Greg Shove, CEO at Section AI

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Greg Shove is the CEO of Section and a 6x founder and CEO of tech-powered companies that rode 3 previous tech waves (Internet, Cloud, Mobile) with $250M in exits. He’s also a founder at Machine & Partners, an AI consultancy helping companies identify and prototype AI products, and Personal Math, a newsletter for professionals in their 30s and beyond.

The Discussion

Q: In terms of AI-driven transformation, what does success look like for your organization over the next 5 years?

A: Education is primarily a content business. Generative AI has already had a dramatic impact on what we do and that will only accelerate. At a minimum, the Section employees of the future will have to meet expert level AI proficiency (as defined by our own proprietary AI Proficiency Diagnostic) and they'll need to be able to integrate AI into every single one of their workflows. When working at the intersection of tech and content, this is not only easy to accomplish, it's essential.

At Section, use an operating framework called O.A.T to guide all the work we do - Optimize, Accelerate, Transform. We believe that every organization should use AI to optimize internally - that's been easy for us because Section is a blend of tech and content (aka what AI does really well). A third of companies also need to think about accelerating their products - and we are with tools like our AI coach, ProfAI. Not many will have to transform their business, but we'd be delusional to think that AI won't fundamentally transform the future of learning experiences. We're not afraid of this - not only will AI make our courses better, it will provide a more personalized, relevant, and accessible learning experience. We're already preparing for that.

Q: What are the key AI-related trends or technologies you're watching closely, and how do you plan to incorporate them into your business model?

A: The price of tokens has dropped 90% and we hope that it keeps dropping. As long as investors want to subsidize OpenAI and Microsoft to lower the price of inference, we all get to ride (and build) on that wave and provide more AI to our customers at an increasingly affordable price.

The elimination of prompting has already started. It's not natural for us to interact with machines in this way and big tech knows that. They've begun to hide prompting behind one-click buttons and voice commands to remove user friction with their AI tools. The masking of prompts will only get more common - and alludes to a future full of AI agents.

AI's memory feature has great promise but it doesn't work well yet. ChatGPT might store things but it can't call them up in a super relevant way when you need them. But this feature will become key as we come to rely on AI as a thought partner more and more. The value of being to roleplay strategic scenarios with an LLM that remembers all the context and can provide nuanced advice is significant.

Q: How do you see AI reshaping leadership roles and decision-making processes over the next few years?

A: Leaders will be expected to manage people and AI. AI shouldn't care the same weight as the people on their team, but it does need strategic oversight. I would expect a future leader - whether it's the head of marketing or sales - to be able to speak to me about their people management strategies (like training and promoting) as well as how they're managing AI for their team (what are the policies, how is it integrated? etc.) There's a philosophical element to this - what is AI's place on the team? - and there's a practical element - how do you operationalize it for your team?

Today's leaders are already expected to be data-driven - AI will only make that more important and more powerful. Marketing, for example, used to be about intuition and gut checks - you just knew a good ad when you saw one. But it's become increasingly more focused on performance and those leaders have had to adapt. Now that parsing data to make decisions is already a given in today's leaders, the next question is: How do you collaborate with your AI to do this better?

The talent pipeline, and how people are trained and promoted, will be one of the largest organizational challenges AI will bring about. Entry level knowledge work is boring and repetitive, but it's designed to be that way - it's how you learn how the industry works. You need to have institutional knowledge to build off of and grunt work is how you give people a foundation for functional roles - they're a training mechanism. If AI is able to take over a significant amount of that low-hanging grunt work, how do you onboard new people? How will you see who shines? And what are the implications of that - will we completely lose the talent pipeline? It might be a good thing - maybe lawyers waste 1 year of their career instead of 3 filling out paperwork. But what are the unseen implications? This unanswered question is why so many people are sitting on their hands with AI - it rebuilds the ladder of their entire industry.

Q: How do you separate truly groundbreaking AI technologies from those merely following the hype?

A: For user-facing AI, the groundbreaking stuff is a mixture of magic + a business model. You want the experience to feel like a card trick to the user, but you need a business model that attracts investors to make it enduring vs. novel. There's a lot of cool AI stuff out there that won't last because no one is going to pay for it. I'd argue that groundbreaking tech is actually less interesting than groundbreaking business models because we're overwhelmed with new product releases. There's no shortage of cool AI tools. But how many of them have a business model that checks out?

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