AI is gaining self awareness
- Matt Symes
- 11 minutes ago
- 4 min read
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A question came up recently that I suspect a lot of us have been turning over: There's been a wave of content suggesting AI is exponentially gaining self-awareness and capability, with some predicting a real tipping point as early as 2029. The question underneath it was simple: is there merit to this, and if so, how far out should we be planning? Glad it came up, because I think it's worth answering for everyone on this list. Nobody knows whether 2029, 2035, or any other date is right. The people closest to the frontier disagree sharply, and forecasts about this tend to carry more confidence than the evidence actually warrants. That said, I believe waiting for certainty is a strategic mistake. The distinction that mattersWhether AI ever becomes truly self-aware and smarter than humans across the board (what people mean when they say AGI) is a different question from whether it's already disrupting how we work. We don't need a self-aware superintelligence for the economics of our work to change. AI is already excellent at research, synthesis, drafting, scenario analysis, and strategic thinking. And it's already materially changing staffing, pricing, training, and client expectations. That shift doesn't wait for a tipping point. It's underway now. Three implications I keep coming back toFirst, we should assume that a growing share of our work will be performed through human-AI systems rather than by people working alone. The person stays accountable, but the workflow changes. Every team lead should be using AI today to do better, faster work, not someday, today. There are two recent HBR articles that discuss the changing function of the CEO and the Middle Management. This one hits deeper on the workforce plan redesign and how the C-Suite needs to adapt. And this one on the pressure that is falling directly on middle managers. Second, the advantage won't go automatically to whoever has access to the best model. Eventually, everyone will. The advantage will go to the team that has better workflows, cleaner knowledge, stronger governance, and people who know how to frame, verify, and supervise the work. Third, I think this creates as much opportunity as threat. Lower production costs could let us take on work that's currently uneconomic, move faster, deliver a better client experience, and build services that don't fit neatly into how we've always worked. So, yes, planning should begin nowNot as an emergency response to a predicted event in 2029, but as a deliberate capability-building process: experiment, measure, govern, redesign, and learn. The central question in my mind isn't “When will AGI arrive?” (arguably, in some form, it already has). It's this: what capabilities do we need to build now so that we benefit across the plausible range of futures, not just the one we happen to guess right? A few bets, if I had to place them
And the teams that merely automate their existing workflows will lose to the teams that redesign the entire client journey around AI. What this looks like in practiceTake any client engagement and strip it down. It's really just a large, changing pile of information: background facts, evidence, gaps and inconsistencies, numbers, comparable outcomes, and a read on how the other side tends to act. With full context on an engagement, AI can keep producing useful things on an ongoing basis: intake and value assessments, lists of what's missing, timelines, working theories, weak-spot analysis, client-ready summaries, meeting prep, and recommended next steps. The best people on a team will end up handling a lot more work, mainly because they'll spend less time rebuilding context every time they open a file. Their job shifts toward picking the right work, deciding where to spend time and money, making the hard calls, and building the kind of credibility that actually matters. Here's the catch, though. The other side gets the same tools. Competitors and counterparties will use AI to read behavior and spot weaknesses just as easily as we can. It won't simply hand bigger margins to whoever adopts it first. It'll kick off something more like an arms race, where average performers become a lot easier to predict, price, and box in. What holds up over time is what AI can't hand you off the shelf: a strong brand and steady demand, proprietary data built up over years, good judgment about what to take on, real relationships with experts, and an actual willingness to go the distance when it counts. Pricing tied to outcomes instead of hours also tends to protect margins better, because it lets you keep more of the upside when you get faster. One piece of practical adviceIf you're leading a team, you must become a power user. Start by getting honest about where your time actually goes right now. I'd bet we can find most leaders 10 to 15 hours a week back just from that (if they honestly do the exercise). Cheers, Matt New Resources to Check Out For Free NEXT WEEK: We're recording an updated version of our AI in the Workplace day (the 45-minute cut, run for over 3,500 business leaders) to have a fresh asset to share with you down the road. Since we're running it live anyway, we're opening a few free seats to sit in and catch it in real time. Wednesday, August 12 at 11 AM AT. Sign up here if you want in. Lead Gen Prompt: Find Your Next 25 Customers in 5 Minutes Recent Podcast Episodes:
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