shows most pilots deliver no financial return, exposing a gap between enthusiasm and transformation. Many companies face a cliff if they keep operating the old way.

PwC CEO Survey | CEO Turnover Index (RRA)

What's moving to the centre of the table

A decade ago, finance and operations dominated the C-suite. Today, technology and sustainability sit in the middle of strategy, not at the edge. AI, data and carbon economics are now board-level discussions - not side projects.

Skills for the next decade

Executives across the Middle East see both risk and opportunity. In regional surveys, a majority of CEOs say their businesses will not be viable in ten years without change. The playbook: pair digital fluency with human-centric leadership.

"Every day we're advising CEOs how to pair digital fluency with human-centric skills," said Eyhab Abdeen, chief people officer and workforce transformation leader at PwC Middle East. Adaptability, humility and judgment matter as much as vision. Empathy and trust become core: machines can analyse; leaders must align people through uncertainty.

Regional focus: UAE, Saudi Arabia, Qatar

The UAE moved early with a Minister of State for AI and national-scale upskilling. Programs train government employees, schools integrate AI, and the Mohamed bin Zayed University of Artificial Intelligence builds deep talent. Dubai recently appointed 50 chief AI officers across government entities to speed adoption and governance.

Saudi Arabia is growing fast: an IBM-Dubai Future Foundation study says 22% of organisations have a chief AI officer, near the 26% global average. Qatar is classified as an "AI Practitioner" by BCG's 2025 GCC AI Pulse, with solid progress on infrastructure and governance.

New roles at the top

Titles like chief AI officer and chief sustainability officer are spreading, but the bigger shift is horizontal: AI and data capabilities are being embedded across every C-suite seat. Boards now look for leaders with a track record in digital transformation and the nerve to challenge old practices.

In the UAE, mandates push this shift. Federal entities are creating chief AI officer roles, while chief sustainability officers are central to strategy and reporting. Large enterprises are following with group-level AI/data divisions and senior leaders for digital and low-carbon agendas.

Talent scarcity - and pay to match

There's a shortage of executives who fluently connect AI, operations and people. The UAE is investing to close the gap with specialist universities and national programs. Compensation is adjusting: top executive packages increasingly tie incentives to AI and automation outcomes.

Governance and the human side

As AI handles more analysis, the human questions get louder: Which questions matter? What risks are we taking? Who is accountable? "Data may provide answers and guide decisions, but it is humans who must know which questions to ask," said Mr Bikard. Accountability stays with leaders - which means transparency, clear responsibility and strong ethical oversight.

The executive action plan

• Set an AI literacy baseline for the entire C-suite. Make it a requirement, not a nice-to-have.
• Adopt an "orchestrator" operating model: define decisions, run AI scenarios, pressure-test assumptions, then guide execution.
• Fund two tracks: quick efficiency wins (90-180 days) and capability building (12-24 months). Measure both.
• Create a human-AI collaboration mandate: reskill managers, redesign workflows and install guardrails for quality and ethics.
• Align incentives: tie a portion of variable comp to AI-driven outcomes and adoption, not pilots.
• Refresh board reporting: include AI risk, model governance and real ROI, not activity metrics.
• Build a talent pipeline: partner with universities, rotate high performers into data/AI roles and recruit selectively for scarce skills.

Where to upskill fast

If your executive team needs a structured path to AI fluency and role-specific execution, explore:

• AI courses by job function for board, CEO, COO, CFO and CHRO tracks.
• Popular AI certifications tied to automation, data, and decision support.

Looking ahead

By 2030, AI literacy will be assumed. Sustainability and digital execution will be embedded across leadership, not siloed. The risk is chasing hype; the cost of inaction is steeper: weaker competitiveness, lower investor confidence and a shrinking talent pool.

The signal is clear: reinvent the leadership model - or watch the market do it for you.