The Next AI Gold Rush (2025 Opportunities)

Full video transcript

Darby connects with Chris Dagel, CEO of Chief AI Officer, a company helping organizations integrate AI. Chris, based on a ranch in Paige, Texas near Sherwood Forest, joins to discuss the role of the chief AI officer and share perspective on where AI opportunities are heading, drawing on the research his team does and pays attention to across the industry.

Chris explains how he got into this work: he had spent years doing high-level growth architecture consulting for companies, using frameworks like EOS or Scaling Up to help them set big, ambitious three-to-five-year goals. When GPT-3.5 launched in November 2022, he assumed AI would be someone else’s opportunity since he wasn’t technical. His “aha moment” came in March 2023, when he realized that pairing business process knowledge with these tools was the real unlock — knowing how different departments interact makes it easy to see where a tool fits, while knowing only the tools without business context limits real transformational impact.

He then heard Peter Diamandis — co-founder of Singularity University, whose predictions on emerging technology have reportedly been accurate 86% of the time over 30 years — describe the concept of a “chief AI officer” in an interview: not a data scientist or someone fine-tuning an LLM, but someone who understands the business and can scan the landscape of generative AI tools to bring value back to the company. Chris registered the domain immediately and built out a curriculum and faculty, attracting career professionals who see disruption coming and want to get ahead of it rather than build simple bots.

Chris says his team thought they were late starting development in early 2023, but they weren’t — 2023 and 2024 were still early. Momentum picked up through the end of Q3 into Q4, and he expects 2025 to be the year of hyper-adoption for businesses that have stayed on the sidelines.

He frames everyone learning generative AI right now as holding a lottery ticket — some will cash out big, some won’t. Thought leaders who choose to consult and charge for their AI knowledge will make good money over the next year or two because demand outpaces supply, but the market is inefficient: companies looking for a true chief AI officer type don’t go to Upwork, they go to a narrow pool of people who can affect a whole business, not just operate one tool. Those consultants will eventually hit capacity and have to turn away demand, missing the larger wealth transition — evidenced by generative AI businesses of all kinds (not just tech) attracting investment at unusually high multiples of topline revenue.

Chris’s advice: look for bigger opportunities than a side hustle or personal productivity gain. Ask whether something you’re doing cleverly with generative AI in your own business — a process, prompt stack, tool, or agent — could benefit other companies doing the same activity, since most businesses share common functions like HR and payroll. He compares the scale of opportunity to being early on the internet, citing Jeff Bezos and Elon Musk (with PayPal) as examples, while noting he’s not claiming anyone will be “the next” them.

He introduces the idea of “thinking in AI”: you don’t need the answer up front, just a hunch that an opportunity exists, then work with the models to flesh out ten possible opportunities in a given domain. He offers practical advice for people who feel behind or intimidated by the technical reputation of AI: plug into a community so you don’t have to track everything alone, and recognize that understanding your business — knowing what questions to ask and what best practices and constraints look like — is the hard part, and most people already have it. He also suggests that business owners look inside their own team for an enthusiastic learner to send to get trained, rather than hiring an expensive outside “chief AI officer” who still has to learn the business from scratch.

Darby connects this to why Gen AI University started — building a community (hosted on Circle) where members can lean on each other, share insights from mastermind calls, and avoid feeling isolated or fearful about AI. Chris adds that once people start using tools like Gamma, the research shows they shouldn’t just take the time saved and coast — they should reinvest it into learning the next tool or identifying the next process to improve, similar to how bandwidth opens up after training a new virtual assistant. He warns of diminishing returns if that reinvestment stops.

Chris also recommends documenting the work: shoot simple videos, even without expensive equipment, and distribute them on social platforms. He describes using Descript to edit his own footage — adding music, transitions, and a “studio sound” AI feature that can make phone audio sound professionally recorded — all learned through experimentation rather than formal training. He argues showing this work publicly builds recognition with peers, clients, and employers, since most people in a person’s network are facing the same AI questions.

Darby mentions using Descript himself to process the day’s eight hours of live-streamed summit content, since traditional editing would take weeks and cost significant money. Both note that many people are unaware of new AI capabilities — like ChatGPT’s search function becoming available to everyone just days before this conversation — because they tried a tool once, found it lacking, and never returned. Darby shares building an entire presentation in Gamma from a prompt during an Uber ride to a music festival as an example of “productive play” with these tools.

Chris closes by encouraging viewers to start actively looking for opportunities now that they’ve been prompted to pay attention, to bring ideas to their community for collaboration and accountability rather than pursuing them alone (since collaborative accountability outperforms working solo), and to ask what free generative AI tools exist to help build out whatever idea surfaces. He reassures the audience that even if they feel behind hearing this conversation, they are still far ahead of the majority of people who haven’t engaged with AI tools at all.

Darby thanks Chris for the insights as the summit moves toward its next session with speaker John Munsell.