What Happens When Your Customer’s AI Chooses Your Competitor?
Artificial intelligence is becoming a new gatekeeper between businesses and customers. For small and medium-sized enterprises, the challenge is no longer simply being found online, but being recommended.
For two decades, businesses have invested heavily in search-engine optimisation, digital advertising, social media and online reviews. The objective has been straightforward: attract customers, demonstrate value and convert interest into sales.
Artificial intelligence is beginning to change that process.
Increasingly, customers can ask an AI assistant to identify suppliers, compare products, assess value and recommend a purchase. Instead of examining numerous websites, they may receive a shortlist of businesses, accompanied by an explanation of which appears most suitable.
The customer may never encounter the businesses excluded from that shortlist.
For small and medium-sized enterprises (SMEs), this raises an uncomfortable question: What happens when your potential customer’s AI assistant recommends your competitor?
A new gatekeeper emerges
Research by UBS, reported by MarketWatch in October 2026, provides an early indication of how this marketplace might develop.
In an exploratory study involving 12 shopping questions across three American states, researchers examined recommendations generated by major AI shopping assistants. Established retailers, including Walmart and Costco, appeared frequently.
The sample was small and cannot establish how AI recommendations will behave across different industries or customer circumstances. Nevertheless, the findings highlight an emerging competitive issue.
Traditional search engines largely help customers discover businesses. AI assistants increasingly help customers evaluate alternatives and make decisions.
That distinction matters.
A search engine might present ten suppliers. An AI assistant may compare those suppliers and recommend three, potentially identifying one as the preferred choice.
The commercial risk is no longer simply appearing too far down the search results. It is being excluded from the customer’s consideration altogether.
From attracting attention to earning recommendations
Consider a small Australian business supplying specialist commercial equipment.
Traditionally, a prospective customer might search Google, visit several websites, request quotations and compare specifications. The supplier’s challenge was to attract attention and demonstrate its competitive advantages.
Now imagine the customer asking an AI assistant: “Which Australian supplier offers the most reliable equipment for a small manufacturing business, with good technical support and reasonable maintenance costs?”
The assistant might recommend three suppliers and explain their relative strengths.
If your business is absent, its advantages may never be examined.
You might offer superior service, more appropriate equipment or lower whole-of-life costs. But those strengths have limited commercial value if the decision-making system cannot identify them.
Businesses therefore face a new challenge: becoming discoverable and understandable not only to people, but also to the technologies advising them.
The objective is not merely to appear in an AI-generated answer. It is to provide credible reasons for being recommended.
Will the biggest businesses gain another advantage?
One concern is that AI-mediated purchasing could reinforce the position of established market leaders.
Large retailers typically enjoy stronger brand recognition, extensive product information, substantial review volumes and established online reputations.
These characteristics may make them easier for AI systems to identify and evaluate.
If recommendation systems consistently favour familiar suppliers, smaller competitors could struggle for consideration even when their products or services better meet particular customer needs.
A reinforcing cycle could emerge. Businesses receiving more recommendations attract more customers, generating additional reviews and public information that may support future recommendations.
This remains a potential risk rather than an established outcome.
There is also an opportunity.
AI assistants capable of interpreting precise customer requirements may identify specialist suppliers that conventional advertising and broad search results overlook.
A small manufacturer offering a technically superior niche product could benefit when an AI system evaluates suitability rather than brand familiarity.
The critical issue is whether sufficient reliable information exists for the system to recognise that advantage.
The best business may not be recommended
Business owners often assume that superior products, service and value will eventually prevail.
That assumption becomes less dependable when customers delegate part of their purchasing research to technology.
An AI assistant does not necessarily experience service quality, independently verify every claim or fully understand a supplier’s reliability.
Its assessment depends on available information, the tools it uses and the criteria applied.
A business with excellent customer relationships but limited online evidence may therefore be less visible than a competitor with comprehensive product information, documented performance and independent reviews.
This creates an important distinction between actual competitive advantage and visible competitive advantage.
A business can be commercially excellent yet digitally difficult to evaluate.
For SMEs, the challenge is to close that gap.
Five questions every business owner should ask
The appropriate response is not to abandon established marketing strategies or rush into another expensive digital transformation.
It is to examine how effectively an independent digital adviser can understand and assess the business.
1. Can AI accurately explain what your business does?
Ask several AI assistants to describe your products, services, target customers and competitive strengths.
Are their answers accurate? Are important services missing? Is the business confused with another supplier?
Inaccurate responses may reveal weaknesses in publicly available information.
2. Does your business appear when customers describe their needs?
There is a difference between asking about a named business and asking for supplier recommendations.
Test realistic purchasing questions using different requirements and locations. Repeat the exercise periodically.
Individual responses prove little, but recurring patterns may reveal visibility problems.
3. Can your competitive advantages be verified?
Claims such as “industry-leading service” carry limited weight without supporting evidence.
Relevant certifications, detailed specifications, case studies, transparent service commitments and credible independent reviews provide stronger foundations for assessment.
The objective is verifiable differentiation, not louder promotional language.
4. Is your information accessible and current?
Review product descriptions, service areas, technical documentation, pricing information where appropriate, and website accessibility.
Structured data can help digital systems interpret information, although it does not guarantee inclusion in recommendations.
Outdated or conflicting information creates unnecessary uncertainty.
5. Why might a competitor be recommended instead?
Compare your business with competitors on the factors customers actually value: suitability, reliability, service, availability, price and reputation.
If a competitor communicates its advantages more effectively, that weakness can be addressed.
If the competitor genuinely offers better value, the answer is business improvement, not simply better marketing.
A new competitive discipline
The emergence of AI-mediated purchasing has encouraged interest in generative engine optimisation, or GEO: improving how businesses are discovered, understood and referenced by AI-powered systems.
However, businesses should resist treating GEO as another technical shortcut.
There is no universal formula guaranteeing favourable recommendations across AI platforms.
A more durable strategy is to make the business easier to evaluate accurately through clear information, credible evidence, genuine differentiation and independent validation.
These are extensions of sound business practice.
The difference is that the audience increasingly includes software acting on behalf of prospective customers.
Who controls the customer relationship?
There is a broader strategic concern.
When customers use AI assistants to identify suppliers, compare alternatives and initiate purchases, part of the traditional buyer–seller relationship shifts towards a technology intermediary.
That intermediary may influence which businesses receive attention, which characteristics are compared and how value is presented.
The implications extend beyond retail.
Professional services, tourism, insurance, trades, logistics and business-to-business purchasing could experience similar changes.
A business owner seeking an accountant might ask an AI assistant to recommend suitable firms based on industry experience, services, location and reputation.
Firms excluded from the shortlist may never know an opportunity existed.
This also raises questions about transparency.
How will customers distinguish independent recommendations from sponsored placements? How can businesses correct inaccurate descriptions? What happens when platforms have commercial relationships with recommended suppliers?
These questions will become increasingly important as AI purchasing capabilities develop.
Protect the direct customer relationship
Businesses should not respond by making themselves entirely dependent on another digital intermediary.
AI-mediated purchasing remains an evolving market. Recommendation methods, consumer behaviour and commercial arrangements are still developing.
Experimentation and measurement are preferable to expensive commitments based on limited evidence.
Meanwhile, repeat business, referrals, customer loyalty and direct communication remain valuable competitive assets.
A customer who already knows and trusts your business has less reason to delegate the entire supplier-selection process to an AI assistant.
The strongest position is therefore not to choose between traditional customer relationships and AI visibility, but to develop both.
The next competitive question
The UBS findings do not prove that AI shopping assistants systematically favour large retailers or that SMEs will lose market share.
They do, however, highlight a potentially consequential change in how customers discover and evaluate businesses.
For years, companies have asked: “How do we get customers to find us?”
The emerging question is: “How do we ensure that the technology advising our customers understands why we deserve their business?”
That question deserves attention in boardrooms, management meetings and small-business planning.
The next competitive threat may not come from a cheaper product, a new entrant or an aggressive advertising campaign.
It may come from a customer who asks an AI assistant for advice, receives a convincing recommendation and makes a purchase without ever discovering your business.
Your competitor may not need to win the customer’s attention. They may only need to win the recommendation.
In an AI-mediated marketplace, businesses must ensure their competitive strengths are not merely real, but recognisable.
Because no business can win a comparison it never gets invited to join.
Reference
MarketWatch (2026, 5 October). AI chatbots recommend shopping at Walmart over just about anywhere else, analysts find. Reporting on research by UBS analyst Michael Lasser and colleagues.