The Numbers Don’t Lie — And They Should Make You Uncomfortable
Two major research reports dropped this month that every L&D leader and CTO should read back to back. The picture they paint together is not a comfortable one. Kyndryl’s second annual People Readiness Report surveyed 1,100 senior business and technology leaders across eight countries. Its headline finding: 57% of enterprises now have AI embedded in core business processes or deployed broadly across their organizations — up from 35% just one year ago. By any measure, that’s a massive surge in deployment. Here’s the problem. Only 32% of those same organizations have achieved at least one of their top two AI objectives. A mere 11% have hit both. Let that sit for a moment. The majority of enterprises are deploying AI at scale. The overwhelming majority are not getting what they set out to get from it.
Workforce Readiness Is Actually Going Backward
The same Kyndryl study found something that should be alarming to anyone responsible for AI adoption: workforce preparedness has declined over the past year. Only 23% of business leaders now believe their workforce is fully prepared for AI — down six percentage points from 2025. Nearly four in five respondents agreed that the pace of AI development will outstrip their organization’s workforce, governance, and operating models. At the employee level it gets worse. The Achievers Workforce Institute’s seventh annual State of Recognition Report found that just 19% of workers feel confident using AI tools, and only 18% feel supported in adapting to them. That means more than 80% of the workforce in a typical enterprise has neither the confidence nor the clarity to integrate AI into daily work — even as leadership pushes for broader deployment. The gap between what organizations are spending on AI infrastructure and what they’re investing in the people who are supposed to use it has never been wider.
The 9% Who Are Actually Getting Results
Kyndryl’s report identifies a cohort it calls Pacesetters — roughly 9% of respondents — who are achieving measurable AI outcomes. These organizations don’t just deploy AI. They redesign roles around it. They implement structured change management. They invest deliberately in workforce readiness before, during, and after deployment. The performance differential is concrete. Pacesetters are 1.5 times more likely to achieve AI-related revenue growth and 1.6 times more likely to report improved innovation in products and services. The difference is not the tools. The difference is the people and how deliberately they were prepared to use them.
What This Means for Your Organization
If you’re in the 57% that have deployed AI broadly — and statistically you probably are — the question isn’t whether to keep investing in AI. You’ve already made that bet. The question is whether the people responsible for using it have been prepared with the same seriousness as the infrastructure was built. A new model is available to fix this. bILTup and O’Reilly have partnered to deliver cohort-based AI programs that combine O’Reilly’s curated, role-specific content library with bILTup’s hands-on, practitioner-led instruction and embedded office hours. It’s not self-paced learning alone. It’s not a standalone workshop. It’s a structured program that closes the gap between deployment and readiness — built around your team’s actual tools, roles, and outcomes. The organizations closing the gap aren’t waiting for their people to figure it out. They’re building programs that make the outcome inevitable.
Talk to us about building your AI readiness program → Learn about the bILTup + O’Reilly Academy Program →