Enterprises are ‘paralyzed by a lack of understanding’ with AI adoption – and there's one key factor that decides success

It's not the tech that's the problem, it's your business case, says Forrester

Vector image showing male business leader in suit standing beside robot recording AI productivity metrics signified by an arrow pointing in an upward trajectory.
(Image credit: Getty Images)

AI isn't having the impact on businesses that many had hoped – and one analyst firm pins that on a "lack of understanding" of the technology, rather than a fault with AI itself.

That's according to a survey from Forrester that found those having success with AI are being more "deliberate" with the technology when it comes to creating value for their customers, rather than only focusing on productivity or efficiency.

"AI urgency is at an all-time high, but too many businesses are paralyzed by a lack of understanding and siloed adoption," said Sharyn Leaver, chief research officer at Forrester, in a statement. 

That advice follows research from MIT that suggested 95% of business AI projects were failing. Questions over return on investment (ROI) and whether AI is having a tangible impact for enterprises have been mounting over the last 18 months.

A separate survey from PwC in January, for example, found many executives are growing frustrated at the lack of returns, with just one-in-eight CEOs revealing AI has delivered both cost and revenue benefits.

Forget efficiency, focus on customers

In a blog post detailing the survey findings, Leaver noted that AI adoption continues to surge, but warned that a gap remains between AI's promise and results.

"Despite experimentation, few organizations have translated early AI innovation into meaningful business impact," she said.

"Productivity gains are incremental. Trust remains fragile. Customer experience, particularly in North America, is at an all-time low. For many executives, AI feels both urgent and elusive at the same time."

Forrester's survey found that those adopting AI most successfully tend to be customer-led, primarily focusing on creating value for users, improving user experience, or boosting marketing.

"These organizations resist the temptation to keep AI confined to internal use cases," she said.

Leaver added that CEOs can help drive this by using "customer value as your compass" when embarking on an AI adoption program.

Making AI work for them

Forrester found that companies with a high rate of AI adoption were most likely to name their CEO as driving their AI business strategy, at 25% of respondents. This is crucial, as business leaders have a “narrow opportunity to shift the narrative” during the early adoption phases.

"There are leaders and there are followers. Businesses that prioritize customer-led AI experiences will ultimately build trust and long-term value,” Leaver noted. The window to outpace competitors is open, and those who act decisively will be the best positioned to succeed."

The survey also found that skills development was vital, with those companies recording success with AI most likely to specify AI skill requirements in job descriptions, at 47% versus 33%.

These companies were also more likely to require applications to actually demonstrate those skills, at 54% versus 29%.

"They take a human-centric, trust-based, and transparent approach to talent upskilling — treating human potential as central to the strategy, not an add-on," Leaver added in the blog post.

Forrester also noted that realizing AI's value often requires work addressing data governance as well as infrastructure development.

"Successful firms made foundational investments early — in governance, infrastructure, and shared platforms — and are now seeing those investments pay off," Leaver said in the blog post.

"Importantly, readiness doesn’t require decades of work: many high adopters accelerate progress by working with partners to modernize data and platforms faster than they could alone."

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Freelance journalist Nicole Kobie first started writing for ITPro in 2007, with bylines in New Scientist, Wired, PC Pro and many more.

Nicole the author of a book about the history of technology, The Long History of the Future.