The University of Manchester is scrutinizing why growing adoption of AI tools has so far failed to translate into the forecast productivity gains, however, researchers are struggling to give easy answers to close the "AI ambition gap."
In a report, also called “The AI Ambition Gap,” the UK university’s Productivity Institute mulls over the advances that have been made in AI and the expanding adoption of it, and sets out what business leaders and policymakers can do to realize the potential benefits.
The report was commissioned by IT services biz Bytes Technology Group.
One reason for the lack of results is that organizations have invested heavily up front on retraining staff, reorganizing the way they work and other adjustments. Those costs show up straight away, yet the payback doesn’t come until later.
Another reason, the report suggests, is that AI tools can raise productivity at the level of individual tasks, but these gains do not automatically translate into greater productivity across a worker’s whole role or the entire organization.
It cites the example of software developers using GitHub Copilot who completed around 26 percent more tasks, and professionals using ChatGPT for routine writing and analysis that reduced task completion time by 40 percent while improving the quality of the output by 18 percent.
However, a study of AI dev tools found these have increased coding activity by approximately 240 percent, while the number of actual software releases has only grown by about 30 percent. The gap is due to humans still needing to check and test their work before release.
High task exposure to AI does not automatically make a worker more productive, the researchers say. Jobs typically combine automatable activities with tasks that require judgement, coordination, client interaction and critical thinking. As AI removes or accelerates some activities, those complementary human tasks become the constraint on time saving and the translation of task-level gains into greater productivity
Job outcomes therefore depend on task composition and complementary human expertise, the report continues. It suggests AI may in part displace labor from existing tasks, while also creating new tasks in which workers retain a comparative advantage.
This could be good news for the UK, the researchers state. Compared with five other nations (US, Brazil, Colombia, India and South Africa), Blighty has the highest share of workers in occupations with both high exposure to AI and "high complementarity," it claims. This is in part related to the country’s large financial and professional business service sectors, which are characterized by a high share of cognitive occupations.
This is just as well, as the government is pinning its hopes on using AI to drive economic recovery in a strategy outlined at the start of last year.
Britain's AI sector is relatively large by European standards, and the report cites recent OECD estimates that high-exposure economies such as the UK and the US could see annual labor productivity gains of between 0.4 and 1.3 percentage points.
Even an annual uplift of around 0.5 to 0.7 percentage points would represent a significant step change relative to the UK’s stalled productivity performance over the past decade, it says, if this effect is sustained.
The Productivity Institute lists several "mutually reinforcing enablers" to help organizations close the ambition gap it identifies. None is particularly surprising, especially if you have read other reports advising on corporate success with AI adoption.
One is management setting strategic direction for the organization, another is strengthening worker capabilities through greater knowledge and data literacy to help organizations turn individual insight into shared learning. Others include implementing AI governance and focusing on applications that can create new products, improve core processes or solve previously intractable problems.
"AI's productivity potential becomes real when faster tasks lead to better performance across the business," said Bart van Ark, professor at The Productivity Institute and lead author on the report.
"The ambition gap lies between those individual efficiencies and sustained business results. Closing it requires firms to invest in management, skills and the redesign of workflows alongside the technology."
The conclusion is that companies must have faith and keep investing in AI, and eventually the benefits will come if you are doing the right things. These include focusing on high-value use cases linked to strategy, customer value and operational bottlenecks, plus treating AI as a workplace redesign.
Policymakers could help out businesses here by assisting identifying relevant opportunities, the report says, to reduce adoption risks and uncertainty.
Other reports published this week were more defined in their message: Gartner said 75 percent of corporate board members have yet to see any productivity gains or reduce costs from AI use, and private equity biz Apollo Global Management reckons only the biggest tech vendors are enjoying some sort of AI payoff. ®