Gen AI: a trillion-dollar productivity story, with a twist

Generative AI could inject $1 trillion annually to the US economy by 2032, according to our recent research. But whether it reaches those heights—and at what cost—will be determined by businesses and the very human decisions of the leaders who run them.

Generative AI will have enormous implications for the future of work and productivity. But how massive an impact? And with what results for people and jobs?

In our recent research, the answers to these questions were staggering. We partnered with Oxford Economics to create an economic model that would quantify generative AI’s impact on the future of work. The model digs into the 1,000 jobs and 18,000 tasks that drive the US economy and examines the impact of generative AI on those occupations and the people who work in them.

While we focused on the US workforce, the themes that emerged from the findings can be applied globally. The model is also calibrated to reveal three scenarios reflecting low, middle and high levels of business adoption.

Here’s what we found:

• If the “high” scenario plays out, generative AI could inject an additional 3.5% of productivity growth to the US economy by 2032, for a cool $1 trillion per year. For comparison’s sake, that’s more than the entire US construction industry generated last year.
  
  
• While 13% of companies could be leveraging the technology in three to four years, one-third could be on-board in eight years, and nearly half may embrace it in a decade’s time, according to our most bullish scenario.
  
  
• By 2032, the vast majority of jobs (90%) could be disrupted in some way by generative AI, from administrative assistants to CXOs. Over half (52%) could be greatly impacted.
  
  
• Our exposure scores and friction scores show how much an occupation will be impacted by generative AI and how difficult it will be for a displaced worker to find new work. While some of the occupational groups with the highest exposure scores have relatively low friction scores, many others may face more significant and prolonged disruption from generative AI.
  
  
• In some job families, workers may face months of joblessness as they seek to transfer their existing skills to new roles. In total, more than 9% of the current US workforce may be displaced by generative AI. And based on analysis of previous economic shifts, it’s possible 11% of displaced employees—or almost 1% of the total workforce—may struggle to find work again.

Gen AI: a human story

Left unmanaged, this level of disruption would have severe consequences for not only organizations and the people who work in them but also for productivity itself. Because achieving the high end of our productivity forecast requires two things: high levels of business adoption of generative AI and low levels of disengaged or permanently displaced employees.

And here’s where businesses—and the humans who run them—come in. While the story of generative AI’s impact on work and productivity is technology oriented, it will ultimately be written by human hands. What it will take to reach the highest levels of business adoption and the lowest levels of displaced employees is the very human element of trust: trust between employer and employee, and trust in the technology itself.

Because for everyone who welcomes generative AI into the workplace, there’s an equal number who fear the downside of this technology: its potential to disrupt livelihoods, spread misinformation and reshape the very essence of what we’ve always understood to be human.

The time is now, as generative AI begins its ramp-up, for leaders to lay the foundation for a new trust compact, ensuring the technology is a positive force not just for economic productivity but also for workers and society.

A new trust compact

By embracing the following tenets, organizations can take crucial first steps to bolster confidence, build trust and open the door to a new age of productivity and prosperity:

1. Take care of your people. The fear of layoffs should neither be downplayed nor ignored. Addressing this concern with proactive and robust reskilling measures is crucial for fostering trust between employer and employee.
   
   
2. Innovate or stagnate. Employees’ trust will hinge on whether their employers “get it” and are preparing for the next wave of change.
   
   
3. Build confidence with transparency. Instilling trust in the technology will be key to business adoption—which, as our model reflects, is necessary for reaching the highest levels of productivity.
   
   
4. Put gains to good use. Employee-employer trust will only be forged when businesses give at least some consideration to how generative AI benefits will be distributed across society—without hampering innovation and investment.

Answering the many questions raised by generative AI will require time, experimentation and intellectual honesty. If those making the decisions, policies, systems and programs tackle this challenge with the best interests of humanity in mind, then the potential of generative AI won’t be a dry calculation but a living reality with benefits for all. 

For more, read our full report “New work, new world,” visit our Generative AI webpage or contact us.