HR: The Hidden Accelerator Of AI Adoption
Scaling AI starts with people. Yet only half of companies involve HR in their strategy.
Employee experimentation with generative AI is moving almost as fast as the evolution of the technology itself. But organizations? They're trailing behind. Most are stuck in pilot mode, hesitant to move beyond isolated tests. In Bain & Company's global survey of nearly 800 IT executives, 97% said they're testing generative AI, but fewer than 40% have scaled its use.
Legacy technology systems, cultural inertia, and regulatory friction are real hurdles. Even as models like DeepSeek's R1 continue to push down costs and reshape strategies, widespread enterprise adoption is slow.
The reason is simple: Generative AI isn't just a tech upgrade. It's a workforce transformation.
Winning organizations aren't just updating their tech infrastructure. They're preparing their people with training and clear guidelines. According to the World Economic Forum's Future of Jobs Report 2025, 77% of employers plan to reskill and upskill their talent to work alongside AI by 2030. In addition, 69% plan to hire new employees who are skilled in AI tool design.
Yet only half of companies are currently involving HR in their AI strategy. That's a critical miss. When HR is engaged, companies move faster: 62% of high-adoption organizations are investing in employee training. They are scaling the benefits of the technology and quickly pulling ahead. Luckily, it's not too late to catch up.
According to Bain's survey, 77% of companies have seen meaningful time savings in day-to-day tasks through AI-powered processes, with 30% saving more than a fifth of their time in the first year alone. And 69% saw improved collaboration with generative AI. Just 10% said the technology replaced entire roles.
One thing is clear: AI is about unleashing the power of people. That puts HR front and center. Forward-thinking organizations are involving HR in three ways:
Working with HR, the most successful AI adopters are crafting a two-speed strategy that balances ambitious transformation with quick, practical wins.
Big bets are large, strategic investments, such as fully automated supply chains or AI-powered customer service. Intuit, for example, has reduced contact with TurboTax product support by 20% through AI self-help and increased coders' productivity by up to 40% through AI assistance. Efforts that revolutionize how people work require cross-functional alignment, strong leadership commitment, and an emphasis on return on investment.
Small wins, on the other hand, are often grassroots initiatives. Not waiting for top-down mandates, employees use AI to automate daily tasks, generate content, and make informed decisions. These efficiency gains build internal momentum and cultural buy-in. In September, Intuit shared that its generative AI trials boosted productivity by 15% on average, with certain tasks, such as marketing content creation, reporting even higher gains.
Even companies that are all-in on AI integration will face challenges such as modernizing their platforms and balancing innovation with regulatory compliance. Cost of implementation is an issue, too. From upskilling employees to acquiring cutting-edge tools, leaders worry about spending money when return on investment remains unclear.
To overcome these barriers, leaders will take three steps:
Companies that hesitate now risk being left behind—not just by their competitors, but by their own employees. Scaling AI requires learning as an entire organization, through a balance of bold investments and daily improvements. And by elevating HR to a leading role, organizations establish the foundation required to evolve and win.
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