MOLLY WOOD: Today, I am joined by Karim Lakhani, a professor at Harvard Business School, who also chairs several university programs focused on technology management, innovation, and AI transformation, including the university’s new research center, the Digital Data Design Institute. In 2020, before many business leaders were even aware of generative AI or large language models, Lakhani co-authored a book titled Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World. Given the current revolution of AI in every aspect of work, we thought he would be an excellent person to discuss strategies and insights that can help leaders and organizations navigate the AI era. Now, let’s begin my conversation with Karim. Thank you for joining me.

KARIM LAKHANI: Thank you, Molly. It’s great to be here with you.

MOLLY WOOD: You have been writing about and teaching digital transformation and the potential of AI for years. I would love to know what the recent rise of generative AI looks like to you as someone who has been a close observer for so long.

KARIM LAKHANI: The moment of generative AI feels similar to the 1992-1993 browser moment. We had 30 years of the internet, and then Andreessen invented the browser, making the internet democratized and accessible. Similarly, generative AI is the moment when AI, previously the domain of experts in math and computer science, becomes accessible for use in specific tasks. We anticipated the democratization of this technology but did not anticipate the scale, speed, and scope of what generative AI has unleashed.

MOLLY WOOD: So, what changes now? As a Harvard Business School professor, what are you telling your students, particularly those in your new course, Data Science and AI for Leaders?

KARIM LAKHANI: In our new course, we’ve tried to make it AI-native. We use two bots: one that understands concepts from statistics and machine learning to data architectures and transformation challenges, and another service that removes the need for programming in R or Python to do machine learning or statistics. Our MBAs now have this superpower, and the big thesis is that generative AI is lowering the cost of expertise. The internet lowered the marginal cost of information transmission, and everything else followed. Similarly, AI is doing the same for expertise.

MOLLY WOOD: Right. You recently co-wrote a piece about this for the Harvard Business Review titled Strategy in an Era of Abundant Expertise. Can you elaborate on that?

KARIM LAKHANI: Yes, we worked with great colleagues from Microsoft on this. Companies are essentially bundles of expertise, and if the cost of expertise is dropping, that changes the core of what the firm is. At our institute, we’re obsessed with questions around this. One perspective is that generative AI is like a drug – we don’t know the dose, efficacy, right regimes, or side effects in the business world. The only way to figure out what it’s good for and what it’s not is through randomized controlled trials, being experimental and scientific about its effects.

MOLLY WOOD: Right. And how should leaders be thinking about introducing AI into their organization? Should it be through controlled trials or pilots?

KARIM LAKHANI: I see many leaders who are happy to talk about AI but aren’t using it themselves. That’s a problem because you can’t outsource understanding AI to someone else. Leaders need to use AI themselves to understand its power and then make decisions. At the company level, I tell organizations to first get activated, and that activation needs to happen at the highest levels, including the C-suite. My colleague, Iavor Bojinov, came up with an exercise where in 90 minutes, through structured prompts, you can create a snack food company. This exercise helps leaders understand the potential of AI.

MOLLY WOOD: Is there anything we haven’t discussed yet about AI, opportunities, and challenges that you think we’re overlooking?

KARIM LAKHANI: At the company level, my biggest worry is strategic shifts happening faster than imagined. Companies might do the equivalent of what Barnes and Noble did with e-commerce – they had a website but didn’t reimagine their business from top to bottom. At the leader level, there are three big gaps: a learning gap, an adoption gap, and a transformation gap. Leaders need to learn about AI, adopt it quickly and widely, and understand it’s a culture and work play, not just a technology play. For individuals, it’s about practicing and understanding AI, like learning to ride a bike – it takes time and practice to master.

MOLLY WOOD: Thank you so much, Karim Lakhani, a Harvard professor and chair of the school’s Digital Data Design Institute. It was an absolute treat having you on the show. Thanks for your time.

KARIM LAKHANI: It was a lot of fun, Molly.

MOLLY WOOD: Thank you all for joining us. We have more fascinating guests on the way with actionable insights to help leaders develop an AI-first mindset and maximize the ROI of AI. If you have a question or comment, please email us at worklab@microsoft.com. Check out Microsoft’s Work Trend Indexes and the WorkLab digital publication for all our episodes and stories exploring how business leaders are thriving in today’s new world of work at microsoft.com/worklab. Please rate, review, and follow us wherever you listen. The WorkLab podcast is a place for experts to share insights and opinions. As students of the future of work, Microsoft values diverse inputs, but the opinions and findings of our guests are their own and may not reflect Microsoft’s research or positions. WorkLab is produced by Microsoft with Godfrey Dadich Partners and Reasonable Volume. I’m your host, Molly Wood. Sharon Kallander and Matthew Duncan produced this podcast, and Jessica Voelker is the WorkLab editor.