Many thanks to John Werner and his colleagues who put together an amazing event at the MIT Media Lab yesterday. Despite the fact that my brain is still a bit sore from absorbing all the rich panel discussions, I am optimistic about the evolution of the community surrounding this movement.
The format of 30-minute “speed” panels was impressive and the flexibility and authenticity of the panel made conversations fluid and accessible. Speakers ranged from the highly scientific and technical to those focused on the organizational and behavioral impact of AI on the workforce.
The informal gathering of sub-groups, such as the newly formed “Women in AI” made it collegial and convivial! It would be impossible to summarize each panel and likely all will be available on video. But here are a few of my takeaways from a cross-section of panels and panelists that I was fortunate to observe.
• With less than 10% of the workforce using AI, there’s still a lot of confusion about what it “is” and “isn’t” so education and skilling up is still critical.
• Many would say that the adoption of AI depends on the person next to you. Most people are more comfortable learning from their peers.
• There’s some debate about “shadow IT.” With so many solutions out there to solve problems, the biggest challenge is really understanding all the tools available to solve them and choosing the right ones. What’s out there in the stack? AI is truly about problem solving.
• Organizationally – AI needs community along with subject matter experts. It requires cr4oss-functional communication and expertise.
• There’s still much to be learned across modalities. Whereas “text” is well on its way – images, video, and voice – particularly speech recognition still has work to do.
• Selling AI into enterprises is still challenging (especially since much of the expertise is in smaller entities). Relationships matter in order to influence leaders to adopt. Entrepreneurs need to rely on strong boards with good track records with larger companies.
• Agents will start to diversify into many shapes and sizes and business models/pricing will evolve according to just how sophisticated a task the agent is accomplishing.
• There are many efforts to understand the “agent workforce” and what it means for the economy and the 163M jobs. Still many unanswered questions. Most people/companies are not ready for the potential impact.
• The idea behind decentralization of AI is to assure that all the economic power doesn’t end up in the hands of a few companies.
• Cybercrime is on the rise and the professionalization of such needs a strong response. AI has an important role to play. Companies large and small are being attacked “at machine speed” and need to learn to DEFEND at machine speed.
• Leaders need to provide “psychological safety” for their organizations to enable experimentation with AI. It’s about learning to act more like scientists who have the opportunity to fail without huge consequences. It’s critical to create a learning environment. It’s more akin to research and treating it like an investment in research.
The last panel that I attended with distinguished academic and industry leaders was asked for their advice on leadership imperatives. The advice is for leaders to help people “get curious” and share their learnings along the way. Understand that complexity and curiosity go hand-in-hand. Counteract any negative feelings by encouraging their people to find good in what they are doing with AI – and/or ways to use it to make a better world, or free up time to do good in other parts of life.