Is Quantum Really Where AI Was Five Years Ago?

“I would say quantum is there where maybe AI was five years ago,” said Sundar Pichai, CEO of Google and Alphabet in a November 2025 interview, explaining Google’s investment into quantum at that time.

Whether quantum is the next AI has become a common question across the deep technology ecosystem, as AI offers a tempting blueprint for how valuations that once looked untenable can hold as revenue scales. Quantum's smaller revenue base makes its valuations look demanding. However, some AI companies once carried similarly demanding valuation multiples before revenue growth transformed the investment picture. Comparing quantum today with AI before its commercial expansion gives a potential financial pathway, although the significance of the technical milestones that are yet to be reached for quantum cannot be understated.

A fair assessment sets like against like, so the comparison in this article is confined to pure-play companies, the 10 highest-valued AI companies (Figure 1), led by Anthropic and OpenAI, and the 10 highest-valued quantum companies (public and private) (Figure 2). The AI and quantum divisions of Google, Microsoft, and IBM are excluded, since their valuations and revenue are not cleanly attributed, and companies that do not disclose these metrics stay in view but outside the averages. A "multiple" is how many dollars investors are willing to pay for every US$1 of a company's annual sales. Measuring each company's valuation against its revenue to calculate a multiple makes it possible to trace how AI's leaders grew into their prices, what the same path would demand of quantum’s largest companies, and where the quantum industry's route inherently departs from AI's.

Figure 1: Selected AI companies’ approximate equity valuations, annual revenue measures and valuation to revenue multiples, as at October 2026.

Figure 2: Selected quantum companies’ approximate equity valuations, annual revenue measures and valuation to revenue multiples, as at October 2026.

What AI's Falling Multiples Mean for Quantum Valuations

As companies grow and prove themselves, investors usually pay less per dollar of sales, because less of the price is a bet on the future. The AI giant Anthropic offers the clearest example of a valuation holding, then growing, as revenue scaled, and multiples fell. Its early 2024 Series D valued it at US$18.4 billion on annualised revenue near US$100 million, roughly 184×, a round lead investor Menlo Ventures has since called a "bet-the-firm moment”. By May 2026 a US$965 billion valuation rested on annualised revenue above US$47 billion, about 20×, after revenue grew more than 470-fold and valuation roughly 52-fold. Warnings of an AI bubble suggest some valuations may yet prove ambitious, but the sales beneath them are tangible, at least in some cases. Anthropic's annualised revenue of US$47 billion in May 2026 was more than two and a half times the US$18.4 billion the whole company was worth just over two years prior. Databricks followed the same path but at a lesser scale, its multiple falling from about 63× in 2021 to 29× in 2023 as revenue grew 150% and valuation 13%. In both cases, revenue, driven by customer adoption, grew and held.

Figure 3: Illustrative quantum company value scenarios using a 200× starting multiple and future multiples of 28× for the individual AI company average and 15.2× for the combined AI basket.

That adoption followed AI's inflection point, the moment a technology becomes useful enough for customers to pay for it at scale, signalled in the AI industry by ChatGPT reaching an estimated 100 million users within two months of its November 2022 launch. Revenue can climb steeply once that point is passed, as Mistral AI's 20-fold rise to more than US$400 million of annualised revenue in the 12-month period to February 2026 shows, although usable technology does not guarantee paying customers. Inflection AI's Pi chatbot drew around a million daily users but never found an effective business model in a market led by ChatGPT, and its US$4 billion valuation gave way in 2024 to a US$650 million licensing deal under which Microsoft hired most of its staff.

For quantum, the arithmetic of AI's success is encouraging but unforgiving. Based on our comparison, investors pay almost US$200 for each dollar of revenue (200x multiple) across today's most valued quantum companies, against an average multiple of about 28x amongst the AI companies. Hence, if a quantum company fell to that AI multiple, it would need to grow its sales approximately sevenfold just to hold its current value, and more still if the multiple fell further (Figure 3). Meanwhile, growing the company’s sales more than 10-fold would lift its valuation by almost 1.5 times, despite the falling multiple. Quantum does not need to reach Anthropic's scale for a falling multiple to accompany a rising valuation, though the whole path depends on a technological and commercial inflection point of its own.

Why Quantum's Inflection Point Still Lies Ahead

That inflection requirement marks the deepest divergence, since AI proved its technical viability before its revenue surge, and quantum computing has yet to do so. Quantum’s inflection point would be demonstrable advantage on commercially relevant problems, reliably beating the best conventional methods on speed, cost, or quality across a customer's workflow. IBM and partners launched an open Quantum Advantage Tracker in November 2025 so classical specialists can test such claims.

Many applications also need fault tolerance, which rests on logical qubits (protected units of quantum information built from many error-prone physical qubits). A September 2026 framework from Microsoft and Qolab places the low end of useful quantum computing above 100 high-quality logical qubits, with large-scale chemistry and cryptanalysis needing over 1,000, a similar analysis conducted by Firgun Ventures in our Insights Series piece, ‘How Many Qubits Does a Quantum Computer Require?’. Problems will become viable at different stages, so the opportunity is likely to arrive one useful capability at a time. Quantum valuations therefore carry technical uncertainty that had largely been mitigated in the AI industry.

The commercial turning point follows when customers move from experimentation to repeat purchasing, visible in renewed contracts, wider deployments, and usage tied to an identifiable budget. Being technically ahead opens the door, but the company that profits is often the one that makes its product easiest to adopt and pay for. That moment will also arrive unevenly across quantum domains, since quantum sensors and secure communications do not need to wait on quantum computers to become fully error-corrected.

Turning Quantum's Priced-In Future Into Revenue

Quantum also departs from AI in how it reached public markets. AI's leaders have mostly stayed private while many public investors first met quantum through a special purpose acquisition company (SPAC), a listed shell that merges with a private business. IonQ, Rigetti, and D-Wave took this route in 2021 and 2022, and Infleqtion, Pasqal, IQM, and others followed in 2026, each arriving while most of its commercial scale lay ahead. A negotiated SPAC can organise financing around a future business before a large customer base exists, whereas a conventional IPO puts operating history at the centre of a bookbuilding process, and Quantinuum's conventional listing in June 2026 shows the traditional route is now open to the sector too.

The gap between quantum's expected future and AI's realised scale is real, and AI's history gives investors reason to study what could close it, since Anthropic and Databricks grew more valuable even as their multiples declined. Genuine quantum advantage would strengthen the technical foundation and repeat customer spending would convert it into growth, although sector progress will not reward every company, or every entry price, equally. High revenue multiples do not, by themselves, prove overvaluation, as they aim to quantify how much future success is worth. A multiple records what investors expect, and the customers who keep coming back are what will prove them right.