What Becomes More Valuable When Intelligence Becomes Cheap?

On October 22, London Stock Exchange Group announced an agreement to acquire Octus, a specialized credit intelligence and data provider, for approximately $3.54 billion. The transaction comes at an interesting moment for the financial information industry.

AI is changing how people research companies, analyze markets, interpret documents, and make decisions. Work that once required expensive information platforms and hours of specialist analysis can increasingly be performed with accessible AI tools. For businesses whose value has traditionally depended on providing information, that creates an obvious challenge. If customers can obtain answers faster and more cheaply, what are they still willing to pay for?

LSEG’s acquisition offers one possible answer. Octus possesses proprietary information, specialized expertise, and established workflows serving credit markets, including areas where high-quality information is difficult to obtain. Those assets become particularly interesting in a world where the tools for interpreting information are becoming widely available.

When intelligence becomes easier to produce, the things that make intelligence valuable become more important.

The changing economics of knowing things

For much of the modern economy, specialized knowledge has been a source of competitive advantage. Organizations built businesses around acquiring information, developing expertise, analyzing complex subjects, and delivering insights that customers could not easily produce themselves.

The barriers were significant. Information was difficult to find. Expertise took years to develop. Analysis required specialized resources. Distribution was expensive.

AI is reducing some of those barriers. A small company can now access analytical capabilities that previously required substantial teams and infrastructure. Individuals can synthesize information across large volumes of material. Specialized knowledge is becoming easier to access and apply. This changes the economics of many businesses. But it changes where the value of expertise and information resides.

The act of producing an answer may become less differentiated. The ability to supply reliable inputs, understand context, exercise judgment, and embed an answer into a consequential decision may become more valuable.

• A model can analyze a document. That does not mean it has access to every relevant document.
• It can summarize a market. That does not mean the available information accurately represents the market.
• It can recommend an action. That does not mean the organization has the authority, capabilities, or relationships required to execute it.

Scarcity is changing

Every major technological shift changes what is abundant and what remains scarce. The internet dramatically reduced the cost of distributing information. That created extraordinary opportunities for businesses built around search, aggregation, platforms, and digital access. Cloud computing made infrastructure easier to acquire, changing the economics of software development and enabling new business models.

AI is producing a similar shift in the availability of cognitive capabilities. But abundance in one part of a value chain often increases the importance of constraints elsewhere.

• If virtually anyone can build a basic application, the ability to reach customers becomes more valuable.
• If analysis becomes inexpensive, access to differentiated data becomes more valuable.
• If content can be produced at scale, trust, credibility, and genuine audience relationships become harder to replicate.
• If competitors can develop similar features quickly, deep integration into customer workflows becomes a stronger source of retention.

The strategic opportunity lies in understanding how these relationships are changing. This is what makes the LSEG–Octus transaction noteworthy. LSEG is acquiring specialized assets within markets where obtaining and validating information can be difficult.

According to Permira, Octus more than tripled its annual recurring revenue during roughly four years of ownership while developing its credit intelligence and AI capabilities. The transaction illustrates the potential value of combining proprietary information with technology, established customer relationships, and commercial distribution.

It does not prove that proprietary data alone guarantees a durable advantage. Data can become outdated, alternative sources can emerge, and customers’ willingness to pay can change. But it points toward a critical distinction: information that can be generated or accessed by everyone is economically different from information that remains difficult to obtain, validate, or replace.

The new competitive advantage may be what you control

This has implications far beyond financial services. Consider an industrial company with decades of operating data and deep knowledge of equipment performance. Historically, that information might have been used primarily to improve its own operations. Combined with modern analytical capabilities, it could potentially support predictive services, performance guarantees, or entirely new commercial offerings.

Or consider a professional services company whose expertise is concentrated in the experience of its people. If the organization can codify portions of that expertise, combine it with unique customer context, and create repeatable workflows, it may be able to commercialize capabilities that previously depended entirely on labor-intensive delivery.

A distributor with longstanding customer relationships may discover that its greatest asset is no longer physical distribution, but access to demand and an understanding of purchasing behavior.

In each case, the underlying asset already exists. What changes is the range of ways it can create value.

Owning an asset is not the same as having an advantage

There is a temptation to treat proprietary data, intellectual property, customer relationships, and specialized expertise as automatic sources of differentiation. They aren’t. An asset creates competitive advantage when it allows an organization to deliver value that customers recognize and competitors cannot easily reproduce.

A large proprietary dataset may have limited commercial value if it is incomplete, inaccessible, or disconnected from meaningful customer needs. An established distribution network may become a liability if customers shift to new channels. Decades of institutional expertise may become less differentiated if competitors can produce comparable outcomes at dramatically lower cost.

What matters is the relationship between the asset, the market, and the customer’s problem. This requires organizations to reconsider their portfolios with a different set of questions:

• What do we possess that has become easier for others to replicate?
• What do we possess that is becoming increasingly difficult to reproduce?
• Which assets could become more valuable when combined with new technology or complementary capabilities?
• Which capabilities that we currently sell as standalone products might be more valuable when embedded into someone else’s workflow?

From information products to decision systems

One of the more consequential opportunities is the movement from providing information to helping customers make and execute decisions. For years, businesses have sold research, dashboards, reports, databases, and analytical tools. Customers then translated those outputs into action. AI creates opportunities to connect more of that process.

These shifts create opportunities for greater customer value, but they also change the requirements of the business. Delivering a recommendation carries different expectations than providing a dataset. Integrating into a customer’s operations requires different capabilities than selling access to information. And supporting consequential decisions introduces questions about accuracy, accountability, trust, and the boundaries between human and automated judgment.

The commercial opportunity is significant precisely because it involves more than adding AI features to an existing product. It may require redesigning the business around a different source of value.

Reconsider what business you’re actually in

The organizations best positioned to benefit from this shift may be those that understand most clearly how AI changes the economics of their markets. That means looking beyond the immediate productivity gains. It means examining the value chain to understand which activities are becoming commoditized, where new bottlenecks are appearing, and which assets will become essential to delivering a differentiated outcome.

For some companies, the answer will be developing new products. For others, it will mean acquiring specialized capabilities, restructuring partnerships, repositioning existing offerings, or moving into adjacent markets. And for some, it will mean recognizing that a previously defensible business model is becoming less valuable and acting before the market makes that decision for them.

The LSEG–Octus acquisition reflects one company’s strategic response to these changing conditions. Whether the transaction ultimately delivers its expected value remains to be seen. But the broader question applies to virtually every industry. As intelligence becomes easier to access, what will your customers value enough to pay for?

When something becomes abundant, look for what becomes scarce. That’s often where the next market is taking shape.

At Eudai, we help organizations identify emerging sources of competitive advantage, uncover opportunities within existing assets, and develop the strategies and capabilities required to turn them into commercial value.

Sources

• LSEG, LSEG to Acquire Octus, October 22, 2026.
• Permira, Permira Agrees Sale of Octus to LSEG, October 22, 2026.
• Reuters, LSEG to Buy Octus in $3.5 Billion Deal, October 22, 2026.