AI and the Collapse of Business Moats

This entry is part 7 of 8 in the series Gen-AI Erodes Business Models

For decades, the equity value in corporations has rested on their ability to build and defend “moats” — structural barriers that protect profits from competition. These moats have come in many forms: scale, brand, distribution, information asymmetry, and switching costs. They created stability for incumbents and concentrated power in large, bureaucratic organizations.

Generative AI is systematically weakening these barriers. The result is not only business model erosion at the firm level but also a potential reshaping of entire economies.

 

From Scale to Individual Leverage

Scale once justified headcount. Hundreds of analysts, marketers, or designers were needed to sustain output. Now individuals and small teams can harness AI to achieve capacity that rivals entire departments.

  • Example: A two-person startup can now produce marketing campaigns, financial models, and investor presentations that previously required dozens of staff. Indie game developers using AI for art and dialogue design can compete with mid-tier studios that once relied on large teams.

Organisational scale still matters in capital-intensive industries (like manufacturing or energy), but in knowledge work it is becoming far less decisive.

From Information Asymmetry to Commoditised Knowledge

Consulting firms, data vendors, and publishers thrived by owning proprietary insights. AI undermines this advantage by synthesizing public data at scale, surfacing answers once locked inside databases or hidden behind paywalls.

  • Example: Legal AI tools such as Harvey or Casetext can draft briefs and conduct case law research at a fraction of the cost of junior associates, eroding law firms’ advantage in information-heavy tasks. Market research once requiring paid reports from Gartner or McKinsey can increasingly be replicated with AI-driven synthesis.

Knowledge is becoming less about what you own, and more about how you contextualize and apply it.

From Network Effects to Layer Inversion

Platforms like Amazon, YouTube, and Airbnb have long benefited from network effects. The more users and suppliers they attracted, the stronger their position became. Continue reading

Tariffs, Trade Deficits, and Prosperity Surpluses: Rethinking the U.S. Position in the Global Economy

This entry is part 2 of 4 in the series Tariffs

Introduction

The debate over tariffs in the United States is often framed around trade imbalances. Successive administrations have argued that persistent deficits in goods — imports consistently exceeding exports — reflect unfair competition and a loss of industrial capacity. This framing positions America as a country being taken advantage of. Yet when the lens is widened beyond bilateral trade flows to the global distribution of income and production a different picture emerges. With only around 5% of the world’s population but roughly 25% of global GDP the United States enjoys a disproportionate share of prosperity. From that perspective the “problem” of trade deficits looks less like evidence of decline and more like a natural by-product of extraordinary privilege.

Tariffs as Fiscal Tools

Tariffs are a fiscal instrument. They raise government revenue by taxing imports, while simultaneously transferring wealth from importers and consumers to the state and, indirectly, to domestic producers who gain from reduced competition. This redistribution is visible and politically attractive. For example the recent U.S. tariff on Mexican tomatoes raised costs for consumers but promised relief for Florida growers.

Economically, however, tariffs act as a negative supply shock. By making imports more expensive they increase consumer prices, disrupt supply chains, and reduce efficiency. They may stimulate some investment in protected sectors but this is often inefficient investment, guided not by comparative advantage but by political shields. Continue reading

Consulting in the Age of AI

This entry is part 6 of 8 in the series Gen-AI Erodes Business Models

Consulting has long thrived on a simple premise: firms bring external perspective, proprietary knowledge, and structured problem-solving to help organizations address complex challenges. The value of the consulting model rests on three pillars: the brand premium of trusted firms, access to proprietary databases and benchmarks, and the ability to mobilize armies of analysts to process information quickly.

But generative AI may be eroding all three.

AI as a Force-Multiplier for Clients

Consultants have justified their fees by framing problems, gathering information, and producing structured recommendations. Yet senior and mid-level managers already hold most of the operating experience that consultants spend weeks “discovering.”

With generative AI managers can now:

  • Frame insights directly: into prompts enriched with company data.
  • Test hypotheses instantly: cross-checking with public benchmarks or market analysis.
  • Generate strategic options: without needing external researchers.

In this model, AI helps clients convert tacit knowledge into structured intelligence. What once required an outside team can now be done internally faster, cheaper, and sometimes better.

Continue reading

Banks and the Utility Era

This entry is part 5 of 8 in the series Gen-AI Erodes Business Models

Banks have long enjoyed dual advantages: they not only owned the balance sheet but also owned the customer relationship. Depositors and borrowers came for safety, trust, and capital; and then stayed because switching was costly and alternatives were limited.

Fintech challenged the second advantage, but not the first. Generative AI is now pushing the erosion further.

The Irreducible Moat: Balance Sheet Trust

Despite waves of fintech innovation, large regulated banks remain irreplaceable because they own balance sheets that are:

  • Large and diversified: able to absorb shocks.
  • Equity-buffered: giving depositors confidence.
  • Regulator-backed: often explicitly by central banks.

Depositors, savers, and institutional investors continue to prefer this combination. For all the user experience innovation in fintech the fundamental preference for safety and stability means banks retain their role as systemic anchors.

Portability: Banks as Utilities

The true disruption is not replacing banks but commoditizing them.

Continue reading

Marketplaces and the Rise of AI Shopping Agents

This entry is part 4 of 8 in the series Gen-AI Erodes Business Models

Marketplaces have been one of the internet’s most successful business models. From Amazon to eBay to Alibaba they thrive by owning the consumer entry point, controlling search and discovery, and taking a cut of every transaction.

But generative AI is beginning to erode this model as well.

How Marketplaces Work Today

The traditional marketplace model depends on three pillars:

  1. Traffic Control: Consumers start their journey on the platform.
  2. Search & Discovery: The marketplace determines what products are surfaced thus shaping demand.
  3. Transaction Capture: Every sale flows through the platform, securing fees and data.

The platform’s strength lies in controlling both demand aggregation and supply access.

The AI Shopping Agent Shift

Generative AI agents change the consumer journey. Instead of searching inside Amazon or eBay, a consumer can now tell an AI: “Find me the best mid-range laptop for graphic design under $1,500.”

The agent can then:

  • Search across multiple marketplaces and independent sellers.
  • Compare prices, reviews, and delivery times.
  • Present the user with a shortlist — often with a single “best option.”

In this world, the marketplace is no longer the starting point. It becomes just one of many suppliers feeding the AI layer.

Continue reading

Social Platforms in the Age of Generative AI

This entry is part 3 of 8 in the series Gen-AI Erodes Business Models

For nearly two decades social platforms like Facebook, Twitter (X), YouTube, and TikTok have defined the way information is consumed online. Their business model has been remarkably consistent:

  1. Capture attention through feeds optimised by algorithms.
  2. Monetise discovery by inserting ads into those feeds.
  3. Lock in creators and audiences by making the platform the essential intermediary between the two.

This model relies on one central feature: control over content discovery. The feed is the bottleneck and the algorithm is the gatekeeper.

Generative AI is shifting that balance of power.

From Algorithmic Feeds to User-Directed Discovery

In the old model users consumed what the platform’s algorithms decided was relevant. Discovery was not organic, rather it was curated by the system to maximise engagement.

Generative AI enables a different interaction. Users can now summarise, filter, or reorganise content themselves without depending on the platform’s feed. For example:

  • Instead of scrolling through thousands of tweets, a user can ask an AI agent to summarise trending discussions.
  • Instead of relying on YouTube’s “up next” suggestions, a user can instruct AI to curate a learning path across multiple creators.

The power shifts from platform-driven feeds to consumer-driven control. Continue reading

The Airline Loyalty Program Revolution

This entry is part 1 of 2 in the series Business Model Innovation

Airlines are notorious for their slim margins. Volatile fuel prices, labor disputes, and economic downturns have historically left the industry exposed to shocks that can wipe out years of profitability in a single quarter. Yet hidden in plain sight lies one of the most successful business model innovations of the last half-century: the airline frequent flyer program.

What began as a simple marketing perk in the late 1970s, rewarding customers with miles for loyalty, has since evolved into a multi-billion-dollar financial powerhouse. In fact, loyalty programs have in some cases become more valuable than the airlines themselves.

Examples include:

  • United’s MileagePlus was appraised at $21.9 billion in mid‑2020 while the airline itself was much less valuable.
  • United also secured a $5 billion loan using MileagePlus as collateral—valued around $20 billion.
  • United’s and Delta’s programs were separately valued at $22 billion and $24 billion respectively.

From Perk to Balance Sheet Powerhouse

Early frequent flyer programs were straightforward: fly more, earn miles, redeem them for free flights. But over time airlines recognized that miles were more than just a perk—they were a currency.

By selling miles to banks, credit card companies, hotels, and retailers, airlines created high-margin, recurring revenue streams. In 2019 alone U.S. airlines generated billions in revenue simply from selling miles to credit card issuers.

The true significance of this shift came into focus during crises. In American Airlines’ 2011 bankruptcy its AAdvantage loyalty program was valued at nearly USD 20 billion far exceeding the airline’s market capitalization at the time. During the COVID-19 pandemic airlines used their loyalty programs as collateral to raise emergency financing. What once looked like a side business became the crown jewel of the balance sheet.

Reframing the Business: Airlines as Financial Services Firms

The key insight was reframing. Airlines realized they weren’t just in the business of moving passengers from A to B. They had become issuers of a loyalty currency, with economics closer to a financial services firm than a transport company. Continue reading

Search Engines in the Age of Generative AI

This entry is part 2 of 8 in the series Gen-AI Erodes Business Models

 

For two decades, search engines have been the primary gateway to the internet. Their business model rested on a simple formula:

  1. Aggregate attention by being the starting point for information discovery.
  2. Monetize visibility through advertising, with sponsored results and keyword auctions.
  3. Lock in users through habitual use and incremental improvements in relevance.

This model created some of the most profitable businesses in history. Yet generative AI now strikes at the very foundation of this model.

From Queries to Answers

Traditionally, search engines returned lists of links. Users had to sift through them to find what they needed. Advertisers paid to appear prominently in those lists.

Generative AI reframes this interaction. Instead of links, users receive direct, synthesized answers. The entire logic of the search engine — page ranking, sponsored slots, click-through funnels — is undermined when the answer bypasses the list.

Erosion of the Advertising Core

This shift has two profound consequences:

  • Fewer impressions – If the user receives their answer in the AI output, they have less reason to scroll through search results or click ads.
  • Weaker targeting – AI intermediates the query, stripping out much of the context advertisers once used to optimize placements.

The economic engine of search is paid visibility and weakens as AI compresses the user journey from query links clicks to simply query answer. Continue reading

Gen-AI Erodes Business Models: Series Introduction

This entry is part 1 of 8 in the series Gen-AI Erodes Business Models

 

Generative AI is beginning to erode some of the most entrenched business models of the last century. Where traditional competitive moats relied on scale, distribution, information asymmetry, or regulatory capture, AI is flattening those advantages. What once seemed unassailable is now vulnerable.

This series explores how AI is reshaping industries not by incremental efficiency gains, but by dismantling the very structures that created durable equity value in the first place. The common thread: AI collapses barriers to entry, redistributes power, and creates space for small, nimble actors to compete with, or even replace, incumbents.

The Core Thesis

Most legacy business models share a common foundation: they controlled the first step in the customer journey (search, discovery, or access) and extracted value through aggregation. AI undermines this control by allowing consumers and businesses to bypass the gatekeepers and move directly to optimal outcomes.

This shift does more than disrupt individual companies, it also changes the geography of global commerce. Power tilts away from monolithic institutions and toward decentralized ecosystems, where SMEs and independents can thrive on equal footing. Nations and cities that once competed to host multinational headquarters may instead compete to host the AI ecosystems that enable these SMEs worldwide.

Where We’re Going

Upcoming posts will map out how this plays out sector by sector: Continue reading

Strategic Reframing in Business Negotiation: Lessons from Mexico’s Tomato Export Policy

This entry is part 1 of 4 in the series Tariffs

Background & Context

Since 1996, the Tomato Suspension Agreement regulated Mexican tomato exports to the United States, establishing pricing and quality standards. This arrangement provided stability in a market where Mexico supplied the majority of U.S. winter tomatoes.

In July 2025, the U.S. withdrew from the agreement and imposed a 17% anti-dumping duty on Mexican tomato imports. The move was intended to support domestic growers—particularly in Florida—and was framed around claims of unfair pricing. The duty affected roughly two-thirds of U.S. tomato supply, valued at around $3 billion annually (Reuters, July 14, 2025).

Mexico’s position was immediately challenging. Tomato exports to the U.S. were projected at 1.83 million metric tons in 2025—around 93% of its total exports—and output was expected to fall about 5% in response to the tariff (USDA Foreign Agricultural Service, Aug 2025).

On August 8, 2025, Mexico’s economy and agriculture ministries announced minimum export prices (MEPs) for each tomato variety—for example, $1.70/kg for cherry, $0.88/kg for Roma—aimed at protecting domestic supply and rural livelihoods while also signaling fair-market compliance (Reuters, Aug 10, 2025).


The Strategic Move: Narrative Judo in Action

Mexico’s introduction of MEPs is an example of narrative judo—using the momentum of the other side’s framing to reverse positional disadvantage and redefine the terms of engagement.

Continue reading