AI adoption is a culture challenge as much as a technical one: Gartner

AI adoption is an organisational issue as much as it is a technical one, Gartner senior director and analyst, Clement Christensen, has said.

“Culture is a thing that is going to leave you scratching your head long after the data science model,” Christensen told the Gartner CFO conference on Tuesday.

“Teams that are much more accepting of AI are, surprise, surprise, far more likely to reach higher maturity in their implementation of AI.”

Despite AI’s promises of enhancing efficiency, a survey by Gartner found that many businesses struggled to turn AI investments into material improvements in worker productivity. Of companies that had used AI, only 37 per cent reported high productivity gains.

Addressing cultural issues would be key to boosting AI adoption, Christensen said. Fear of experimentation and fatigue from events in recent memory, from geopolitical shifts to the pandemic, have stifled workers’ willingness to adapt to change.

Lack of familiarity with AI tools has also driven hesitance in the uptake of new technologies.

“We have this culture that is afraid, unfamiliar, fearful, and they're really, really tired, and that is not the kind of culture that is open minded and willing to embrace new ways of working,” Christensen said.

Workers were also worried about AI's effects on their job security. Firms that viewed AI tools as a means to boost worker productivity instead of a means to reduce headcount were poised to gain the most from AI adoption, Christensen said.

“In our own surveys, we found that about seven in 10 employees are pretty worried about what AI is going to do to their profession, to their career, to their role in an organisation,” he said.

“It is on us as leaders to help [workers] understand that we are not intentionally trying to drive them out with the adoption of an AI tool. We find that those organisations that do think that way tend to fail.

“[Businesses are] much more likely to succeed with AI if they think about it as a productivity improvement measure rather than as a head count reduction.”

Randeep Rathindran, vice president of research in the Gartner Finance practice, said: “The most successful teams approach AI with an openness to learn and explore new use cases, rather than fearing job displacement.”

“By redesigning structures and workflows to eliminate process bottlenecks and shifting time to value-added tasks, these teams maximise AI's potential and achieve meaningful productivity gains.”

To allow workers to feel more comfortable with adopting AI in their day-to-day processes, Christensen advised that finance leaders implement AI slowly into workflows, with a focus on automating time-consuming, mundane tasks.

“Always start small. Don't scare your team by bringing in the massive forecasting tool on day one,” he said.

“We're removing the kind of laborious, manual work that seems to drag a lot of teams down and tire them out and hopefully free up more time for the kind of intellectual, creative work that we want to move them to.”

Rather than imposing sweeping changes, leaders should collaborate with workers and identify areas of work that could be automated with AI.

“We're always looking for ways to say, Man, that is a frustrating part of my day. How do I use AI to get rid of that? That's the kind of attitude we’re ultimately building towards.”

“Lots of small changes, rather than a few big ones, are going to be your key to success.”