Why AI isn't delivering as well as it should

Employers struggling to keep up with individual adoption, says expert

Why AI isn't delivering as well as it should

While artificial intelligence (AI) promises a boost in productivity for employers, it has yet to fully deliver, according to one expert.

And that’s because employers are struggling to implement an enterprise-wide adoption of the technology, says Tim Creasey, chief innovation officer of Prosci, in talking with HRD Canada.

"There is a fascinating variation in pace around how that impact is coming to life," he says, noting that individuals tend to embrace AI faster than teams, and teams faster than entire enterprises.

The opportunity for organizations, he believes, lies in aligning these different levels of AI engagement to maximize efficiency.

Six in 10 Canadian companies are prioritizing generative AI adoption, but full integration remains a challenge, found a previous study.

Why do companies have trouble implementing AI?

Currently, the ability to access generative AI tools on a personal level has created a gap between individual and enterprise-wide adoption, he says. For example, while 60% of employees in one company were already using AI to improve their productivity, the organization itself hadn’t yet defined a formal AI strategy.

Part of that is “individual access to a tool like an Integrated CRM or integrated ERP,” says the Prosci chief innovation officer. 

“Anybody that has access to the Internet now has access to large language models and the power of generative AI.”

The other half of it, however, is organizations are “working through challenges around strategic alignment, risk, security, data, privacy, investment strategy.” 

“And as they're working to get those things figured out, people can… bring in a large language model assistant that could help them write the email they're working on that afternoon.”

The big reason why organizations aren't realizing the value of AI, Creasey explains, “is they haven't figured out how to cross that chasm [and] catch up to the pace of individual adoption.”

Policies surrounding the use of AI appear to be falling behind the growing use of the emerging technology among HR professionals, according to a previous report.

How can businesses implement AI?

Creasey believes that to ensure that AI is more widely used among workers in the company, they should consider “cross-enterprise solutions as opposed to enterprise-wide solutions”.

Enterprise-wide AI deployment would mean every single person should be using AI.

“There's a lot of challenge and struggle in terms of driving sufficient adoption and usage and really achieving the benefits and values promised out of those enterprise-wide adoptions,” he says.

Meanwhile, cross-enterprise AI applications would mean that this would be implemented across teams. 

“There's huge productivity and power organizations are realizing from those cross-function, cross-enterprise solutions, as opposed to the enterprise-wide solutions.”

Creasey also notes that employers should not mandate employees to use AI in everything.

Instead, he proposes an “AI integration framework” that breaks down job tasks into three categories:

  • human-exclusive tasks
  • AI automation potential
  • AI collaboration opportunities.

Human-exclusive tasks – which rely heavily on emotional intelligence or human sensitivity – will always require a person’s touch. The tasks with AI automation potential are ones that could eventually be fully automated.

AI collaboration opportunities

Alexander sees the greatest value in tasks that fall under "AI collaboration opportunities," where AI enhances human output without replacing it. 

“The magic is in the middle,” he says.

Those are the tasks that are part of your job bundle “that you can do at higher quality and less time, with less mental strain and with higher levels of enjoyment when you integrate an AI into the way that you do those tasks”. 

“I don't think enterprises should dictate AI usage, but I do think successful enterprises will require everyone to think about their jobs and which part of their jobs are human-exclusive, which parts could be automated, but which parts are AI-collaboration opportunities.”

Employers are banking on artificial intelligence (AI) to provide a lot of positives, but very few have put in the groundwork to actually benefit from the technology, according to a previous Infosys report.