Defining A Human-Centric Approach To Generative AI Adoption

Companies should listen to employees, lean in with empathy, and provide plenty of training to unlock the technology’s benefits

Mercer's Ravin Jesuthasan, Microsoft's Deb Cupp, and Huma Therapeutics' Dan Vahdat exchange views in our Davos panel discussion on tapping AI's power in the workplace.

Mercer's Ravin Jesuthasan, Microsoft's Deb Cupp, and Huma Therapeutics' Dan Vahdat exchange views in our Davos panel discussion on tapping AI's power in the workplace.

The transformative potential of generative artificial intelligence (AI) was the talk of this year’s annual meeting of the World Economic Forum, held in Davos, Switzerland, from January 15 to 19. Will this powerful technology “usher in a golden age of productivity or destroy millions of livelihoods across the global economy,” in the provocative words of the Oliver Wyman Forum’s new report, “How Generative AI Is Transforming Business And Society.”

To dig into that question and explore how business can maximize the benefits of generative AI and minimize the risks, the Oliver Wyman Forum and Mercer brought together business and technology leaders in Davos on Jan. 16. They included Deb Cupp, president of Microsoft Americas; Tanuj Kapilashrami, chief human resources officer at Standard Chartered Bank; Azeem Azhar, entrepreneur, bestselling author, and CEO of technology newsletter Exponential View; Dan Vahdat, founder and CEO of health-tech software firm Huma Therapeutics; Ana Kreacic, chief knowledge officer of Oliver Wyman and chief operating officer of the Oliver Wyman Forum; and Ravin Jesuthasan, global transformation leader at Mercer and bestselling author on the future of work. Martine Ferland, CEO of Mercer and Vice Chair of Marsh McLennan, and Oliver Wyman Forum CEO John Romeo provided introductory remarks.

While speakers had different views on the scale and pace of generative AI’s disruption, they agreed companies can best unlock its potential by taking a human-centric approach, and giving employees the training and information they need to thrive alongside the technology. Here are some of our key takeaways:

  • Mass adoption doesn’t automatically translate into mass productivity gains. Generative AI tools were being used weekly by over 50% of employees just a year after ChatGPT was released, compared with the 17 years it took for the internet to reach mass adoption. The ability to use natural language to question generative AI models enables people with no coding skills to use these powerful tools, which explains why people have embraced them so quickly. That democratization of access is “a gift” that corporate leaders should take advantage of, said Vahdat. So far, though, most organizations are still experimenting with the technology and trying to figure out what use cases best suit their operation. Business needs to accelerate that process if we don’t want to see AI become the butt of the early joke about the internet – that its impact can be seen everywhere but in productivity statistics. "The way you're going to get the commercial value is through adoption," said Romeo. "And the only way you do that is if you focus on the people – the culture, the leadership, the capacity to change."
  • Organizations should adopt a human-centric approach. Generative AI is expected to affect four out of every five existing jobs, but displacing jobs doesn’t necessarily mean eliminating them. AI can augment workers’ capabilities by taking on a lot of today’s rote, transactional tasks and enabling employees to focus more on relational, creative, and expertise-related functions. This demands that leaders stop thinking of their organizations as a collection of jobs and pivot to an emphasis on skills. By focusing on the intersection of technological and human talent, in the words of Kapilashrami, “as machines get better at being machines, humans can get better at being humans.”
  • The challenge is as much cultural as technological. That starts with a growth mindset, said Cupp. Companies need to be open to thinking differently and taking decisions amid uncertainty. At the same time, they should communicate expectations clearly to employees and give them the education and training they need, something a majority of respondents in the Oliver Wyman Forum survey say is currently lacking. Executives also need to listen to employees, recognizing that the people on the ground are generating some of the best use cases. And with three in five white-collar employees saying they fear generative AI will eventually make their roles redundant, employers should lean in with compassion – to balance economics and empathy, as Jesuthasan put it – as they push adoption. “The disconnect between what executives think is enough versus workers is huge and companies just need to do a lot more,” said Kreacic.
  • While AI is generating some impressive efficiency gains, the big prize is AI’s potential to drive transformational change. It’s a challenge because the technology is very young and we don’t yet know its full capabilities and weaknesses. But that’s all the more reason for companies to actively explore the frontiers of generative AI’s utility, said Azhar. That entails thinking like a startup, imagining how you might serve customers if you were starting with generative AI, and looking to draw lessons from firms that succeeded in previous rounds of digital disruption. Vahdat said generative AI can slash the time it takes a clinical nurse to monitor a patient and write summary notes by 90% –  a 10X improvement in productivity. And that’s before taking account of the technology’s potential to improve the quality and consistency of care.
  • Manage risks but don’t let the unknowable future stall progress today. We don’t have all the answers to AI adoption, and perhaps not even all the questions. Kreacic noted the perennial question of equity that comes with every technological advance – who will see the gains, employers or employees? History favors the former. Will generative AI be widespread in the workplace in two years or 20? (Azhar noted that it took computers only eight years for a computer to beat a computer-assisted human at chess.) And will the relationship between humans and the technology be transformed in the process? Rather than dreading the possibility that machines may overtake humans in intelligence, such a future “might free up lots of time for us to do the things that we really love,” such as travel or taking up a sport, said Vahdat.

Generative AI promises to have a profound effect on our lives in the years ahead, and we look forward to working with the public and private sectors and civil society to help shape that future.