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.
