In the AI: Trust but Verify podcast, our host, Alec Crawford (@alec06830), Founder and CEO of Verapath (www.verapath.com), interviews guests about how they are using AI in business, where you can trust AI, and where you need to put up guard rails. Podcast production and sound engineering by Troutman Street Audio. You can find them on LinkedIn.

Tim Sears is the Chief AI Officer at HTEC, a deeply technical consulting and engineering company with roughly 3,000 people and about 2,500 engineers, working across sectors with clients that include hyperscalers, large tech companies, and a significant share of the Fortune 100 Tim’s career started on Wall Street in the bond markets, where he and Alec were part of the wave bringing technology into finance; they later lived through the dot-com boom at Morgan Stanley before reconnecting in the AI era Tim also worked at Target with data science and engineering teams on early AI-related work, and before HTEC he led software applications at Groq, where the team built AI accelerator technology for high-speed inference .

5 Key Takeaways

• AI will be bigger than the internet boom. Alec and Tim compare the current AI wave to the dot-com era around 2000, with Alec noting that AI could be the most dramatic technology shift of the next five years .
• AI strategy is not just turning on tools. Tim argues that giving everyone AI tools is not a real strategy; the bigger opportunity is using AI as a catalyst for teamwork, better processes, and faster execution with humans still playing a critical role .
• The hard part is organizational redesign. For CEOs, Tim says AI adoption should start with business goals like revenue growth or cost reduction, but leaders need to understand that AI will force a redesign of the organization, skills, workflows, and leadership approach .
• AI risk management needs “trust but verify.” The conversation emphasizes moving from low-risk internal uses to higher-risk external applications carefully, with more human oversight as risk increases — especially in sensitive areas like healthcare, customer service, and regulated industries .
• Ethics has to come from leadership, not just engineers. Tim’s view is that “AI ethics” is really just ethics: company values must show up in business decisions, and engineers can help build what leaders want, but they should not be solely responsible for deciding what ought to be built .

Links

• HTEC — Tim’s current company: https://htecgroup.com
• Groq — AI inference accelerator company Tim previously worked at: https://groq.com
• Morgan Stanley — where Alec and Tim worked during the dot-com era: https://www.morganstanley.com
• Goldman Sachs — where Alec and Tim first met: https://www.goldmansachs.com
• Target — where Tim worked with data science / engineering teams: https://www.target.com
• NVIDIA — discussed in the context of GPUs and AI compute constraints: https://www.nvidia.com
• Marcus Hutter — AI / AGI / superintelligence researcher mentioned in the episode: https://www.hutter1.net
• Reid Blackman — mentioned in the discussion of AI ethics: https://www.reidblackman.com
• Large Language Models / LLMs — central model architecture discussed: https://en.wikipedia.org/wiki/Large_language_model
• World Models — mentioned as a possible future AI architecture direction: https://en.wikipedia.org/wiki/World_model
• Quantum Computing — discussed as another major future technology wave: https://en.wikipedia.org/wiki/Quantum_computing
• Post-Quantum Cryptography — related to the “Q-Day” discussion about quantum computers breaking encryption: https://csrc.nist.gov/projects/post-quantum-cryptography
• Verapath — platform mentioned in the episode: https://www.verapath.com