New global research from Kyndryl suggests that while AI adoption continues to accelerate, businesses are increasingly struggling to translate those investments into meaningful outcomes.
The company’s second annual People Readiness Report, based on a survey of 1,100 senior business and technology leaders across eight countries, found that workforce preparedness has declined over the past year even as AI becomes more deeply integrated into day-to-day business processes. The findings point to a widening disconnect between ambitious AI strategies and organizations’ ability to execute them successfully.
With Gartner forecasting worldwide AI spending will reach US$2.52 trillion in 2026, the research suggests organizations will need to invest as much in workforce readiness as they do in AI technology if they are to realize stronger business outcomes.
AI Deployment Grows, but Business Outcomes Remain Difficult to Achieve
The report shows AI adoption has accelerated significantly over the past year. More than half (57%) of organizations now say AI is embedded in core business processes or deployed broadly across the enterprise, up from 35% a year earlier, demonstrating that AI is moving beyond experimentation and becoming a core operational capability.
Despite that progress, relatively few organizations are realizing the business value they expected. Only 32% reported achieving at least one of their two primary AI objectives, while just 11% said they had successfully met both. According to the report, the difference lies less in the sophistication of AI technologies than in how effectively organizations redesign work, prepare employees for change and establish governance that builds confidence in AI systems.
The research also identified a small group of high-performing organizations, referred to as “pacesetters,” representing just 9% of respondents. Kyndryl found that pacesetters are 1.5 times more likely to report AI-driven revenue growth and 1.6 times more likely to see stronger innovation across products and services than their peers, suggesting organizational readiness plays a major role in determining whether AI investments deliver tangible returns.
People, Governance and Operating Models Emerge as the Defining Factors
Kyndryl argues that the discrepancy between adoption and readiness is not driven by a lack of investment in AI itself, but by insufficient preparation for the organizational change that accompanies it.
According to the report, pacesetters share several common characteristics that help drive stronger AI outcomes.
These organizations consistently redesign roles around AI, implement structured change management programs and invest heavily in workforce readiness, while also demonstrating significantly stronger AI governance across multiple areas.
Organizations are beginning to respond to the new dynamics AI has ushered in, with 61% reporting they have already restructured existing roles and nearly a quarter creating entirely new positions focused on AI management. At the same time, more than half say finding employees with the right AI-related skills has become increasingly difficult, highlighting the growing competition for talent.
Summarizing the findings, Katrin Marquardt, Associate Director, ABM and Field Marketing Manager at Kyndryl, said:
“There is a clear gap between AI ambition and AI execution. And I don’t think that’s a technology story. It’s a leadership story.”
She added: “Most companies don’t have an AI-use-case problem. They have a people, governance and operating model problem.”
The report also highlights governance as a critical enabler of AI adoption. Around one-third of organizations have implemented clear policies defining which decisions AI can and cannot make, while just over a quarter have established monitoring capabilities across all AI systems. According to Kyndryl, organizations with stronger governance frameworks also report greater workforce trust in AI strategy and are considerably more likely to achieve transformational outcomes from their AI investments.
Preparing for More Autonomous AI
The findings also point to an emerging governance challenge as businesses prepare for increasingly autonomous AI systems. While 81% of organizations expect AI agents to make impactful decisions within the next year, only one-quarter currently say they completely trust AI systems operating without human oversight, underlining the importance of establishing clear guardrails before autonomous AI becomes commonplace.
For many organizations, that means workforce transformation will need to become as much of a strategic priority as technology deployment. The research suggests businesses that invest in employee training, redesign work around AI capabilities and implement strong governance structures are significantly better positioned to generate long-term value from their AI initiatives.
Marquardt believes businesses that fail to evolve their people strategy alongside their AI strategy risk creating ambitious programs that never deliver meaningful business impact.
As enterprise AI investment continues to accelerate over the coming years, Kyndryl’s findings suggest competitive advantage will depend less on who deploys AI first or most extensively and more on who prepares their workforce, operating model and governance framework to support it.
