Greater Risk, Greater Return

McKinsey's recent 2025 AI survey reveals widespread organizational adoption, with 88% using AI in at least one function (up from 78% in 2024), driven by generative AI. However, most remain in early stages: two-thirds are experimenting or piloting, with only 7% fully scaled enterprise-wide. 

Interest in AI agents is high: 62% are experimenting, but scaling is limited to 23% in select functions like IT and knowledge management. Positive impacts include use-case cost/revenue benefits and 64% reporting enhanced innovation, though only 39% see enterprise EBIT effects. High performers (6% of respondents) prioritize growth/ innovation alongside efficiency, redesign workflows, and achieve greater value. Almost one-in-three organizations (32%) anticipate decreasing their workforce in 2026, while less than half anticipated remaining at status quo, and only 13% anticipated increasing.

Additionally, survey findings indicate organizational size drives scaling disparity. Larger firms (> $5B revenue) are nearly twice as likely to scale AI (48% vs. 29% for <$100M firms), often hiring more AI talent (e.g., software/data engineers) and allocating >20% of digital budgets to AI, suggesting resource advantages accelerate progress while smaller organizations lag in integration. 

In the end it seems high performers face more risks but also manage them better. Organizations deriving significant value from AI (e.g., >5% EBIT impact) report higher rates of negative consequences like inaccuracy or IP issues, yet they mitigate twice as many risks on average, indicating that ambitious AI deployment increases exposure but pairs with proactive governance to sustain benefits.

It seems even in the AI era, an old adage holds true: the greatest returns go to those who thoughtfully embrace greater risk rather than avoiding it entirely.

Read the full survey findings from McKinsey: https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai#/