#2 Disrupted at the Core – How AI is Dismantling the Enterprise Value Chain Faster Than You Think
Executive Summary
A half-forgotten fable about wheat on a chessboard and a 1965 prediction by Intel co-founder Gordon Moore both teach the same lesson: once growth keeps doubling (2 becomes 4, 4 becomes 8), it looks tame right up to the moment it overwhelms everything that came before. Artificial-intelligence research has just crossed that tipping point. AI has crossed that tipping-point. The price-performance of compute power, that is how much model-training muscle you get for a dollar now doubles roughly every six months, several times faster than Moore’s famous silicon curve. The next jump in capability will be larger than all previous jumps combined.
Boards that still plan on linear timelines will see margins and strategic options evaporate in real time. This article retells the chessboard parable, links it to Moore’s Law, and shows why recognising exponential change and not merely reacting to it has become a director-level skill.
1. The Chessboard Parable: A Doubling That Bankrupted an Empire
When the inventor of chess asked his emperor for one grain of wheat on the first square, doubling on each of the 64 squares, the monarch agreed, thinking the request trifling. By the 32nd square the tally reached about 279 tonnes; the very next square demanded the same again, and by the 64th the debt exceeded global wheat output many times over.
Humans miss the danger because our brains evolved for linear threats—tracking prey, gauging seasons—not for compound doublings. As physicist Al Bartlett observed, “The greatest shortcoming of the human race is our inability to understand the exponential function.”
2. Moore’s Law: Putting the Chessboard on Silicon
Gordon Moore noticed that transistor counts on integrated circuits were doubling every two years, a cadence that has guided the semiconductor industry for decades. Companies that missed the moment smartphones leapt past feature phones paid a heavy strategic price. AI has now moved onto its own chessboard, one where the squares flip twice as fast.
3. Square 33 in 2025: Real-World Signals of Exponential AI
Perplexity.ai grew from a US $3 billion valuation in early 2024 to US $9 billion eight months later, serving 600 million queries a month to 30 million users—compressing search margins in under two years.
Midjourney users generated 15 billion images in a single year, more than the historical catalogue of Getty Images; the service crossed US $50 million in revenue and a US $10 billion valuation inside its first 12 months.
Character.ai amassed 28 million monthly active users less than three years after launch, with users spending an average of two hours per visit and investors valuing the business at up to US $2.5 billion.
None of these firms existed five years ago; all now pressure-test incumbents’ profit pools.
4. Why Linear Governance Fails at Square 33
Corporate planning assumes gentle slopes: annual budgeting rounds, five-year strategic horizons, incremental talent plans. Exponentials, by contrast, deliver vertical walls. The mismatch shows up in three ways:
- Risk Radar Lag – Issues appear negligible until they are existential.
- Capital Misallocation – Resources flow to sustaining projects rather than to high-optionality bets.
- Decision Cadence Mismatch – Board cycles measured in quarters cannot steer markets that mutate in weeks.
Traditional playbooks, annual budgeting, five-year strategies and incremental KPIs were designed for slopes, not walls.
5. Board-Level Reflections and Immediate Moves
- Name the Curve – Ask whether each briefing assumes linear or exponential trajectories; insist on both scenarios.
- Shorten the Clock – Move from annual to rolling, quarterly strategy updates focused on AI-driven threats and openings.
- Invite the Heretics – Bring in younger operators, open-source founders, or internal ‘red teams’ who see the business from an exponential vantage.
- Treat Data as Dynasty – Begin valuing proprietary datasets like crown jewels; they are the gating asset for fine-tuned private models.
- Re-score Leadership KPIs – Add metrics for experiment velocity and option creation, not just incremental EBITDA.
- These moves do not replace long-term stewardship; they create the breathing room to still have a long term.
6. Where This Series Goes Next
Over the coming weeks this Insight series will unpack concrete playbooks—data moat strategies, agent-native operating models, and incentive designs—that help boards lead at exponential tempo. For directors who want to experience the dynamics first-hand, a hands-on simulation is available through a tailored Defence & Dominance session. Details are at the end of the series.
Closing Thought
The emperor never paid his wheat debt; he could not. Boards and Executive teams face a similar reckoning: every upcoming doubling of AI capability will remake value pools faster than a traditional governance cycle can respond. Recognising that fact with ‘square 33 thinking’ is the first step towards leading through it.