Deloitte’s Global Technology Leadership Study finds that the rapid spread of artificial intelligence is fundamentally changing what is expected of CIOs, CTOs, CISOs and CDAO‑level leaders. Traditional leadership skills are no longer sufficient on their own: AI already shapes organizations’ strategic priorities and day‑to‑day operations.
Key responsibilities and expectations
The survey shows technology leaders are increasingly expected to convert AI initiatives into measurable business outcomes while also ensuring security, regulatory compliance and effective cross‑functional collaboration. More than 70% of respondents said they feel inspired or highly motivated about the future of the technology leadership role, but they also acknowledged the need to redefine that role as AI’s business significance grows.
Successful technology leaders must act both as strategic business decision‑makers and technical experts: aligning stakeholder interests, supporting organizational change, managing trade‑offs and ensuring technology investments deliver business value. The most effective leaders translate technological vision into commercial outcomes while navigating complex domains such as AI, architecture, cybersecurity, risk management and emerging technologies.
New risks and governance demands
Deeper integration of AI into business processes brings new types of risk and more complex governance requirements. The study emphasizes the need for much closer collaboration among technology, data, AI, cybersecurity and HR leaders so that security, compliance and resilience are embedded from the earliest stages of development and deployment.
Kiss Dániel, Deloitte’s Central Europe leader for Technology Strategy & Transformation, warned that while AI is undeniably influential, it must not become the sole focus. Concentrating disproportionate resources on AI risks sidelining broader business objectives and exacerbating fragmentation and efficiency problems AI was meant to solve.
Where performance measurement is shifting
Respondents report that AI‑related outcomes dominate how they measure their own success: CIOs prioritize AI adoption and value creation, CTOs emphasize automation and faster innovation, CISOs focus on AI‑built security controls, and CDAO‑s center on business value derived from data and AI. This AI‑centred measurement can, however, overlook the broader responsibilities technology leaders hold and the overall measurable priorities of their organizations.
Organizational barriers to scaling AI
The research identifies three main constraints that can slow AI‑driven transformation:
- Structural fragmentation: growing numbers of technology leadership roles complicate decision‑making and collaboration. In 71% of surveyed organizations, at least five technology leaders sit on the executive team.
- Funding limits: technology investments in 2026 average 6% of company revenues and are expected to rise to 8% within two years. Nevertheless, 89% of respondents said they allocate at most one quarter of their technology budget to AI developments.
- Outdated operating models: while 81% of leaders believe their current operating model supports enterprise AI adoption, three‑quarters expect substantial model changes will be needed in the next 12–18 months to generate real business value.
These findings suggest that technology development alone is insufficient; governance structures and operating models must also evolve.
Strategic directions for adaptation
Deloitte highlights six strategic priorities technology leaders should pursue:
- Make AI’s business impact more predictable and integrate it into core operations.
- Make technology decisions through deliberate trade‑offs, based on clear business value and risk frameworks.
- Proactively manage regulatory, data‑handling and operational risks.
- Elevate AI to a corporate priority with active involvement from the CEO, finance, HR and strategy leaders.
- Embed AI into enterprise platforms, processes and operating models so it becomes part of daily operations.
- Tie all technology decisions to business performance and value creation, and center communications on business outcomes, risks and feasibility.
Conclusion
The next era of technology leadership will be defined less by familiarity with the most tools or platforms and more by the ability to combine technical expertise with business acumen. Leaders who can pair AI opportunities with disciplined operations, strategic thinking and measurable value creation will be best positioned to shape their companies’ futures. Deloitte’s study makes clear that ambition must be matched by changes in organizational structure, funding and governance to realize AI’s business potential.
