If you're the one who must decide how your company moves on AI, you already feel the pressure.
Leadership wants movement. Your people want clarity. Right now, almost nobody is delivering both at once.
There are many reasons for this, like the rapid adoption of AI technology coupled with the focus on AI outcomes before the organization's structure can support them, and these are presenting clear and present challenges to companies trying to navigate an AI journey.
Making investments in AI technology means organizations are spending real money and expecting returns. Licenses, tools, and pilot programs are rounding out tech stacks that already touch data management, enterprise software, and process automation.
The reality is that most of that spending isn't producing the return anyone expected.
WHY THE RETURNS AREN’T SHOWING UP
MIT found that 95 percent of enterprise generative AI pilots showed no measurable business return.
That might be surprising if you're a leader who has assumed by now that you'd be seeing massive returns on AI. After all, you're investing in technology to move faster and do it with cost savings in mind.
For a deeper lens, PwC's most recent Global CEO Survey, which polled 4,454 CEOs across 95 countries, found that 56 percent saw neither higher revenue nor lower costs from the AI they'd already rolled out. That's just over half.
The tools are working but the organizations using them aren't seeing the payoff. So what's going on here?
The reality is that there's a widening gap between what the technology can produce and the use cases leaders think AI will address. RAND's interviews with 65 experienced AI practitioners found the root cause: cited more than any technical issue, leadership misunderstanding the problem before the work even begins was the top driver of failure, at 84 percent.
This points to a leadership misalignment from the very beginning.
WHERE AI ADOPTION BREAKS DOWN
That gap shows up everywhere once you start looking for it.
- A failure to include guardrails in data governance structures
- A lack of transparency in the AI strategy, with no clear policies on AI use
- A difficulty in locking down metrics that prove AI tools worked and are generating a return
If this sounds familiar, then you've probably seen the public headlines by now.
A company clears the calendar for thousands of employees to spend a week exploring AI and finds out nobody knew where to start. A customer service AI gets rolled out, and the company quietly starts rehiring the human agents it replaced. A chatbot gives a customer bad information, and the company that deployed it gets held responsible in court.
These aren't edge cases anymore. They're becoming a pattern.
The public has had wide access to AI tools for nearly four years (OpenAI’s first public research preview of ChatGPT was November 2022, and Anthropic didn’t become available to the general public until Claude 2 launched in July 2023), and in that window, that pattern has shown that most of these failures break down into a few habits.
Companies rush to buy tools before they've defined the problem those tools should solve, and leaders assume their people are ready, then blame the workforce when adoption stalls.
Nobody owns governance, either, so it grows in the dark. About 56 percent of employees already use AI tools their company hasn't approved, while only 37 percent of organizations have any governance policy in place at all.
If leadership misunderstanding the problem is the leading cause of AI adoption failure, then bringing in an outside perspective to catch that blind spot can drive you towards success. Hiring an experienced AI adoption consultant is smart, precisely because it corrects for the blind spot RAND identified.
Yet notably, that public access timeline mentioned earlier is also how long the AI adoption consulting space has existed.
Hundreds of consultants have jumped into it, and not all of them are ready for what your organization needs.
Hiring the wrong one can be costly. You could lose budget, months of hard work, and, more importantly, your people's trust in the whole effort, which is much harder to win back than the money. The right consultant can help you look at your organization critically and unlock real value fast. The wrong one leaves you further behind than if you'd waited.
The reason the right consultant matters so much is that most of AI's value never comes from the technology itself. Around 70 percent of it comes from the people side of the equation, and companies that prepared their workforce before demanding AI adoption are the ones seeing real returns.
IKEA retrained thousands of call center agents into a new advisory role instead of replacing them, and that channel now earns over a billion euros a year. Amazon put more than a billion dollars into upskilling before pushing new tools on its workforce.
These aren't coincidences. Both companies treated AI adoption as a people problem before they treated it as a technology problem, and that's exactly the kind of problem a firm rooted in HR is built to solve.
You don't need a billion-dollar budget to apply the same principle. Putting people first and bringing in an outside perspective works at any size.
44%
of U.S. workers
44% of U.S. workers say their employer has no clear AI policy, or they aren't sure one exists.
SO, HOW DO YOU GET STARTED?
When you're choosing an AI adoption consultant, look for five things. They span your entire operation, from data governance to workforce readiness to the bottom line, and together they separate the ones who can deliver from the hundreds who've simply jumped into the space.
- Organizational transparency. They'll show you the real track record, wins and misses both.
- Data governance. Clear guardrails for what the AI can access and who's accountable for it.
- Operational structure. A plan to rebuild the process around the tool, not bolt AI onto something that was never designed to hold it.
- A human-first approach. Employees who trust and use what's being rolled out. This goes beyond tolerance with true adoption.
- AI metrics of adoption. An agreed definition of success before the work starts, checked long after the launch excitement wears off.
HOW WE CAN HELP
This isn't theoretical for us here at HR Soul. We know AI adoption can be complicated.
We firmly believe that a human-first approach to AI adoption is more about change management than anything else, and we can guide you through it. We have the experience, and based on it, we've put together a free white paper of 20 questions worth asking any consultant, including us.
Before you work with anyone, complete the form below and we will send you the free white paper.
Take a hard look at these questions. Bring the ones that matter most to your first real conversation with any consultant you're considering. If they can't answer them with real examples, keep looking. If they can, you may have found the right fit!
GET YOUR FREE WHITEPAPER TODAY