A quiet but fundamental shift is underway in commerce.
AI and large language models (LLMs) are rapidly becoming buying intermediaries – not just tools for discovery, but decision-makers that shape what consumers see, trust, and ultimately purchase. This shift is not speculative. It is structural. And for manufacturers and large brands, it demands action now.
What we are witnessing is comparable to the rise of SEO in the early 2000s or the dominance of marketplaces in the 2010s. Those who adapted early won disproportionate advantage. Those who didn’t paid for it later.
1. Accept the Strategic Reality
The first principle is simple but uncomfortable: AI will sit between you and your customer.
Consumers are increasingly asking AI:
- What should I buy?
- What is best for my specific needs?
- Where should I buy it?
In response, LLMs are already:
- Comparing products across brands
- Summarizing reviews and expert opinions
- Recommending alternatives
- In some cases, triggering purchases directly
If your products are not understood, trusted, and retrievable by AI systems, they will simply not be considered. This is not optional. Visibility in AI-driven commerce will soon be as foundational as search rankings once were.
2. Rebuild Product Information for AI Consumption
LLMs require product data that is:
- Structured
- Consistent
- Unambiguous
- Rich in context
This means brands must move beyond marketing copy. Product information needs to clearly express:
- Use cases
- Comparisons and alternatives
- Compatibility and constraints
- Proof points and evidence
Standardizing product attributes globally and enriching them with real-world context is no longer a data hygiene exercise – it is a commercial necessity. AI cannot recommend what it cannot clearly understand.
3. Shift From Brand Storytelling to Machine-Readable Trust
Brand power is not disappearing, but it is changing form.
In an AI-mediated world, brand value must be translated into signals machines can evaluate:
- Facts
- Evidence
- Consistency across sources
This requires active management of:
- Reviews and ratings
- Expert and third-party content
- FAQs, objections, and edge cases
LLMs reward clarity, consistency, and credibility. Vague positioning and unsupported claims lose power when machines – not humans – are doing the filtering.
4. Treat LLMs as a New Marketplace Category
Many brands are making a dangerous mistake: treating LLMs as just another marketing channel, search engine, or chatbot.
They are none of these.
LLMs should be viewed as a new class of marketplace, with its own ranking logic and rules. Like traditional marketplaces:
- You don’t control the interface
- You don’t own the customer relationship
- You must optimize to platform logic, not brand preference
This mental model shift is critical. Brands that understand this early will shape how they are surfaced. Those that don’t will be shaped by it.
5. Build “LLM Readiness” as a Core Capability
LLM readiness cannot live in a single team or be treated as an experiment on the side.
Organizationally, brands must:
- Assign clear ownership for AI and LLM commerce
- Integrate readiness into product, content, and commerce teams
Technically, foundations matter more than ever:
- Clean PIM, DAM, and CDP systems
- Structured feeds and APIs
- The ability to track AI-driven referrals and conversions
This is infrastructure for the next decade of commerce.
6. Experiment Early at Low Risk
The smartest brands are not waiting for perfection. They are running controlled experiments now.
Early LLM commerce pilots help brands understand:
- How AI currently describes their products
- Which competitors are being recommended instead
- Where misinformation or gaps exist
These insights are invaluable — and far cheaper to uncover now than after AI-driven demand has scaled. Early experimentation is not a cost; it is strategic insurance.
7. Rethink Distribution and Merchant-of-Record Models
AI commerce will compress and abstract the transaction layer:
- Fewer checkout steps
- Payments, tax, and compliance handled invisibly
- Shifting ownership of the customer and transaction
Brands must make deliberate choices:
- When to sell directly
- When to rely on marketplaces
- When merchant-of-record models make sense
This is not a technical decision. It is a core commercial strategy question.
What Happens If Brands Don’t Act
The downside of inaction is already clear:
- AI recommends competitors
- AI defaults to large marketplaces
- Brand differentiation erodes
- Price becomes the dominant signal
- Margins compress
AI commerce is not coming — it is already here. The only real question is whether your brand will be shaped by it, or whether you will shape your position within it.
The time to act is now.
