Which stocks are the most resilient to disruption?

2026-08-01 · By Lubin Danilo, founder of Lubin Investment

I compared the quality score out of 10 of fifteen large-cap stocks to a distinct grade, resilience, which measures their ability to still matter in ten years against AI and disruption. Counter-intuitive result: Amazon leads with a quality score of just 6 out of 10, while Mastercard and Adobe, scoring 9 and 10, fall into the fragile category.

A different question from my quality score out of 10

On my site, every stock gets a quality score out of 10 based on concrete financial criteria: profitability, sales and cash growth, share buybacks, controlled debt. That score answers one specific question: is this company financially solid today? But it answers no other question, in particular this one: will this company still have a role in ten or twenty years, once artificial intelligence, automation, or a new competitor have reshuffled its industry?

That is exactly the gap a second, separate grade fills, one I call resilience. It runs from A (very solid) to E (fragile) and measures a company's ability to exist AND thrive in the future, not just its current financial snapshot. A company can perfectly well combine excellent numbers today with fragile resilience for tomorrow: these are two separate questions, exactly the way I always keep a stock's quality and its price separate.

This grade is still being rolled out across my universe of several thousand tickers: it is available today for the most followed and best-documented companies, not yet across the whole site. I spell this out clearly further down, because I would rather give an honest sample than a false impression of full coverage.

How I calculate this resilience grade

The grade rests on six criteria, each scored separately and then combined into a 0-100 score, which is then converted into a letter from A to E. The first, the moat, measures the depth and durability of whatever protects the company's profits: a genuine wide moat has to combine a durable rent, a model that is hard for a competitor to replicate, and a real penalty for a customer who would switch supplier. The second, disruption resilience, tests directly whether AI, a new technology, or a new entrant reinforce or weaken the business: full marks require that at least one identified disruption reinforces the company and none weakens it.

The next four criteria dig further. Residual dependencies measure how much weight suppliers, platforms, regulators, or talent still carry for the company, dependencies that, left unmitigated, can become a breaking point. Structural demand capture looks at whether an already observable structural trend is genuinely monetized in revenue or contracts, not just promised in an investor slide. The role in tomorrow's economy, the most forward-looking criterion, asks whether the underlying need the company serves, its own role in the value chain, and its ability to capture a share of it, all three survive in a world where AI and automation are fully adopted. Finally, recurrence and absorption capacity check whether revenue naturally repeats from one period to the next and whether the balance sheet can absorb a shock without breaking the business model.

To give a concrete sense of the gap these criteria can produce: Moody's scores 87 out of 100 on resilience (grade A), with full marks on four of the six criteria. Meta Platforms, at the other end, scores 18 out of 100 (grade E), with a flat zero on the moat, on structural demand capture, and on its role in tomorrow's economy. The same scoring model, applied to two very different companies, produces a 69-point gap.

The ranking: who holds up against disruption, who wobbles

Here is a sample of sixteen well-known large caps, ranked by descending resilience grade. I deliberately picked names you already know, so the comparison with your own intuition is possible.

Company	Quality score /10	Resilience	Score /100
Amazon (AMZN)	6/10	A	92
Moody's (MCO)	9/10	A	87
Visa (V)	8/10	A	87
Nvidia (NVDA)	9/10	B	79
Apple (AAPL)	8/10	B	79
Microsoft (MSFT)	8/10	B	73
Alphabet (GOOGL)	6/10	C	68
Salesforce (CRM)	10/10	C	51
Tesla (TSLA)	4/10	C	51
Costco (COST)	7/10	D	49
Mastercard (MA)	10/10	D	43
Coca-Cola (KO)	7/10	D	41
Adobe (ADBE)	9/10	D	39
McDonald's (MCD)	6/10	E	34
Airbnb (ABNB)	10/10	E	32
Meta Platforms (META)	8/10	E	18

The contrast jumps out if you look at the left column and the right column at the same time. Salesforce, Mastercard, and Airbnb all show the best possible quality score, 10 out of 10, yet fall into grade C, D, and E respectively on resilience. Conversely, Amazon caps out at 6 out of 10 on quality, the lowest score in this entire ranking tied with Alphabet and McDonald's, and yet tops the resilience ranking. The two grades measure genuinely different things: do not expect them to line up.

The paradox: a near-perfect quality score does not prevent grade E

Meta Platforms illustrates this paradox most clearly. The company scores 8 quality criteria out of 10: its margins are thick, it buys back its own stock aggressively, its balance sheet is solid, as I showed in my analysis of its latest quarterly results. But on the resilience grid, it scores a flat zero on three of the six criteria: the moat, structural demand capture, and its role in tomorrow's economy. The mechanism makes sense once you understand it: almost all of Meta's revenue comes from advertising served on its platforms, a model that depends on capturing and holding human attention. If generative AI changes how people get information, entertain themselves, or interact online (AI agents that summarize and filter information instead of a social feed, for instance), the very mechanism that makes Meta money today is not guaranteed to survive in its current form. This is a question of business-model structure, not execution quality.

Mastercard, Adobe, and Airbnb follow a similar logic without being identical to each other. All three show a near-perfect quality score (9 or 10 out of 10, as detailed in my full thesis on Mastercard), and yet fall into grade D or E on resilience. I will stay honest about one point: the resilience grid is newer and more forward-looking than my quality score, which is built on decades of fundamental-analysis literature. The precise detail of each sub-criterion can look harsh at first glance (a global payment network like Mastercard scores zero on the strict definition of moat used here), and I would rather say so than invent an after-the-fact justification. What I mostly take away is the direction of the signal: these three companies execute remarkably well today, but the resilience grid asks a different, harder question about tomorrow.

Amazon: near-perfect resilience, a quality score of just 6 out of 10

Amazon's case deserves its own section because it shows so clearly why the two grades should never be conflated. Its quality score of 6 out of 10 is dragged down by a very thin free cash flow margin, squeezed by massive spending on AI data centers. On the resilience grid, however, Amazon scores the maximum on five of the six criteria, including a perfect score on disruption resilience: in its case, the identified technological disruptions (generative AI first among them) reinforce the model rather than weaken it, because Amazon Web Services sells exactly the computing infrastructure those same disruptions need to exist. You can check these figures in detail on Amazon's page.

The lesson: a massive investment that temporarily squeezes available cash, and therefore the quality score that judges today's financial snapshot, is not the same thing as a fragile business model. Amazon is spending to build the infrastructure the next decade will consume, which weighs on its cash today but strengthens its structural position for tomorrow. That is exactly the kind of nuance a single score, taken in isolation, can never capture.

The honest limits of this grade

I would rather say this clearly than leave a false impression: this resilience grade is still a work in progress on my site. It is currently calculated only for part of my stock universe, concentrated on the most followed and publicly best-documented companies, the ones for which enough qualitative information exists to judge a moat, a dependency, or a sector trajectory. Many smaller stocks, or ones less covered by the financial press, do not have a grade yet: that is not a judgment on their quality, it simply means the work has not been done for them yet. I would rather have an honest, well-documented sample than broad but sloppy coverage.

How I use this resilience grade

I use it as a third dimension, after quality and price, never as a standalone signal. A stock can be very good quality, fairly valued, and still carry a long-term structural risk that only this resilience grade brings to light: that is a signal to pay attention to, not an automatic sell order. Conversely, excellent resilience never excuses skipping a check of current financial quality and the price paid: the three dimensions (quality, price, resilience) stay separate and combine, they do not replace one another. That is exactly the logic I wanted to automate in my stock analysis tool: judging each dimension for what it is, never blending them into a single number that would hide what matters.

The resilience grade (A to E) measures whether a company will still matter in ten years against AI and disruption; it is distinct from the quality score out of 10, which judges its current financial soundness.
Amazon (6/10 on quality) earns the best resilience in the ranking (92/100, grade A) thanks to its structural position in AI infrastructure, despite cash squeezed today by heavy investment.
Salesforce, Mastercard, and Airbnb, all three scoring 9 or 10 out of 10 on quality, fall into grade C, D, or E: excellent execution today does not guarantee a solid structural position tomorrow.
Meta illustrates the mechanism most clearly: a flat zero on the moat, structural demand capture, and its role in tomorrow's economy, because its advertising model depends on human attention that generative AI could capture differently.
This grade remains partial, still being rolled out across my stock universe: I use it as a third dimension, never as a standalone signal that would replace quality and price.

FAQ

What is the resilience grade, and how does it differ from the quality score out of 10?

The quality score out of 10 judges a company's current financial soundness (profitability, cash growth, debt). The resilience grade, from A (very solid) to E (fragile), judges something else: its ability to still matter in ten or twenty years against artificial intelligence, automation, and new competitors. These are two separate questions that can give very different answers for the same company.

How can a stock scoring 10 out of 10 on quality fall into resilience grade E?

Because quality judges today's execution (margins, growth, buybacks) while resilience judges the business-model structure for tomorrow. Airbnb, for instance, scores 10 out of 10 on quality but falls into grade E: excellent current execution does not guarantee a protected structural position in ten years.

Why does Amazon show near-perfect resilience with a quality score of just 6 out of 10?

Its quality score is dragged down by a very thin available-cash margin, squeezed by massive AI infrastructure spending. But that same spending strengthens its structural position: Amazon Web Services sells the computing infrastructure generative AI needs, which explains its near-perfect resilience score.

Does this resilience grade cover every stock on the site?

Not yet. It is currently calculated for part of my stock universe, concentrated on the most followed and publicly best-documented companies. I would rather say so clearly than let you believe in a complete coverage that does not exist yet.

Does a fragile resilience grade (D or E) mean you should sell or avoid the stock?

No. It is a long-term signal to pay attention to, not a sell order. A stock can remain good quality and fairly valued today while carrying a structural risk worth watching. This is not personalized investment advice, do your own research.

About the author

Written by Lubin Danilo, founder of Lubin Investment. A self-taught individual investor, I find fundamental analysis fascinating, and it has delivered excellent results. For three years now, my performance has beaten the S&P 500. But analyzing every stock took too much time: sites with incomplete data, calculation methods and criteria never aligned with mine. And spotting the best stocks was just as time-consuming, even with my own well-defined checklist. So I put my software development background to work to build this software, base my investment strategy on its results, and share it with people who share the same passion as me. It judges a company's quality and its price separately, using criteria drawn from the financial literature (Warren Buffett, Michael Mauboussin, Aswath Damodaran).