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Every major technology cycle creates its own language of excitement. In the late 1990s, it was the internet. Today, it is artificial intelligence. Markets move quickly when investors, entrepreneurs and executives become convinced that a new technological shift will redefine business itself. That belief is often correct. The danger emerges when enthusiasm begins to replace disciplined business judgment.

The current acquisition environment surrounding artificial intelligence increasingly reflects this tension. Companies are being valued, marketed and pursued primarily because they position themselves as “AI businesses.” Yet the label alone reveals very little about the actual strength of a company, the sustainability of its operations or the commercial viability of its products.

Â鶹Éçs entering acquisition discussions during the AI era should therefore exercise a level of caution that history has repeatedly shown to be necessary during periods of technological enthusiasm.

In conventional acquisition practice, businesses are generally acquired through two broad approaches. One is share acquisition, where the buyer acquires ownership and control of the business entity itself as an ongoing concern. The other is business or asset acquisition, where the buyer acquires a specific product, technology, intellectual property asset, platform or operational capability without necessarily purchasing the entire company structure.

What AI actually is (and isn’t)

One of the most important misconceptions emerging in today’s market is the tendency to think of AI as a standalone product category. In reality, AI is rarely valuable in isolation. Most commercially successful applications of AI emerge when it enhances an already established product, operational workflow or customer experience. AI increasingly functions as an enabling capability rather than an independent commercial destination.

A software platform becomes more competitive because AI improves automation and personalization. A logistics company becomes more efficient because AI optimizes routing and forecasting. A healthcare product gains value because AI accelerates diagnostics or data analysis. In each case, the underlying business or product already possesses functional purpose, operational structure and market relevance before AI enhancement occurs.

This distinction is critical because it changes how acquisitions should be evaluated.

Evaluate the business before the AI

An entrepreneur considering a share acquisition during the AI era should first examine the target organization as a functioning business independent of its AI narrative. The core questions remain remarkably traditional. Does the company possess sound operational processes? Is its governance stable? Does it solve a real market problem? Are its revenues sustainable? Does management execute effectively? Is there evidence of customer retention, operational discipline and scalable practice?

Only after these business fundamentals are validated should AI become part of the strategic evaluation process. At that stage, AI should be examined not as a fashionable label but as a practical factor that may strengthen or weaken the company’s long-term competitiveness. The analysis should focus on whether AI integration genuinely improves efficiency, decision-making, customer value, scalability or market differentiation.

This sequence matters because history repeatedly demonstrates what happens when technological identity overtakes commercial reality.

The dot-com lesson

The dot-com boom of the late 1990s offers one of the clearest examples. As internet adoption accelerated, enormous amounts of capital flowed into companies whose primary distinction was simply having an online presence. Investors often assumed that a website alone represented a transformative business model.

Between 1995 and early 2000, the Nasdaq Composite index rose from roughly 1,000 points to more than 5,000 points, driven heavily by internet-related speculation. By 2002, after the collapse of the bubble, the index had lost nearly 78% of its value. Trillions of dollars in market capitalization disappeared, and many heavily funded startups vanished entirely.

The underlying lesson was not that the internet lacked value. On the contrary, the internet ultimately transformed the global economy. The real lesson was that technological presence alone does not create a functioning business. A domain name, a website and investor excitement could not compensate for the absence of sustainable operations, commercial discipline or coherent business practice.

The businesses that survived the dot-com collapse were generally those with real operational foundations. They possessed functioning processes, viable revenue models, customer demand and practical execution capability. Their digital presence extended and enhanced established business logic rather than replacing it.

AI as an opportunity — and a threat

Many organizations currently market themselves through AI branding even when their operational maturity remains uncertain. In some cases, AI integration may be superficial, commercially untested or excessively dependent on third-party infrastructure. In others, the cost of maintaining AI systems may exceed the economic value they create. Regulatory exposure, data governance concerns, cybersecurity risks, model reliability issues and rapid technological obsolescence further complicate the picture.

For entrepreneurs pursuing share acquisitions, AI should therefore be treated not only as an opportunity factor but also as a threat factor. The existence of AI integration does not automatically increase business quality. In some situations, it may introduce operational fragility, compliance uncertainty or inflated valuation expectations that weaken the acquisition rationale.

When a company acquires a specific product, the first step should be evaluation of the core product itself according to established product development principles. Is the product functional? Does it address a meaningful market need? Is it reliable, scalable, maintainable and commercially viable? Does it possess genuine customer adoption or strategic utility?

Only after the product demonstrates intrinsic value should AI enhancement become part of the assessment process. The relevant question is not whether the product contains AI features, but whether AI integration materially improves performance, automation, adaptability, customer experience or competitive differentiation in a sustainable manner.

This perspective becomes increasingly important because AI capabilities are rapidly becoming normalized across industries.

Where the real competitive advantage will come from

As that normalization occurs, the true source of competitive advantage will likely shift away from simply possessing AI functionality and toward the quality of business execution surrounding it.

Organizations that combine operational discipline, sound governance, effective product development and strategically integrated AI capabilities are far more likely to create durable value than organizations built primarily around technological marketing narratives.

Â鶹Éçs and executives, therefore, face an important responsibility during this phase of technological transition. Excitement surrounding AI should not eliminate the discipline traditionally required in acquisition analysis.