The age of experimentation with generative AI (gen AI) is quickly giving way to a more intentional, transformative phase. McKinsey’s latest global survey of nearly 1,500 organizations paints a clear picture: companies aren’t just using AI—they’re rewiring themselves to fully capture its value.
While the journey is still in its early days, the report reveals which strategies are making a real difference. From CEO-level engagement to complete workflow redesigns, businesses are starting to lay the foundations for long-term competitive advantage.
Gen AI Adoption Is Up—But Value Requires More Than Just Use
In 2024, 78% of surveyed organizations reported using AI in at least one business function, up from 72% earlier that year. Gen AI use also rose significantly, with 71% regularly using it across functions like marketing, product development, service operations, and IT.
But adoption alone isn’t enough. According to McKinsey, only a minority of companies are seeing material enterprise-level impact on EBIT. The key to unlocking value lies not in scattered use cases, but in end-to-end transformation.
Workflow Redesign: The #1 Driver of Impact
Of all organizational changes linked to gen AI success, fundamental workflow redesign ranks highest. Companies that reimagine how work gets done—rather than simply layering AI on top—are seeing the strongest impact.
Yet, only 21% of organizations using gen AI have redesigned at least some workflows. The opportunity is clear: those willing to rethink their operations are poised to benefit most.
Leadership and Governance: The C-Suite Must Lead
The report finds that CEO oversight of AI governance is strongly correlated with higher bottom-line results. Still, just 28% of companies say their CEO oversees AI governance, and only 17% report board-level involvement.
AI governance is often shared across functions, but success depends on senior leadership engagement, clear direction, and a shift from tech-led implementation to executive-led transformation.
Risk Management Is Catching Up
AI-related risks are top of mind—and increasingly being addressed. Since early 2024, more organizations have taken steps to mitigate inaccuracy, cybersecurity threats, IP infringement, and privacy concerns. Larger companies, in particular, are more proactive in managing these risks, though challenges around explainability and fairness persist.
Still, 47% of organizations report having already experienced at least one negative consequence from gen AI. The message is clear: risk management must evolve in parallel with AI deployment.
Skills, Talent, and the Workforce Shift
AI is reshaping workforce dynamics. While hiring AI data scientists and machine learning engineers remains challenging, the overall difficulty has declined compared to previous years. New roles—such as AI compliance and ethics specialists—are also emerging.
Reskilling is gaining traction: many companies have retrained up to 10% of their workforce due to AI, and expectations for reskilling in the next three years are even higher. Interestingly, most companies are redeploying the time saved through AI into new tasks, rather than cutting jobs outright.
Adoption Best Practices: Still Underused, But Effective
McKinsey outlines 12 best practices that enhance AI scaling and adoption—from tracking KPIs to establishing a clear roadmap. But fewer than one-third of organizations have implemented most of them. Larger firms are ahead, especially in:
- Creating dedicated gen AI adoption teams
- Rolling out employee training
- Communicating AI successes internally
- Building trust frameworks for employees and customers
These practices correlate directly with EBIT impact. Yet most companies haven’t fully committed.
Revenue and Cost Effects: Emerging, But Not Yet Enterprise-Wide
Organizations using gen AI are increasingly reporting revenue gains and cost reductions at the business unit level—especially in service operations, product development, and sales. However, over 80% still don’t see a clear enterprise-wide impact on EBIT.
That’s likely to change. As gen AI becomes more deeply embedded and more companies follow the proven playbook, we can expect broader, more measurable gains.
Final Thought: Transformation, Not Just Technology
This year’s report reinforces a powerful message: AI value doesn’t come from the tools—it comes from transformation. Companies that treat AI as a strategic, top-down shift—not just a tech upgrade—are moving faster, managing risks better, and seeing early signs of competitive advantage.
In 2025 and beyond, the organizations that commit to rewiring their workflows, governance, and workforce will be the ones best positioned to thrive in the AI era.
