In the CHRO Association’s 2026 survey (mind it’s the US), 91% of HR leaders ranked AI and workplace digitization as a top-five immediate concern, far ahead of governance, engagement, or talent.
Now let’s look at the real adoption:
Nearly 88% of organizations now regularly use AI in at least one business function, and 80%+ have already piloted tools like ChatGPT or Copilot. On paper, almost everyone is “doing AI.” At the same time only about one-third (33%) have actually scaled AI across the enterprise. In HR specifically, the drop-off is starker — just 14% of organizations actually use the AI capabilities built into their core HR system, while 29% have those capabilities but leave them switched off entirely. Only 39% report any enterprise-level financial (EBIT) impact from AI — and just 6% see a material impact of 5% or more. A Gartner survey of HR leaders was even blunter: 88% said they had realized no significant business value from AI tools, despite widespread attempts to deploy them.
The most cited evidence here is MIT’s GenAI Divide: State of AI in Business 2025 (Project NANDA): despite an estimated $30–40 billion in enterprise spending, roughly 95% of generative-AI pilots delivered no measurable impact on the bottom line. Only about 5% crossed from pilot into real, value-generating production.
Crucially, MIT found the problem isn’t the technology — it’s the learning gap: tools and organizations that never adapt the AI to real workflows. Generic tools shine for individuals but stall in the enterprise because they don’t learn a team’s context. Seems it’s time to stop spending a lot and start choosing the tools serving teams and reducing bottlenecks.
What it means for HR in practice:
- Think of those that can be automated (typically operations / data gathering and analysis / matching data)
- Imagine what is possible when your pinpoint are solved
- Find a reliable partner, who is a subject expert and knows what to do or how to address your issues the best way
Or Talk to us -> we can navigate you!