Organizations racing to adopt artificial intelligence are discovering that their greatest obstacle isn't technology or budget, but rather their own people. Two major studies released this week reveal a stark divide between companies that are simply automating existing processes and those redesigning entire workflows around AI, with the latter seeing dramatically superior returns on their investments.

Why Are Most Companies Falling Behind on AI Readiness?

Despite accelerating AI adoption across enterprises, workforce readiness is declining. According to Kyndryl's second annual People Readiness Report, which surveyed 1,100 senior business and technology leaders across eight countries, only 23% of organizations believe their workforces are fully prepared for AI, down from 29% last year. This gap is widening even as companies invest heavily; worldwide spending on AI is forecast to reach $2.52 trillion in 2026, a 44% increase year-over-year, according to Gartner.

The disconnect is striking. While 57% of organizations say AI is now embedded in core business processes or deployed broadly across their enterprises, only 32% have achieved at least one of their top two AI goals, and just 11% have achieved both. This suggests that deployment and actual business value are two very different things.

The challenge intensifies as autonomous AI agents become more prevalent. Eighty-one percent of organizations expect AI agents to make impactful decisions within the next year, yet only 25% completely trust AI systems operating without human oversight. This trust gap reflects deeper concerns about governance, control, and organizational readiness.

What Separates High-Performing Organizations From the Rest?

Kyndryl's research identifies a small group of "Pacesetters," representing just 9% of organizations, that are achieving outsized results from their AI investments. These companies share three critical behaviors that distinguish them from peers struggling to realize value.

• Role Redesign: Pacesetters actively redesign roles around AI capabilities rather than simply automating existing job functions. Sixty-one percent of all organizations say they've already redesigned roles, while 24% are creating entirely new positions focused on AI management.
• Change Management: These organizations implement deliberate change management so the workforce understands the new operating model and has clear guardrails in place, building trust and reducing resistance to transformation.
• Workforce Readiness Investment: Pacesetters dedicate resources to upskilling and retraining, recognizing that people are the limiting factor in AI success, not technology or capital.

The payoff is substantial. Pacesetters are 1.5 times more likely to achieve AI-related revenue growth and 1.6 times more likely to report better innovation for products and services. They're also roughly twice as likely to have fully implemented every governance dimension measured, suggesting that strong governance and people readiness reinforce each other.

The Hackett Group's new AI World Class HR benchmarks provide concrete numbers on what process-led AI transformation can achieve. When organizations redesign entire end-to-end talent acquisition processes around AI, rather than automating individual recruiting tasks, the results compound across the entire workflow.

How to Build Organizational Capability Around AI

Organizations pursuing AI transformation can take several concrete steps to improve workforce readiness and governance:

• Implement Clear AI Decision Policies: Only 33% of organizations have clear policies on which decisions AI can and cannot make. Establishing these boundaries upfront reduces confusion and builds employee trust in AI systems.
• Deploy Monitoring and Registry Systems: Just 27% of organizations are using a registry and monitoring capabilities for all their AI systems. Implementing visibility into AI deployment helps organizations maintain control and identify governance gaps.
• Invest in Targeted Training Programs: A third of leaders have fully implemented training programs focused on helping employees collaborate effectively with AI tools. This targeted upskilling addresses the skills gap that 52% of leaders say has become more challenging to overcome.
• Redesign Workflows End-to-End: Rather than automating isolated tasks, reimagine how work flows across entire processes. The Hackett Group's research shows that talent acquisition costs per hire can decline by up to 61%, recruiter productivity can improve by up to 119%, and time-to-fill can decrease by up to 57% when the entire process is redesigned around AI.

The research also highlights a critical finding about trust. Organizations with stronger governance frameworks report that their workforces trust more in AI strategy and execution, and high-trust organizations are significantly more likely to report transformative outcomes from their AI investments.

"This is a critical moment for global enterprises as they race to adopt AI, redesign workflows and pursue innovation, yet they're finding that their greatest assets, their people, need more attention," said Kim Basile, CIO at Kyndryl. "The data shows that the organizations investing in people, whether it's rethinking roles and workflows, dedicating resources for upskilling and retraining, or guiding employees through change, are experiencing positive outcomes at a much higher rate."

Kim Basile, CIO at Kyndryl

The Hackett Group's benchmarks extend this insight to specific HR processes. When organizations redesign talent acquisition around AI, improvements in sourcing, screening, interview coordination, hiring, and onboarding reinforce one another. Better decisions upstream reduce effort downstream, creating compounding value throughout the process.

"Most organizations are still trying to justify AI investments one use case at a time," said Lee Derryberry, principal and HR Transformation practice leader at The Hackett Group. "Our research shows the greatest returns come when organizations redesign end-to-end processes enabled by AI, allowing improvements to compound across HR as a whole."

Lee Derryberry, Principal and HR Transformation Practice Leader at The Hackett Group

Beyond talent acquisition, the benefits extend across the entire hire-to-retire lifecycle. AI World Class organizations achieve internal fill rates that are up to 101% higher, provide up to 160% more training hours, and increase HR self-service by up to 187%, creating capacity for HR teams to focus on higher-value strategic and business partnering activities.

What Does This Mean for Enterprise AI Strategy Going Forward?

The research signals a fundamental shift in how organizations should approach AI transformation. The era of point solutions and isolated automation is giving way to a new phase defined by organizational capability, process redesign, and workforce readiness. Companies that recognize this transition early and invest accordingly will likely pull further ahead of competitors still chasing technology-first strategies.

Seventy-nine percent of organizations agree that the speed of AI will outpace their organizations' workforce, governance, and operating models. This gap represents both a risk and an opportunity. Organizations that close it through deliberate investment in people, governance, and process redesign are positioning themselves to capture outsized returns as AI becomes increasingly central to business operations.