Beyond Business Adjacency: The Decline of Expertise Moats and the Rise of Organizational DNA

🧭 Dojo Compass

Module: Strategy, Markets and Competitive Advantage

Curriculum Area: Strategy and Business Models

Learning Format: Article

Traditional business strategy has generally placed considerable importance on adjacency. Companies have tended to expand into markets and activities that are relatively close to their existing businesses, capabilities and areas of expertise. Moving into unfamiliar sectors was often expensive, difficult and risky because acquiring the necessary knowledge and operational capabilities required substantial investment.

Artificial intelligence is changing this equation. As AI makes expertise more accessible, companies can increasingly investigate and pursue opportunities in sectors that were previously considered too distant from their existing operations.

However, this raises a more fundamental strategic question: if expertise and business adjacency are becoming less restrictive, what determines whether a company can successfully compete in unfamiliar markets?

This article explores the declining importance of traditional expertise moats, the growing strategic possibilities associated with non-adjacent business expansion, and the increasing importance of organizational DNA, adaptability and the ability to create competitive advantages by combining different business models and perspectives.

🎯 Key Challenge

Business adjacency has traditionally played an important role in corporate strategy.

When considering expansion, companies have generally preferred opportunities that build upon their existing products, services, customers, technologies, distribution channels or operational capabilities.

There are sound reasons for this preference.

A company entering an adjacent market can often leverage existing infrastructure, relationships, knowledge and expertise. It may already understand the customers, competitive environment and commercial dynamics. Consequently, the cost and risk of expansion are generally more manageable.

Moving into a non-adjacent business, however, has historically presented much greater challenges.

Consider a manufacturing company contemplating entry into financial services, a software business considering agricultural operations, or an agricultural company exploring opportunities in advanced data analytics.

Although these opportunities might be commercially attractive, the companies would generally lack important industry-specific knowledge and capabilities.

They might need to recruit specialist personnel, acquire businesses, develop new technologies, establish relationships and invest considerable resources simply to understand how the new industry operates.

These requirements have created what might be described as expertise moats: barriers to entry arising from the difficulty and expense of acquiring the knowledge and capabilities necessary to operate successfully in a particular business.

As a result, companies have frequently restricted their strategic ambitions to activities that are relatively close to their existing operations.

However, AI is beginning to change the economics of this constraint.

Companies can now use AI to investigate unfamiliar industries, understand commercial models, research regulatory requirements, analyze competitors, develop technical knowledge and explore operational approaches that would previously have required considerable time and specialist resources.

Expertise that was once expensive and difficult to acquire is becoming increasingly accessible.

This does not mean that all barriers to entering unfamiliar businesses have disappeared. Industry experience, relationships, regulatory permissions, physical infrastructure and execution capabilities can remain substantial obstacles.

Nevertheless, the cost of understanding and exploring unfamiliar business opportunities is declining.

This creates a fundamental strategic challenge.

If companies are increasingly able to overcome expertise moats and consider opportunities with decreasing degrees of business adjacency, what determines whether they can actually compete successfully in those unfamiliar markets?

Is it still primarily what they know, or is it increasingly how they operate?

🥋 Dojo Solution

The Dojo solution is to recognize that as expertise becomes more accessible, the relative importance of organizational DNA, operational adaptability and the ability to combine different business models and capabilities increases.

Companies should increasingly evaluate strategic opportunities not simply by reference to how close they are to their existing businesses, but by considering whether their underlying organizational characteristics enable them to compete effectively in those opportunities.

1. Recognize the declining importance of expertise moats

Expertise has historically been an important source of competitive advantage.

Companies with specialist knowledge, experienced personnel and established industry capabilities have enjoyed advantages over potential competitors who would need to invest considerable resources to develop equivalent expertise.

AI is changing this relationship.

A company can now use AI to:

Investigate unfamiliar industries and commercial environments.
Understand products, technologies and operational processes.
Research regulatory and competitive conditions.
Develop preliminary technical and commercial knowledge.
Explore alternative business and revenue models.
Identify specialist capabilities that need to be acquired or accessed.
Evaluate potential partnerships and acquisition opportunities.

This can substantially reduce the initial knowledge disadvantage faced by a company entering an unfamiliar sector.

Importantly, acquiring information and understanding an industry are not the same as possessing the practical experience necessary to operate successfully within it.

AI does not automatically provide customer relationships, regulatory approvals, manufacturing infrastructure, tacit operational knowledge or industry credibility.

Nevertheless, it can help companies identify precisely which of these capabilities are required and how they might be developed, acquired or accessed.

The strategic implication is that lack of existing expertise should increasingly be regarded as a challenge to investigate and potentially overcome, rather than an automatic reason to exclude an opportunity.

2. Rethink business adjacency as a strategic constraint

Traditional strategy has generally emphasized expansion into core and adjacent activities.

A company might first expand its existing product range, then enter related markets, and eventually consider more distant opportunities.

This progression reflects the practical difficulties of acquiring unfamiliar expertise and capabilities.

However, as these difficulties decline, companies can increasingly explore opportunities across a much broader range of business activities.

It is useful to think of adjacency as a continuum.

For example:

Degree of adjacency	Description	Illustrative opportunity
Core	Existing business activities	Expanding an existing product range
High adjacency	Closely related activities	Offering complementary services to existing customers
Moderate adjacency	Different activities using several existing capabilities	Applying existing technology to a new industry
Low adjacency	Unfamiliar markets with limited existing operational overlap	Entering an unfamiliar service sector
Non-adjacent	Businesses with substantially different industry structures and operating models	Applying an established financial services model to an unrelated industry

These categories are illustrative rather than absolute. A business can be technologically adjacent but commercially distant, or commercially adjacent but operationally very different.

The important point is that adjacency should no longer be treated as a rigid boundary around strategic possibilities.

Companies should instead investigate how their existing resources and capabilities might be applied in different contexts, including opportunities that initially appear unrelated to their core activities.

3. Recognize the increasing importance of organizational DNA

If expertise becomes easier to acquire, what distinguishes companies that can successfully enter and compete in unfamiliar markets?

An increasingly important factor is organizational DNA.

Organizational DNA describes the underlying characteristics that determine how a company operates, makes decisions, allocates resources, responds to opportunities and manages change.

It goes beyond the company’s stated values or corporate culture. It reflects the practical operating characteristics that influence what the organization can actually accomplish.

Consider several important dimensions.

Strategic curiosity: Does management actively investigate unfamiliar opportunities, or does it tend to concentrate exclusively on existing markets and business activities?

Decision-making flexibility: Can the company make decisions quickly when circumstances change, or are decisions constrained by excessive approval processes and established organizational structures?

Resource adaptability: Can the company redeploy financial, human and technological resources to pursue new opportunities?

Experimentation: Is the organization prepared to test unfamiliar business models, learn from unsuccessful experiments and modify its approach?

Operational flexibility: Can existing processes and structures be adapted to accommodate different types of business activities?

Risk management: Can the company distinguish between manageable uncertainty and unacceptable risk, rather than treating all unfamiliar activities as inherently dangerous?

Learning capability: Can the organization rapidly absorb new knowledge and translate it into operational improvements?

Management integration: Can the company bring together people with different backgrounds, disciplines and perspectives to develop new solutions?

These characteristics can be more important than the company’s existing industry expertise when evaluating its ability to enter unfamiliar markets.

Two companies might have access to the same AI models, specialist consultants and market information, but their ability to convert those resources into commercial results could be very different.

One might be constrained by rigid structures, slow decision-making and an unwillingness to experiment. The other might be capable of assembling new teams, testing alternative business models and rapidly adjusting its operations.

The second company may therefore be better positioned to exploit opportunities beyond its traditional areas of expertise.

4. Understand the strategic value of non-adjacent business model collisions

Perhaps the most interesting opportunity associated with decreasing business adjacency is the possibility of creating new competitive advantages by combining business models and operating approaches from different industries.

Companies often assume that successful practices in their own industry provide the most relevant examples for improving their businesses.

However, this can create intellectual and operational limitations.

If everyone in an industry approaches customers, develops products, manages operations and generates revenue in broadly similar ways, opportunities for differentiation may become increasingly restricted.

Looking outside the industry can reveal entirely different approaches.

Consider some illustrative examples:

Applying subscription-based revenue models to industries traditionally dependent on individual product sales.
Introducing software-platform economics into traditionally fragmented service industries.
Applying predictive analytics and automated monitoring to physical asset management.
Introducing financial risk-sharing arrangements into industries traditionally based on straightforward product sales.
Applying logistics and network optimization techniques from one industry to another.
Using customer relationship models from digital businesses to improve traditionally transactional industries.

In each case, the opportunity arises from transferring an approach from one business environment into another.

The result need not be disruptive in the conventional sense of replacing an incumbent technology or destroying an established business model.

It may instead represent a positive collision of different business perspectives, resulting in better products, improved services, more efficient operations or entirely new commercial opportunities.

We can describe this as cross-adjacency innovation.

Cross-adjacency innovation occurs when companies combine business models, capabilities, technologies or operating approaches originating in different sectors to create new forms of commercial value.

AI can accelerate this process by helping companies identify practices in unfamiliar industries, understand how they work and evaluate whether they can be adapted to their own business environments.

The competitive advantage comes from recognizing connections that companies operating exclusively within their own industries might overlook.

5. Develop the ability to convert non-adjacent ideas into competitive operations

Identifying an interesting business model from another industry is only the beginning.

The real challenge is adapting it to a different commercial environment and making it work.

A business model that is successful in one industry may not be directly transferable to another.

Customer expectations, economics, regulations, infrastructure, competitive dynamics and operational requirements may be substantially different.

Consequently, companies need the ability to translate ideas rather than simply copy them.

This requires several capabilities.

Contextual adaptation: Understanding which elements of an external business model are relevant and which need to be modified.

Operational integration: Incorporating the new approach into the company’s existing systems, processes and organizational structures.

Commercial validation: Testing whether customers value the proposed approach and whether it produces attractive economics.

Capability development: Identifying the additional expertise, technology and resources required to implement the model successfully.

Organizational learning: Refining the approach based on practical experience and changing circumstances.

AI can assist with each of these activities, but management must ensure that the resulting business model is commercially viable and operationally sustainable.

The objective is not to become a collection of unrelated business activities.

It is to develop the organizational ability to take ideas from different environments, adapt them and convert them into competitive business practices.

6. Build operational structures that support non-adjacent expansion

Organizational DNA is important, but it must be supported by appropriate operational structures.

A company may have an entrepreneurial culture and an appetite for experimentation but still struggle to pursue unfamiliar opportunities if its organizational systems are designed exclusively around existing operations.

Companies seeking to expand beyond traditional adjacency should consider several structural characteristics.

Modular operations: Organizing activities so that new business initiatives can be developed without unnecessarily disrupting existing operations.

Flexible resource allocation: Allowing management to redirect financial, human and technological resources as opportunities emerge.

Cross-functional teams: Bringing together different disciplines and expertise to investigate and implement unfamiliar business activities.

External capability access: Developing relationships with specialist providers, technology partners, universities and other organizations that can supply expertise the company does not possess.

Decentralized experimentation: Giving appropriately empowered teams the ability to test new ideas within established financial, legal and risk-management parameters.

Scalable systems: Developing technology and management infrastructure that can accommodate new business activities without requiring the company to rebuild its operating model each time it expands.

Appropriate governance: Establishing clear accountability and oversight without creating unnecessary bureaucratic obstacles to experimentation.

The objective is to create an organization that can pursue new opportunities without requiring every initiative to be built from scratch.

7. Reconsider the sources of competitive advantage

If AI makes expertise more accessible and reduces some of the traditional barriers to entering unfamiliar industries, companies need to reconsider the sources of their competitive advantage.

Expertise will remain important, particularly where it involves tacit knowledge, accumulated experience, specialist judgment or regulated professional qualifications.

However, possessing knowledge may become less differentiating when competitors can access similar information and analytical capabilities.

Other characteristics may therefore become relatively more important.

These include:

The ability to identify opportunities before competitors.
The speed at which an organization can mobilize resources.
The quality of its decision-making processes.
Its ability to adapt business models to unfamiliar environments.
The strength of its customer and partner relationships.
Its operational flexibility and execution capabilities.
Its capacity to combine different technologies, expertise and commercial approaches.
Its organizational ability to learn and continuously improve.

In other words, competitive advantage may increasingly depend on how effectively a company can organize and deploy accessible knowledge, rather than simply how much knowledge it possesses.

This does not mean that all companies will become equally capable of entering all industries. Capital requirements, regulatory barriers, physical assets, customer trust and execution complexity will continue to create important differences.

Rather, it means that companies should increasingly examine whether their organizational characteristics allow them to overcome barriers that previously appeared insurmountable.

8. Develop a strategy for exploring non-adjacent opportunities

Companies should not interpret declining expertise moats as an invitation to pursue every unfamiliar business opportunity.

Strategic expansion still requires discipline.

A useful approach is to evaluate non-adjacent opportunities through four complementary questions.

First: What is the opportunity?

Is there a genuine commercial opportunity in the target market? What customer needs, competitive weaknesses or emerging developments make the opportunity attractive?

Second: What can we bring?

Which of our existing assets, capabilities, relationships, technologies and organizational characteristics could create an advantage in this market?

Third: What must we acquire or develop?

What additional expertise, resources, infrastructure, relationships or regulatory permissions would be required? Could these be accessed through AI, partnerships, recruitment, acquisitions or other arrangements?

Fourth: Can we operate differently and better?

Can we introduce a different business model, operating approach or combination of capabilities that creates an advantage over existing competitors?

AI can help investigate each question, develop alternative scenarios and identify the assumptions that require testing.

Management can then prioritize opportunities based on their commercial attractiveness, strategic fit, resource requirements and practical feasibility.

The objective is to expand the company’s strategic horizons without losing sight of the importance of disciplined execution.

🏗️ Putting It into Practice

A company can begin exploring non-adjacent opportunities through a structured AI-assisted exercise.

The following eight steps provide a practical approach.

Step 1: Map the company’s organizational DNA

Ask management to identify the characteristics that fundamentally define how the company operates.

Consider:

How quickly does the company make decisions?
How does it allocate resources?
How readily does it experiment?
How does it manage risk?
How effectively does it integrate new technologies?
How adaptable are its operational processes?
How does it develop and retain relationships?
What distinguishes its approach from competitors?

The objective is to understand the company’s actual operating characteristics rather than simply its formal organizational structure.

Step 2: Identify existing assets and transferable capabilities

Prepare an inventory of the company’s tangible and intangible resources.

Include technology, intellectual property, customer relationships, distribution channels, data, infrastructure, financial resources, management capabilities and specialist knowledge.

Ask AI to identify capabilities that might have applications beyond the company’s existing industry.

Step 3: Explore non-adjacent industries

Select several industries that are not traditionally associated with the company’s activities.

Ask AI to investigate their commercial structures, customer requirements, revenue models, operational processes and competitive environments.

Do not initially exclude opportunities simply because the company lacks direct industry experience.

Step 4: Identify cross-adjacency opportunities

Ask AI to identify business models and operating practices in those industries that might be adapted to the company’s existing activities.

Also ask whether the company’s existing capabilities could be used to create an entirely new business offering in those sectors.

Look particularly for combinations of resources and business models that could produce distinctive commercial advantages.

Step 5: Evaluate organizational compatibility

Assess whether the company’s DNA and operational structures would support entry into each potential market.

Identify organizational strengths that could facilitate expansion and weaknesses that would need to be addressed.

Distinguish between capabilities that can be acquired relatively easily and those requiring substantial organizational development.

Step 6: Identify the capability gaps

For the most promising opportunities, establish what additional expertise, resources and infrastructure would be required.

Consider whether these requirements could be met through AI, partnerships, acquisitions, recruitment, outsourcing or internal development.

Prepare a preliminary assessment of the cost, time and complexity involved.

Step 7: Test the most promising opportunities

Select one or two opportunities and design relatively inexpensive experiments to test their commercial viability.

These might include customer interviews, prototype development, pilot projects, partnership discussions or preliminary market testing.

Use AI to help analyze the results and refine the proposed business model.

Step 8: Incorporate the learning into strategy

Evaluate the results and determine whether the opportunities justify further investment.

Document what has been learned about the company’s ability to operate beyond its traditional areas of expertise.

Repeat the exercise periodically, gradually developing a broader understanding of the company’s non-adjacent strategic possibilities.

📌 Key Takeaways

Traditional business strategy has generally favored adjacent opportunities because acquiring unfamiliar expertise and capabilities was expensive and difficult.
AI is reducing the cost and time required to investigate unfamiliar industries and develop new knowledge, weakening some traditional expertise moats.
Business adjacency should increasingly be viewed as a continuum rather than a rigid boundary around strategic opportunities.
As expertise becomes more accessible, organizational DNA, adaptability and operational structures become increasingly important determinants of competitive success.
Organizational DNA influences how effectively a company identifies opportunities, makes decisions, allocates resources, manages risk and responds to change.
Cross-adjacency innovation occurs when business models, capabilities and perspectives from different industries are combined to create new commercial value.
The ability to translate and adapt external business models is more important than simply copying practices from other industries.
Companies need flexible operational structures that allow them to experiment, mobilize resources and enter unfamiliar markets without unnecessarily disrupting existing operations.
AI can help identify and evaluate non-adjacent opportunities, but commercial validation, execution and management accountability remain essential.
The emerging competitive advantage may increasingly lie in a company’s ability to convert accessible knowledge and unfamiliar ideas into distinctive and effective business operations.

🌿 Reflection

For much of business history, companies have been constrained by the boundaries of their existing expertise.

They have generally expanded into businesses they understand, using capabilities they already possess and operating models familiar to their industries.

AI is beginning to change this equation.

As expertise becomes increasingly accessible, companies may find that opportunities previously considered too distant, complicated or unfamiliar are now realistically within their reach.

But access to knowledge does not automatically create competitive advantage.

If competitors can access the same information, technologies and expertise, what makes one company more successful than another?

Perhaps the answer increasingly lies in organizational DNA: the ability to recognize possibilities, bring different perspectives together, adapt established ways of operating and translate unfamiliar ideas into commercial results.

Consider whether your company is organized primarily to protect and optimize what it already does, or whether it is also capable of discovering and exploiting what it has never done before.

The next generation of competitive advantage may belong to companies that are not simply better at doing familiar things, but better at making unfamiliar things work.

⚔️ Dojo Mission

The Non-Adjacent Opportunity Challenge

Choose an industry in which your company has no significant existing business activity.

Ask AI to explain the industry’s business models, principal revenue sources, competitive dynamics and operational requirements.
Identify three business models or operating practices from that industry that could potentially be applied to your company’s existing business.
Ask AI to identify five ways your company’s existing assets, capabilities and organizational DNA could create value in that unfamiliar industry.
Identify the expertise, resources and operational changes required to pursue the most interesting opportunity.
Develop a small experiment to test whether the opportunity is commercially viable.

Finally, ask yourself:

If we were not constrained by what we already know how to do, what new business opportunities might we be capable of pursuing?