Before I get into it, I want you to wear one of two hats while reading this:If you’re a builder, an individual contributor who ships things every day, think about how you can influence your leadership so the people, products, and company around you become more AI ready. From my time leading teams at Google DeepMind, Meta, and Google Labs, I can tell you that the ICs winning right now are the ones doing this really well. So my hope is you walk away with a clearer picture of how to become that 10x engineer or that IC who actually shapes their company’s strategy.If you sit at the strategy level, I want you thinking about how your organization is wrestling with the questions I’ll raise. These are the same questions I’ve grappled with at DeepMind and Google, and the same ones I’m helping companies work through now from the outside.How to prepare for physical AI: 5 steps for engineers and tech leadersJensen Huang called it “the ChatGPT moment for robotics.” Deloitte says 80% of businesses plan to use physical AI within two years. Here is what you actually need to know, and do, to prepare…AI Accelerator InstituteAndrew LovellThe three pillars of AI readinessI think about becoming AI ready as three big things working together.The first is the business itself. And I use “business” loosely here; it really means your product and your technology. Is the business AI ready or not?The second is the team: are the people in your organization actually AI ready?The third is the one most people miss. It’s whether you have a flywheel, a self-improving system that keeps getting better in both your team and your product.Let’s go through them.Pillar one: is your business AI ready?AI traffic has grown roughly 7 x 10³ over the past two or three years. That’s an enormous shift in how people are interacting with the internet.Take one slice of that growth. About 2 billion queries land in ChatGPT every day. That’s just ChatGPT, based on what’s publicly available. Roughly 150 million of those queries come from a user who wants to buy something.I should have hidden this stat and made you guess: how many of those queries actually result in a transaction?Less than 1%.Think about what’s happening here. I go to ChatGPT with a broken sink, upload a picture, and ask how to fix it. I work through the suggestions and it becomes pretty clear I’m not fixing this myself. The natural next step is to find a plumber. I’d usually go to Angie or Thumbtack. If I try to do that inside ChatGPT, I fail miserably.So we have these agents sitting on a goldmine of intent data, capable of powering some of the best service commerce out there, and we convert less than 1% of it into actual business outcomes.This pattern shows up across every product category. Across the 40 or so products I’ve worked with at Google and Meta, the same fundamental thing keeps getting missed.Solutions built before 2024 were designed for a human who would open a browser, create an account, and click through a flow. After 2024, your customer often isn’t a human anymore. It’s an agent acting on behalf of a human, and that agent breaks down the moment it has to log in, enter card details, or execute anything meaningful.If your product wants to be AI ready, it has to be agent ready.You’re going to be one of two companies in the next few years. You’re either the competitor making 30% more conversions and potentially 200x’ing your revenue, or you’re the one still optimizing for a buyer journey that’s quietly disappearing.Innodata GenAI Summit London: May 21, 2026On May 21st, the Innodata GenAI Summit convenes in London for a single day of rigorous, practitioner-led exchange on the challenges defining frontier AI in 2026. Here is what the agenda covers, who is in the room, and why it’s a must for AI professionals…AI Accelerator InstituteAndrew LovellA simple framework: discover, experience, transactWhen I work with companies on this, I break the AI-ready product question into three areas.💡Discover. Is your website, your product, even your LinkedIn profile, discoverable by agents? Job seekers have already started doing AEO (agent optimization) on their LinkedIn. The same logic applies to your product. In an agent-mediated world, discoverability has new rules.Experience. Once an agent or a user finds you, is the experience natively AI? Plenty of us still hit websites that ask us to fill out five rows of form fields. That’s a relic. The experience needs to feel conversational where it makes sense, dynamic where it should be, and powered by recommendations that adapt to context. Rethink the product experience from scratch.Transact. Once those two are working, think about the business layer. Dynamic pricing based on geography, dynamic UIs based on where users churn, AI-powered funnel analysis. Look at the entire funnel through an AI lens.
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Pillar two: is your team AI ready?None of the product work matters if your team can’t think in AI.💡Here’s where I think the industry narrative has it slightly wrong. Everyone’s focused on whether companies are adopting AI. About 88% of companies have people using ChatGPT or some equivalent every day. But only about 5% are seeing meaningful gains.