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4 ways to usher in ‘smooth scaling’ of generative AI


When it comes to embracing generative AI, healthcare is something of a straggler. Some 89% of organizations in pharma/healthcare have neither deployed nor experimented with the technology.

So reports a team of researchers at MIT Technology Review Insights. The authors came by the finding after conducting a global poll of 1,000 executives in multiple industries. They also interviewed experts in academics, data science and AI.

But generative AI participation is just an aside to the investigators’ primary interest. What they’re really after is what it takes to scale the technology from a toe in the water by one or two brave departments to a full-on swim by a broad swath of the enterprise.  

Sooner or later, healthcare and fellow slowpokes—most notably government, transport/logistics, energy/utilities and travel/hospitality—will take that plunge. In the meantime, here’s what they can do now to ensure, in the MIT authors’ words, “smooth scaling.”

1. Know that partnerships with both AI startups and Big Tech will be critical to smooth scaling.

“Most executives (75%) plan to work with partners to bring generative AI to their organization at scale. While Big Tech has an ecosystem advantage, startups enjoy advantages in several specialized niches. Executives are somewhat more likely to plan to team up with small AI-focused companies (43%) than large tech firms (32%).”

2. Pace for success.

“Firms should move steadily and cautiously to enterprise-wide AI deployment, especially in light of evolving regulatory and legal regimes. History shows that new technology adoption is often slowest at the start but can accelerate exponentially thereafter.”

3. Avoid overpredicting workforce reductions.

“Today’s decisions could spread worker productivity and value. And dystopian unemployment forecasts may overestimate the power of automation and undervalue the know-how of employees. Executives should look to the potential of technology to enhance customer and employee experience, not merely to cut costs.”

4. Allow time for new laws and oversight bodies to take shape.

“New legislation and institutions are warranted to manage AI risk, but these will take time to establish. In what may be AI’s ‘Napster moment,’ the current period could give rise to new business models and consumer norms.”

MIT produced the report with backing from several tech companies. Read the whole thing for free here.

 

Leah Sirama
Leah Sirama
Leah Sirama, a lifelong enthusiast of Artificial Intelligence, has been exploring technology and the digital realm since childhood. Known for his creative thinking, he's dedicated to improving AI experiences for all, making him a respected figure in the field. His passion, curiosity, and creativity drive advancements in the AI world.
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