Why CTOs Are Losing Faith in AI—Despite Billions in Investment
Global, Tuesday, 23 June 2026.
For the third year in a row, CTO confidence in scaling AI has plummeted—dropping from 82% in 2024 to just 48% in 2026. The shift exposes a harsh reality: businesses are struggling to move beyond AI experimentation. Over 80% of companies report no measurable gains from AI, despite widespread adoption. The challenge has evolved from efficiency to integration, with leadership gaps, workforce distrust, and uncertain ROI emerging as critical barriers. Even as innovation overtakes cost-cutting as the primary driver of digital investment, the gap between AI ambition and execution is widening. Are we witnessing the end of AI hype—or the beginning of a more realistic era?
The Confidence Collapse: A Three-Year Decline
Chief Technology Officers’ (CTOs) confidence in scaling artificial intelligence (AI) has experienced a dramatic three-year decline, reaching its lowest point in 2026. According to Akkodis’ What CTOs Think 2026 report, confidence plummeted from 82% in 2024 to just 48% in 2026, reflecting a -41.463% drop [1]. This decline marks the third consecutive year of eroding confidence, despite record levels of investment in AI technologies [1]. The report, released on 23 June 2026, surveyed 500 CTOs as part of Adecco Group’s broader Business Leaders 2026 research, which included 2,000 C-suite executives globally [1]. The findings suggest that the initial enthusiasm for AI is giving way to a more sober assessment of the challenges involved in scaling the technology across complex enterprise environments.
From Efficiency to Integration: The Shifting AI Landscape
The focus of AI investment has undergone a significant shift, moving away from efficiency gains toward integration challenges. In 2026, innovation has overtaken cost-cutting as the primary driver of digital investment for the first time, according to the Akkodis report [1]. This shift reflects a growing recognition that AI’s potential cannot be fully realized without addressing systemic integration issues. CTOs now cite leadership gaps, workforce distrust, and uncertain returns on investment (ROI) as the most pressing barriers to scaling AI [1]. Specifically, only 44% of CTOs believe their leadership teams have sufficient understanding of AI, while just 46% report having established frameworks for responsible AI deployment [1]. Workforce trust remains another critical issue, with only 36% of CTOs expressing satisfaction with their employees’ confidence in AI systems [1].
The ROI Paradox: Billions Invested, Few Measurable Gains
Despite widespread adoption and significant financial investment, the majority of companies report no measurable gains from AI. Over 80% of organizations have yet to see tangible benefits from their AI initiatives over the past three years, according to insights shared by Jonas Prising, Chair and CEO of ManpowerGroup, during the World Economic Forum Annual Meeting of the New Champions on 23 June 2026 [2]. This paradox highlights a growing disconnect between AI ambition and execution. CTOs point to several key challenges, including a lack of in-house technology skills (32%), uncertainty around ROI (31%), and a lack of urgency at the business level (27%) [1]. The findings suggest that while AI adoption is accelerating, its impact remains uneven across industries, with many organizations struggling to translate technological advancements into scalable, real-world applications [2].
Agentic AI and the Future of Work
As businesses grapple with integration challenges, a new trend is emerging: agentic AI. Defined as systems capable of planning, decision-making, and task execution, agentic AI has been cited by 40% of CTOs as one of the most impactful trends for 2026 [1]. This shift toward more autonomous AI systems reflects a broader evolution in how organizations envision the future of work. According to the Akkodis report, 50% of CTOs report changes in the skills required for their workforce, while 49% note shifts in day-to-day activities [1]. However, the impact on employment remains limited, with only 21% of CTOs reporting workforce reductions due to AI [1]. These findings underscore a growing emphasis on augmentation rather than replacement, as businesses seek to leverage AI to enhance human capabilities rather than eliminate jobs.
Three Approaches to AI Scaling: Task Automators, Pilot Operators, and Enterprise Orchestrators
The Akkodis report identifies three distinct organizational approaches to AI scaling, each reflecting a different stage of maturity and strategic focus. Task Automators prioritize efficiency, using AI to automate repetitive tasks and optimize existing processes [1]. Pilot Operators take a more experimental approach, focusing on testing AI solutions in controlled environments before broader deployment [1]. Meanwhile, Enterprise Orchestrators represent the most advanced stage, emphasizing the integration of AI across complex systems and workflows to drive innovation and growth [1]. The report suggests that most organizations currently fall into the first two categories, with only a minority achieving the level of integration required to fully capitalize on AI’s potential. This classification highlights the gap between AI experimentation and large-scale implementation, as well as the need for more robust strategies to bridge the divide.
A Moment of Realism: Beyond the Hype
The decline in CTO confidence does not signal the end of AI adoption but rather a shift toward realism. As Jo Debecker, President and CEO of Akkodis, noted in the report, ‘What we’re seeing now is not a slowdown in AI adoption, but a moment of realism. Organizations are moving beyond experimentation and encountering the reality of scaling AI across complex environments’ [1]. This sentiment is echoed by industry leaders, who emphasize the need for a more strategic and measured approach to AI deployment. The upcoming AIBC World conference in Rome, scheduled for 2-5 November 2026, will bring together 30,000 delegates from over 150 countries to address these challenges, focusing on how businesses can turn broad AI deployment into scalable value [3]. The event underscores the growing recognition that AI’s long-term success will depend not only on technological advancements but also on effective integration, workforce readiness, and clear business strategies.
Industry-Specific Priorities: Aerospace, Life Sciences, and Energy
The Akkodis report reveals that AI priorities vary significantly across industries, reflecting the unique challenges and opportunities each sector faces. In aerospace, workforce development emerges as the top priority, as companies seek to upskill employees to work alongside AI systems [1]. Life sciences organizations, on the other hand, are focused on accelerating innovation, leveraging AI to streamline research and development processes [1]. In the energy sector, resilience takes center stage, with AI being used to enhance operational stability and mitigate risks [1]. These industry-specific approaches highlight the need for tailored AI strategies that address the distinct needs of different sectors. As AI continues to evolve, businesses will need to align their investments with their long-term goals, ensuring that the technology delivers measurable value rather than merely following trends.
The Road Ahead: From Experimentation to Execution
The decline in CTO confidence may serve as a critical inflection point for the AI industry, marking the transition from hype to execution. While the challenges of scaling AI are significant, they are not insurmountable. The shift toward innovation-driven investment suggests that businesses are beginning to view AI as a tool for growth rather than just a means of cost reduction [1]. However, the path forward will require addressing key barriers, including leadership gaps, workforce trust, and ROI uncertainty. As organizations move beyond pilot projects and toward large-scale deployment, the focus must shift from technological capabilities to integration strategies, workforce readiness, and measurable outcomes. The upcoming AIBC World conference in Rome will provide a platform for industry leaders to share insights and best practices, offering a glimpse into the future of AI-driven enterprise [3]. For now, the decline in confidence may be a necessary correction, paving the way for a more sustainable and impactful era of AI adoption.