Driving Insights in the Age of AI
When Knowing Isn’t Enough. Overcoming the Commoditization of Knowledge
The Knowledge Saturation Paradox
Remember when the hardest part of any project was finding the information? Today the problem has flipped: every answer sits one prompt away and the real work is deciding which answers matter. Knowledge has become a commodity—abundant, low‑cost, and almost weightless. Yet with this abundance comes a paradox: when everyone knows everything, knowledge itself loses strategic value. If access is universal, where does the competitive edge come from?
The Algorithmic Monoculture (The Quiet Shift No‑One Talks About)
Large language models promised infinite originality, yet most of them were trained on the same public soup of text. Ask three different chatbots a nuanced question and you’ll often get the same middle‑of‑the‑road reply, polished but predictable. This quiet convergence—call it an algorithmic monoculture—flattens thinking into consensus mush. Competitive edge now depends on escaping that gravitational pull toward safe, identical conclusions.
From Information Advantage to Insight Advantage
Before the internet, having the facts first was enough. In the Google era, speed mattered. In the LLM era, neither is special: everyone has the facts instantly. What endures is the ability to turn raw material into a perspective that others haven’t considered yet. Insight is interpretation plus intent which is the moment data crosses over into a clear, confident "therefore we should…".
How AI Accelerates Commoditization
AI is not just leveling the playing field – it’s flattening it. Drafting a memo, profiling a market, sifting annual reports—jobs that once signaled expertise now look like table stakes. As default knowledge rises, decision makers risk drowning in a warm bath of competent but interchangeable analysis. Noise increases, signal stalls.
The Hidden Cost of Cognitive Off‑Loading
There’s a subtler danger in letting machines chew the thinking for us. The less mental friction we feel, the weaker our pattern‑recognition muscles become. Over time companies can lose their intuitive sense for an industry—the half‑remembered anecdotes and intuitive leaps that never make it into a database but often spark the breakthrough. Insight, therefore, is not just about speed – it’s also about retention: keeping enough mental friction to foster novel connections humans alone can see.
The Gap: Insights as the New Scarcity
That is why genuine insight is suddenly scarce again. It requires synthesis across disciplines, an eye for context, and crucially the confidence to lean into a reading that might be wrong. Good insights feel slightly uncomfortable; they carry tension. They are also, for a brief window, non‑fungible: once an insight is obvious to everyone, its value collapses. In an age where everyone can access the same knowledge base, those who can consistently extract real insights will create disproportionate value.
Expert Insight: The Last Offline Frontier
Talk to people who spend their days on factory floors, in grow‑rooms, or inside regulatory offices and you’ll hear things you won’t find in any dataset. A maintenance lead knows the seal that always fails in July; a winemaker can taste next year’s mold risk; a junior civil servant might mention a clause that’s just been struck from a draft bill. None of this tacit knowledge is searchable, and no model can predict it before someone says it out loud. Surfacing it means picking up the phone, scheduling coffees, and walking the shop floor—the slow, slightly awkward work most teams skip. Precisely because it is messy and offline, it remains the last well of insight that hasn’t been flattened into commodity information. The insight itself may resist commoditisation, but with the right tools its discovery and access can be shared far more widely.
Winning Insight Velocity and Insight Arbitrage
Having a clever perspective is good; having it first is better. Speed matters – but in the future, it’s the speed of generating and accessing insights that will define leaders.
We measure that gap—raw information to action taken—as insight velocity. Move quickly and you enjoy a period of insight arbitrage, exploiting a reading before the market digests it. Our job is to shorten that loop without losing the human judgment that keeps it sharp.
The Quiet Rise of Insight Privacy (The New Trade Secret)
Firms used to guard datasets. Now the smarter ones guard interpretive frameworks: proprietary taxonomies, contrarian heuristics, shadow models that never leave the vault. We expect this to merge into a new discipline—insight privacy—where the moat is not what you know (raw data) but how you see (the lens through which the data is viewed). Protecting that lens from replication becomes paramount.
Conclusion
Knowledge now costs nothing while insight can still tilt a market, converting one into the other has become both the hardest and the most profitable job in business. The challenge—and the opportunity—is to deliver those insights at machine speed to the people bold enough to act on them.
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The views expressed here are my own. All information contained in here has been obtained from publicly available information. While taken from sources believed to be reliable I have not independently verified such information and make no representations about the enduring accuracy of the information or its appropriateness for a given situation. This content is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. Charts and graphs provided within are for informational purposes solely and should not be relied upon when making any investment decision. For questions simply reply to this email.