Product leader who builds businesses around technology. I align product strategy with broader company objectives to deliver outcomes—from revenue growth to customer retention. I focus on understanding customer needs, modernizing legacy systems, and developing strategies grounded in customer behavior and market awareness. I've launched agentic and non-agentic AI products from the ground up, transformed business models, scaled global product organizations, and turned sluggish teams into high-functioning execution engines. I’m ruthless at alignment and getting stakeholder buy-in. Inertia kills organizations and my top priority is to persist in moving forward until we achieve our business goals.
Annan Patel has been a guest on 1 episode.
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Your CEO Thinks AI is Working. Your Team Doesn’t. Here’s Why. | Annan Patel, VP Product (Tricentis)
October 20th, 2026 | Season 2 | 30 mins 2 secs
business, digital experience, product management, technology
Ask a CEO how their AI roll-out is going, and 81% will tell you that they're highly confident. Talk to the people doing the work, and that number drops to 56%.
Our guest today sits right in the middle of that gap. Annan Patel is VP of Product at Tricentis, a leader in enterprise software testing, where he builds AI products for companies where a bad release can cost tens of millions of dollars. He's spent over 15 years in product across ad tech, Microsoft, and WP Engine.
Tricentis recently surveyed more than 2,500 people across the tech industry. The headline: 83% of companies say they trust AI agents to make release decisions, while 60% admit they're shipping untested code. The unsurprising top reason why? Pressure from leadership to move faster.
Annan's take: AI gets sold as a tool you plug in. In practice, it's a new operating system for how work gets done.
In this episode, he shares:- Why "plug and play" AI only gets you about 60% of the way there, and why the rest is context your team has never written down
- Why their first AI products stalled after a strong start, and how they rebuilt them around one key concept: the AI is never the one held accountable
- And why tokens spent and lines of code shipped tell you nothing about whether your AI initiatives are actually adding value