Speculation, sentiment, and the search for intrinsic worth in an AI-driven market.

Introduction: The New Gold Rush

The surge in artificial intelligence (AI) company valuations has captured the financial world’s imagination. From chipmakers and model developers to data infrastructure startups, the market seems to be rewarding anything branded with “AI” at staggering multiples.
Some firms, barely generating revenue, now boast valuations once reserved for global industrial giants.

Yet beneath this euphoria lies a growing unease: are these companies truly worth what investors claim they are? Or are we witnessing the inflation of yet another speculative bubble — one where narratives, not numbers, define value?

The deeper question is philosophical as much as financial: what is the real value of a company?

1. Market Value vs. Real Value

In capital markets, two forms of valuation coexist uneasily: market value and
intrinsic (or real) value.

• Market value reflects what investors are willing to pay for a stock today. It’s driven by supply, demand, and collective belief — often influenced by momentum, sentiment, and hope.
• Intrinsic value, by contrast, represents what a company is actually worth based on its ability to generate
  future cash flows. It’s rooted in fundamentals: revenues, costs, capital efficiency, and risk.

The classic way to estimate intrinsic value is the Discounted Cash Flow (DCF) method — summing up the expected cash flows a business will produce over time, discounted back to today’s terms.

This approach may not generate headlines, but it anchors valuation in measurable reality — a sharp contrast to the market frenzy that currently surrounds AI.

2. The Speculative Disconnect

AI companies today are being priced on potential rather than performance. The prevailing assumption is that AI will reshape entire economies, upend every industry, and produce profit margins unlike anything before.

But most of these companies are still in their investment phase:

• They burn enormous amounts of cash on computing power, data acquisition, and model training.
• Monetization paths remain uncertain or unproven.
• Competitive pressures are escalating, not easing.

The result is a wide gulf between market expectations and financial substance. History tells us such gaps rarely endure. From the dot-com bubble of the late 1990s to the crypto and electric vehicle manias of the 2020s, enthusiasm always outpaced earnings
— until reality reasserted itself.

When speculation replaces evidence, valuation ceases to measure value and becomes a reflection of collective belief.

3. What Actually Determines a Company’s True Worth

A company’s real or intrinsic value rests on a few enduring pillars. Regardless of sector or technology, these fundamentals never change:

1. Earnings Power: Sustainable profitability over time. Real value is created when earnings are repeatable and resilient.
2. Free Cash Flow (FCF): The lifeblood of valuation — cash available after expenses and reinvestment needs. Accounting profits mean little without cash backing them.
3. Return on Invested Capital (ROIC): A key test of managerial efficiency. When ROIC consistently exceeds the cost of capital, true value is being created.
4. Competitive Advantage (Moat): Whether the firm possesses durable, defensible strengths — proprietary technology, network effects, or data — that safeguard future profits.
5. Balance Sheet Strength: Solid capital structure and liquidity to weather downturns.
6. Management Discipline: Leadership that prioritises long-term value creation over short-term hype.

When these fundamentals are absent, valuation becomes little more than speculation, no matter how revolutionary the underlying technology may seem.

4. The AI Valuation Paradox

Artificial intelligence sits at the intersection of two powerful forces: transformative potential and extreme uncertainty.

• Transformative Potential: AI promises vast productivity gains, automation breakthroughs, and new forms of intelligence-driven decision-making. Its economic impact could rival the industrial revolution.
• Extreme Uncertainty: The technology is still evolving. Business models remain fluid. Regulation looms. Energy demands are surging. And competition is fierce — from cloud giants to open-source innovators.

This combination fuels what we might call valuation asymmetry: investors extrapolate massive potential but heavily discount the risks and unknowns.

A startup with limited revenues may be priced at billions simply for “owning a large language model.” A chipmaker’s valuation may embed assumptions of infinite AI demand.

But technological revolutions do not always translate into investor profits. The railway boom, the early automobile era, and the first wave of internet companies all created immense technological progress — yet most early investors lost money.

Innovation drives progress. Execution drives value.

5. Why Markets Lose Perspective

Even professional investors can succumb to speculative momentum. Several forces distort rational valuation:

• Fear of Missing Out (FOMO): No one wants to be the analyst or fund manager who missed “the next Nvidia.”
• Narrative Bias: Humans are wired to believe compelling stories more than dry numbers. “AI will change everything” becomes an investment thesis in itself.
• Abundant Capital: Years of low interest rates encouraged risk-taking and made speculative bets easier to justify.
• Benchmark Pressures: Institutional investors chase what others buy, amplifying trends.
• Limited Historical Anchors: With few precedents for monetizing AI at scale, markets over-rely on imagination.

As each round of optimism feeds the next, valuations detach further from fundamentals — until the illusion breaks.

6. The Reckoning: When the Weighing Machine Returns

Benjamin Graham’s timeless observation remains the market’s ultimate truth:

“In the short run, the market is a voting machine. In the long run, it is a weighing machine.”

Right now, AI valuations are in the voting phase — a popularity contest based on belief and emotion. The
weighing phase will arrive when investors start asking hard questions about profitability, scalability, and return on capital.

That reckoning may not spell disaster for the entire AI sector — genuine winners will emerge — but it will likely separate
visionary firms from valueless speculation.

History’s lesson is clear: markets eventually rediscover gravity.

7. Real Value Endures

So, what is the real value of a company?

It’s the sum of its expected future cash flows, adjusted for risk — no more, no less.

It’s the worth of what remains when hype fades and the market’s illusions dissolve.

The real value of a company is grounded in what it does, not what it
promises.

It’s reflected in cash flow, not press releases.

It’s built over years, not announced in quarters.

Artificial intelligence will indeed reshape industries, perhaps even society itself. But only those AI companies that translate potential into sustained profitability — with discipline, defensibility, and demonstrable returns — will ultimately justify their
valuations.

Conclusion: The Enduring Test of Reality

Every generation of investors rediscovers the same lesson in a new form. Technology evolves, narratives shift, and markets change — but the essence of value remains constant.

When excitement exceeds evidence, bubbles form. When expectations outrun earnings, corrections follow. And when sentiment finally yields to substance, the true worth of a company — its
intrinsic value — emerges once more.

AI is not a bubble. But some AI valuations are. The difference lies not in the brilliance of the technology, but in the realism of the pricing.

In the end, the market always returns to its central principle:

Value is not what people say it is — it’s what it proves to be.