What's AI's Real Failure? No One's Actually in Charge
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Key Takeaways
- HR must evolve from support role to strategic driver of measurable business outcomes.
- Companies that unify people, data and decisions will outperform slower, siloed competitors.
Generational threats have a way of forcing people inside companies to find different — and better — ways of working together.
We saw it during Covid, when HR, IT and finance teamed up to manage the transition from office life to remote teams. It wasn’t easy — but with no other choice, companies found new ways to collaborate and get work done, more efficiently than before.
In hindsight, that was almost a dress rehearsal for what’s happening now with AI.
AI is already rearranging the business landscape faster than anyone anticipated. Its ultimate impact will be much bigger than the internet, the shift to the cloud or the mobile revolution. As much as $100 trillion could be up for grabs.
But only for companies able to keep up. Those that can’t will get crushed by smarter, nimbler rivals using AI to gain an edge. And the difference may come down to a department that’s traditionally overlooked in the AI discussion: HR.
The AI leadership vacuum
Right now, at most businesses, no one is in charge of AI. Six out of 10 senior leaders say it has no clear owner.
The challenge is that AI’s implications extend across departments. It’s fundamentally changing how people do their jobs. But it’s also intimately wrapped up with IT and has profound implications on finance and planning functions.
And that’s precisely why HR finds itself in a pivotal moment. As the people side of the org, it’s a natural fit to drive AI transformation — but not alone. Truly harnessing AI will require HR to do something new and different. Specifically, building bold new bridges with departments not normally allied with HR: IT and finance.
It won’t be easy. Organizational silos don’t vanish on goodwill alone. If HR, IT and finance really want to meet the AI challenge, they need a strategy.
I work with thousands of companies transforming their workforce with AI. The ones succeeding are taking decisive steps to bring HR, IT and finance together and drive real change. Here’s how.
Step 1: Bridge cultural and organizational barriers
As a technologist, I believe in the power of tools. So it might be surprising to hear this from me, but the No. 1 barrier to successful AI adoption isn’t technological. It’s cultural. In fact, in a recent survey of executives, half cited organizational and cultural hurdles as a critical barrier to AI success, while only about 40% flagged technical limitations.
CHROs, CIOs and CFOs have traditionally each operated in their own fiefdom, with their own priorities and preferences. Building a productive working relationship in the AI era starts with breaking down these walls — and rallying around a clear North Star.
For most companies today, that North Star is survival. In the face of fierce competition, shifting geopolitics and tech uncertainty, only the strong — and aligned — will survive.
What does this kind of collaboration look like in practice? An extreme example is pharmaceuticals giant Moderna, which wedded HR and IT, putting its CHRO in charge as chief people and digital technology officer. The new boss has expertise in digital transformation as well as HR.
Labels aside, breaking down barriers also requires a mindset shift. HR must stop thinking of itself as just an administrative or support function — and ask how it can help drive business results.
For CHROs, that means finding new and better ways to connect talent with outcomes. Turnover figures alone are instructive but not actionable, for example. The real power lies in showing how churn impacts spending and revenue targets.
Connecting those dots, however, is easier said than done, which brings us to Step 2.
Step 2: Connect talent with outcomes
Right now, almost every company is collecting the data needed to make the right decisions about how and where to leverage AI. It’s all there — in HRM systems and CRMs and ERM platforms and dozens of other places.
But the problem is it’s not connected. HR data lives in its silo (or, more accurately, silos). Financial and performance data in another. Customer and sales data in yet another. So opportunities to truly connect talent with outcomes are missed.
Does paying more for our sales talent boost revenue? Can those support reps be replaced by bots without compromising customer retention? Does more manager training equate to higher performance? In most companies, the honest answer is, “Your guess is as good as mine.”
Even good-faith attempts to share insights across departments are undermined by data misalignment. Total Cost of Workforce, for instance, means one thing to HR and something very different to finance. For most companies, problem