The Next Kodak Moment Is Coming — Why Disruption Resilience Matters More Than Growth
June 25, 2025
11 min read
The Next Kodak Moment Is Coming — Why Disruption Resilience Matters More Than Growth
AI is accelerating disruption exponentially. The critical question is no longer "how fast can a company grow", but "how deep is its moat". Our original analysis for The Market NZZ — plus the in-depth investor view for arvy readers.
The thesis in video — 1 minute
In 30 seconds — the core thesis
- AI accelerates disruption exponentially — what used to take years can happen in months. Chegg's $13B education-tech business model collapsed within months of ChatGPT's debut.
- The question has shifted — no longer "how fast can this company grow", but "how deep is its moat". Defensibility becomes the primary investment property.
- The historical Kodak parallel is real — and it will repeat. The next Kodak moment is probably happening right now, somewhere. Disciplined investors audit their portfolios systematically for disruption risk.
The original analysis — the opening
«The only constant in life is change.»
— Heraclitus, Greek philosopher (ca. 500 BC)
The Kodak Moment.
A phrase once synonymous with cherished memories now serves as a stark warning: adapt swiftly — or risk being swept away by innovation.
Today, as AI floods headlines and boardrooms alike, another critical theme emerges with equal urgency — disruption. It is central, constant, and compounding. In this new landscape, we need to change the lens through which we evaluate businesses. The focus must shift — from chasing growth to assessing durability. Growth is good. Defense is better.
The key question is no longer: how fast can this company grow? But: how well can it defend itself? A true moat isn't a metaphor. Picture a fortress surrounded by a deep and wide trench filled with crocodiles and sharks — that is what it takes to protect a business's core advantage today. The real edge lies in how resilient the business model — and its leadership — are when faced with relentless competition.
Investors are starting to pivot. The obsession with future growth is giving way to a deeper appreciation for strategic defensibility — the kind that can endure shocks, shifts, and paradigm changes. Because even the most promising growth story can unravel in an instant when AI accelerates the forces of disruption.
We've already seen what this looks like. Chegg, once a $13 billion education tech darling, seemed unstoppable. But within months of ChatGPT's debut, its business model collapsed.
History offers a chilling parallel. Kodak, once a titan of photography, failed to capitalize on the digital wave it helped pioneer. The result? A dramatic and irreversible decline.
These are not isolated incidents. They are signals. Clear, flashing red lights for anyone not stress-testing their portfolios for disruption risk.
The next Kodak moment could be happening right now. And it's coming for us all.
→ Read the full article on The Market by NZZ
Chart 1: Chegg's collapse after the launch of ChatGPT
Source: TradingView via NZZ The Market
01The uncomfortable question: what if your safest stock is actually your riskiest?
The most painful insight from the Chegg example is not that Chegg fell. It's that Chegg was considered a safe growth stock before the fall. Established business model, clear market position, predictable recurring revenues, profitable. Textbook quality by any conventional definition. And that's what makes the Kodak moment so unsettling for investors: the stocks that look safest today could be exactly the ones the next AI shock hits hardest.
This question doesn't fit into an NZZ column with the depth it demands — but it is the most important question every investor needs to ask today. Which of your positions rely on competitive advantages that AI could dissolve or reverse within the next 24–60 months? Asking this is uncomfortable, because many established business models are more vulnerable on closer inspection than their past stability suggests.
The difficulty is epistemological: what you haven't lived through, you struggle to imagine. Before 2022, Chegg was a safe quality position. Before 2007, Nokia was a safe mobile-phone hegemony. Before 2010, BlackBerry was the standard for business communication. In every case, the fundamentals looked for years exactly the way they had always looked — until suddenly they didn't. Disruption is non-linear. It comes slowly, then all at once.
Why this phase is historically special
Previous disruption waves (PCs, internet, smartphones, cloud) typically took 10–15 years from the first shock to full market reorganization. AI has compressed this timeline dramatically — in education tech, translation, legal research, customer service, code generation, comparable shifts happen in 18–36 months. This fundamentally changes investment-resilience requirements: a "10-year moat" business can become a "3-year moat" business under AI pressure, without quarterly results signaling it in advance.
02Which moats hold — and which don't
Not every competitive advantage is equally resilient to disruption. The critical exercise for any serious investor is to categorize the moats in your portfolio — between those AI strengthens and those AI dissolves. This is the single most valuable diagnostic exercise in modern quality investing.
AI-Resilient
Physical scale infrastructure
Pipelines, power grids, railways, ports, semiconductor fabs. What cannot be replicated in software retains and strengthens its value in an AI world. Examples: Waste Management, Republic Services, Waste Connections.
AI-Resilient
Regulatory entry barriers
Pharma approvals, banking licenses, regulated utilities. AI doesn't shorten a clinical trial approval timeline or simplify a bank's compliance framework.
AI-Resilient
Consumer brands with emotional anchor
Luxury, premium consumer goods, spirits, established food brands. AI cannot replicate a Coca-Cola brand or a 200-year trust relationship.
AI-Resilient
Patents and IP protection
Patent-protected pharma compounds, specialty chemistry formulas, narrowly defined technical IP. Plus complex, hard-to-replicate engineering — aircraft engines from Safran or GE Aerospace, for example. As long as IP systems hold, the protection holds.
Vulnerable to AI
Knowledge aggregation and access
What hit Chegg — tutoring, translation, legal research, many consulting businesses. When AI makes knowledge directly accessible, the intermediation moat melts.
Vulnerable to AI
Standard software without deep integration
Business models based on "feature X as a paid function" — when AI makes that function a commodity, the pricing mechanism collapses.
Vulnerable to AI
Scale moats in digital content
Publishers, individual media brands, aggregators. When content can be generated in seconds, the scarcity logic changes fundamentally.
Vulnerable to AI
Competence intermediation as service
Classical consulting models, low-threshold professional services, mass-market education providers. When AI delivers competence directly, the intermediation margin shrinks.
This categorization is not static — it shifts with every AI iteration. What's classified as "vulnerable" today can defend itself if the business model adapts (e.g. through deeper integration, own AI implementation, value-proposition shifts). What's "resilient" today can become vulnerable when new AI applications open areas we can't foresee. The exercise matters more than the individual answer.
The second layer of disruption
There's a subtler layer of AI disruption many investors miss: not the business model itself gets disrupted, but the value of growth momentum. A software business that was growing organically at 25% because new features were being developed can drop to 10% growth if AI commoditizes feature development. The business "keeps functioning" — but the valuation multiples that carried the fast growth collapse. This is not the dramatic Kodak moment, but the creeping multiple reset. Both are disruption — the first visible, the second often more painful.
03What this means for a quality portfolio
The Kodak-moment logic leads to a fundamental recalibration of what "quality" even means. Classical quality definitions — high margins, stable cash flows, durable competitive advantage — remain valid, but they need an additional filter: disruption resilience. A business can meet all classical quality criteria and still be fragile if its moat doesn't hold in an AI world.
Three diagnostic questions every one of your top positions should pass:
| Question | What to examine |
|---|---|
| 1. What is the moat based on — physical, regulatory, emotional, or digital? | Physical and regulatory moats are more AI-robust. Digital, knowledge-based moats are more vulnerable. |
| 2. Would the business still make sense at half its growth rate in valuation terms? | If the answer is "catastrophically no", the investment case depends too much on growth momentum — which AI could jeopardize. |
| 3. What would a 10× more efficient AI solution change about this business? | The honest answer typically produces a differentiated view — some positions are more robust than thought, others more fragile. |
This exercise is not a call to sell — it's a call to conscious positioning. Some fragile positions you can consciously keep, because you believe in the growth path over the next 2–3 years. Some resilient positions you can consciously scale up, because they are structurally protected against AI risks. What shouldn't happen unconsciously: holding fragile positions because they have historically always been "safe".
How this disruption-resilience logic is applied in practice during stock selection — and which business models come through fundamental shifts systematically better — is deepened in our pillar article The Tortoise Problem: Why Quality Wins — If You Stay the Course. The concrete arvy allocation is documented in the Quarterly Report Q1 2026.
04Three scenarios for the AI disruption wave
No one can time the market — we can't either. But we can describe three plausible paths for how AI disruption shapes the next 24 months:
Bull Case
Resilience premium emerges — quality champions outperform structurally
Several additional Kodak moments in the next 12–18 months make disruption resilience a dominant investment property. Investors differentiate systematically between disruption-resilient and disruption-vulnerable business models. Valuations shift accordingly — quality champions with physical, regulatory, or brand-based moats trade at higher multiples, fragile models at lower ones. In this scenario, discipline is most profitable.
Base Case
Selective disruption shocks, sharp sector differentiation
Not one big disruption wave, but a series of sector shocks — education tech, legal research, translation, customer service, individual software subsectors get fundamentally reorganized over the next 24 months. Investors with well-diversified quality portfolios come through relatively unscathed; investors with concentrations in vulnerable sectors experience hard drawdowns. Differentiation becomes the key skill. Our base case.
Bear Case
Broad AI-driven market reorganization — many quality definitions break down
AI disruption spreads faster and more unexpectedly than forecast. Many business models considered "safe" today prove vulnerable. The result: a broad valuation reordering across sectors, with dramatic value swings for investors who haven't systematically examined their portfolios for disruption. In this scenario, the exercise from section 02 pays off dramatically — those who did it are much better positioned than the average.
How disciplined investors navigate fundamental market shifts — and why quality typically comes through full market cycles better than reactive strategies — is described in our pillar "Investing in Turbulent Times".
05What to check now
The disruption-resilience exercise is the most valuable 30 minutes you can invest in your portfolio in the coming weeks. Four concrete checks:
1. Moat classification of your top 10 positions. Walk through your largest positions and assign each to one of the four resilient or four vulnerable moat categories from section 02. For most investors, this exercise reveals: 30–50% of the portfolio sits on moats under active AI threat. That's not necessarily a problem — but it's a conscious observation worth having.
2. AI stress test per position. For each major position, ask: what would a 10× more efficient AI solution in this area change about the business? Some businesses are robust (Roche for example — AI doesn't make FDA approval faster). Others have real risks (standard software, consulting, education services). The exercise isn't a sell trigger, but an awareness exercise.
3. Kodak-moment watchlist. Which business models in your portfolio or on your watchlist have the potential to be dramatically disrupted in the next 24 months? Maintaining this as a deliberate "watchlist" — without an immediate sell decision — gives you reactivity if disruption accelerates.
4. Quality resilience gap. What percentage of your portfolio sits on clearly resilient moats (physical, regulatory, emotional/brand, IP-protected)? If this number is below 40%, your portfolio has structurally less disruption protection than a balanced quality allocation. Gradual shifting into more resilient positions is a reasonable response.
What disciplined investors do now
They don't panic-sell all "vulnerable" positions — that would be strategy hopping. They run the disruption-resilience exercise systematically, categorize positions honestly, and adjust gradually by deliberately directing new investments or savings-plan contributions toward more resilient businesses. Over 18–24 months, the allocation shifts gradually. It's not spectacular, but it's exactly what makes the difference between loss and protection ahead of a real Kodak moment. Discipline is boring — and precisely for that reason valuable.
06Frequently asked questions
Does this mean arvy no longer holds any "vulnerable" business models?
We examine every position for disruption resilience, but we selectively also hold businesses we classify as "moderately vulnerable" — when management is demonstrably responding to AI shifts, when valuation already contains a risk discount, or when other factors cushion the risk. Disruption resilience is a lens, not a binary exclusion criterion. Concrete positions are transparently documented in the arvy Quarterly Report Q1 2026.
How fast do I need to react to a detected "Kodak moment"?
Honest answer matters here: disruption shocks are non-linear. Sometimes you have 6–12 months warning, sometimes only weeks (cf. Chegg). What counts is preparation, not reaction speed. Whoever has adjusted their portfolio for disruption resilience needs less reactive action at a concrete shock. Whoever hasn't typically reacts too late — when the stock has already lost 50–80%.
Does this mean I should exit tech and software entirely?
No, categorically not. Tech and software remain one of the largest value-creation sectors in the world economy. What has changed: selection within these sectors has become much more important. Hyperscalers with their own AI infrastructure are more robust than standard SaaS providers whose core function AI can replicate. Within software, those with deep customer integration and IP-protected data flows win; those with superficial functionalities lose. Disruption resilience means differentiation, not sector abandonment.
What about Swiss quality champions like Nestlé, Roche, Novartis — are they AI-resilient?
We don't give blanket individual-stock recommendations. But generically: many classical Swiss quality champions stand on moats that structurally belong to the more resilient categories (pharma patents, consumer brands with emotional anchors, specialty chemistry). That's not per se a buy signal — valuation and company-specific factors remain decisive. But the moat characteristic is relatively resilient against AI disruption. Applying the three diagnostic questions from section 03 individually to each position is the disciplined way.
Read next — the thematic anchors of this analysis
The Tortoise Problem
Why real quality survives AI disruption
arvy Quarterly Report Q1 2026
Current sector allocation transparently documented
Trees Don't Grow to the Sky
Why unsustainable growth destroys returns
Focus on the Top Line
Top-Line × Margin Expansion — the compounder engine
Investing in Turbulent Times
Quality through fundamental shifts
Investing with arvy: The Complete Guide
How this analysis fits the overall strategy
Defense is the new growth strategy
The idea that growth is the only relevant investment property has shaped the last 15 years. AI fundamentally changes this equation. In a world where growth rates can be erased by a single model iteration, defensibility is no longer a defensive property — it is the strategic core quality. The businesses that will compound through the next decade are not necessarily those with the fastest growth today, but those with the deepest moats tomorrow.
The next Kodak moment will come. Probably several. They will hit investors who didn't look — who assumed the past would equal the future, that historical stability guaranteed future stability. But they will also not hit investors who did the diagnostic exercise, who categorized their moats, who deliberately calibrated their portfolio for resilience. The Kodak lesson is not "all quality stocks are at risk". The lesson is: look, think, adjust deliberately. Discipline beats reaction. Preparation beats luck. As Heraclitus said 2,500 years ago — the only constant is change. The only investor who thrives is the one who prepares for it.
Original written by Thierry Borgeat, Co-Founder of arvy, for The Market by NZZ. The extended arvy version was reviewed by Patrick Rissi, CFA and Florian Jauch, CFA. Data sources: NZZ The Market, own analyses, public company data on Chegg, Kodak. Last update: April 2026.
Disclaimer: This article is for general educational purposes and does not constitute personal investment advice. Security names mentioned are illustrative and not buy- or sell-recommendations. Past performance is no guarantee of future results. Scenarios are assessments, not forecasts. arvy is a FINMA-supervised asset manager with a CISA license (Art. 24). Imprint & Legal Notices.
