Insights from KeyBank’s Emerging Technology Summit

I just spent a full day in San Francisco at KeyBank’s annual Emerging Technology Summit speaking with institutional investors, technology leaders, and operators about the future of commerce.

One topic dominated nearly every conversation.

Agentic Commerce.

This is not a niche concept or speculative hype.
It represents the most significant shift in the consumer shopping experience since the rise of ecommerce.

The implications will reshape how consumers discover products, how brands get recommended, and how transactions occur online.

This article breaks down what agentic commerce actually is, what is real versus hype today, and what brands must do to prepare over the next three to five years.

What Is Agentic Commerce?

Agentic Commerce is a model of online shopping where autonomous AI agents act on behalf of consumers to discover, evaluate, and purchase products.

Instead of consumers manually browsing websites and marketplaces, AI agents perform much of the shopping process automatically.

An AI commerce agent can:

• Understand a user's preferences
• Anticipate needs based on context and history
• Search across retailers and marketplaces
• Compare products, prices, and reviews
• Evaluate tradeoffs such as quality vs price
• Recommend the best option
• Complete the purchase

In many cases, this process can happen with little to no direct human interaction.

The result is a shopping experience that is:

• proactive
• hyper-personalized
• frictionless
• increasingly automated

What Is an AI Shopping Agent?

An AI shopping agent is a software system powered by large language models and structured product data that can autonomously make purchasing decisions for a user.

These agents combine:

• LLM reasoning
• user preference modeling
• product catalog data
• pricing information
• merchant integrations

Examples beginning to emerge include:

• ChatGPT shopping integrations
• Perplexity commerce experiences
• AI assistants embedded in operating systems
• Amazon’s generative AI shopping features

Over time, these systems will evolve from advisors into active purchasing agents.

What Is Answer Engine Optimization (AEO)?

As AI agents become responsible for product discovery, brands must optimize their presence for AI recommendation engines rather than traditional search engines.

This discipline is called Answer Engine Optimization (AEO).

AEO is also commonly referred to as:

• Generative Engine Optimization (GEO)
• AI Search Optimization

Definition

Answer Engine Optimization is the practice of structuring content, product data, and brand authority signals so AI systems can understand and recommend your products.

In practical terms:

AEO = External Authority Signals + AI-Readable Data

Two components matter most.

1. External Authority (PR)

AI models rely heavily on trusted third-party sources to evaluate brands.

Signals include:

• media mentions
• expert reviews
• industry publications
• comparison sites
• marketplace reputation

These signals provide credibility and validation for AI systems.

2. On-Site AI Optimization

Brands must also structure their own data so AI models can interpret it easily.

This includes:

• rich product descriptions
• structured product attributes
• organized knowledge bases
• machine-readable catalog data

Without structured data, AI agents cannot reliably evaluate products.

If your products cannot be understood by AI systems, they cannot be recommended.

Why Structured Product Data Is Now Non-Negotiable

Structured product data is becoming one of the most critical assets in ecommerce.

AI agents rely on clearly defined product attributes to compare and evaluate options across retailers.

Examples include:

• specifications
• price
• materials
• features
• compatibility
• shipping information

When this information is structured correctly, AI agents can confidently compare products.

When it is inconsistent or incomplete, the product becomes difficult for AI systems to evaluate.

This is why major platforms like Shopify are pushing merchants to adopt agent-ready product data models.

Shopify just published an excellent breakdown on why structured product data is now non-negotiable; read it here: https://www.shopify.com/enterprise/blog/agentic-ready-product-data

Where Agentic Commerce Actually Stands Today

Despite the rapid progress in AI, fully autonomous agent-driven purchasing is still early.

Consumers are experimenting with AI for product research and recommendations, but large-scale automated purchasing has not yet taken hold.

For example, ChatGPT’s Instant Checkout integrations generated significant headlines, but widespread consumer usage has not yet materialized (likely because ChatGPT has really not even rolled it out publicly yet).

This is normal for a technology transition of this magnitude.

Two major factors will determine how quickly adoption accelerates.

The Two Barriers to Agentic Commerce Adoption

1. Consumer Trust

Consumers must feel comfortable allowing AI systems to access sensitive data such as:

• payment information
• personal preferences
• purchase history
• identity data

Early platforms may need to incentivize adoption, similar to how TikTok Shop used aggressive subsidies to drive initial usage.

Trust will develop gradually as consumers see successful transactions occur repeatedly.

2. Agent Performance

AI agents must deliver consistently strong recommendations.

In practice, this means agents must function like high-end personal shoppers.

They must be able to understand nuanced preferences such as:

• price sensitivity
• brand loyalty
• product quality expectations
• sustainability concerns
• aesthetic preferences

If agents consistently recommend the wrong products, consumers will revert to traditional shopping behavior.

Can Brands Simply Buy Their Way Into AI Recommendations?

The short answer is no.

Advertising inside AI systems may exist, but paid placement cannot replace AEO.

AI agents require structured product data and credibility signals in order to evaluate products.

Without those inputs, paid placements will either perform poorly or fail to serve entirely.

At the moment, advertising within AI systems is still extremely early.

Current ChatGPT media buys available include:

• direct campaigns through OpenAI
• Shopify Shop Campaign integrations (see my opinion on this here)
• emerging partner ecosystems like Criteo

Most of these solutions are still in early testing phases and lack mature targeting and measurement capabilities.

Why Shopify Is Positioned to Win the Agentic Commerce Era

Among ecommerce platforms, Shopify has moved aggressively to build infrastructure for AI commerce.

Key developments include:

• Agentic Storefront capabilities
• Storefront MCP integrations
• structured catalog APIs
• Instant Checkout integrations
• Shop Campaign distribution
• knowledge base infrastructure
• the Universal Commerce Protocol (UCP)

These initiatives allow Shopify merchants to expose product data and purchasing infrastructure directly to AI systems.

As a result, Shopify merchants are entering the agentic era with a meaningful head start compared to brands operating on fragmented commerce infrastructure.

Will Agentic Commerce Kill Traditional Marketing Channels?

Several fears surfaced repeatedly in conversations with investors.

Most of them are overstated.

Is Meta advertising going away?

No.

Agentic shopping is intent-driven, similar to search.

Consumers still need to discover brands before asking AI agents to evaluate products.

Top-of-funnel marketing remains essential.

Will Shopify ($SHOP ( ▲ 3.78% ) ) be disintermediated?

Highly unlikely.

Shopify is actively positioning itself as the infrastructure layer connecting brands, merchants, and AI systems while protecting its core revenue streams such as payments and subscriptions.

The Wild Card: Advertising to AI Agents

A fascinating idea beginning to surface in early discussions is whether brands may eventually advertise directly to AI agents.

If AI agents increasingly influence purchase decisions, brands may try to shape how those agents interpret their products.

Some experimental platforms are already emerging around this concept.

One example is Moltbook, a new Reddit-style social network where AI agents can interact, debate, and exchange information while humans observe.

While this concept still sounds experimental, it raises a broader question:

If AI agents become the primary decision-makers in commerce, where do those agents form their opinions?

Understanding that ecosystem could become a new frontier in marketing.

What Brands Should Do Right Now

Despite the early stage of adoption, the strategic direction is clear.

Brands should begin preparing immediately.

Three priorities stand out.

1. Build Structured Product Data

Ensure product catalogs include:

• standardized attributes
• detailed specifications
• consistent taxonomy
• machine-readable formats

This enables AI agents to evaluate products accurately.

2. Build External Authority

Strengthen brand credibility across trusted sources such as:

• expert publications
• industry reviews
• comparison platforms
• marketplaces

AI models rely heavily on these sources to evaluate brands.

3. Optimize Content for AI Discovery

Create content formats that AI systems can easily interpret, including:

• definition-based articles
• structured FAQs
• comparison guides
• authoritative industry explainers

These formats dramatically increase the probability that AI systems cite and recommend your brand.

The Bottom Line

Agentic commerce is still in its early stages.

We do not yet have large-scale real-world data on how consumers will behave when AI agents fully participate in purchasing decisions.

But the direction is clear.

The brands that win will be those that:

• understand AI discovery systems
• structure their data correctly
• build authority across the internet
• prepare their infrastructure for AI-driven purchasing

The shift toward agentic commerce is happening faster than most brands realize.

The companies preparing today will dominate the next era of ecommerce discovery.

One Final Thought

The question brands should be asking is no longer:

“How do we rank on Google?”

The question is becoming:

“Will AI agents recommend our products?”

That answer will determine who wins in the next generation of commerce.

Agentic commerce is still rolling out gradually - we don’t have massive real-world data yet. But it’s arriving faster than most brands are ready for.

The winners will be the ones who master AEO today, leverage platforms like Shopify, and think creatively about influencing the agents of tomorrow.

If your brand feels lost in the agentic shift, contact me. We just acquired a Shopify Premier Partner dev agency and are actively trailblazing this space. We’re productizing “Agentic-as-a-Service” to make winning the race to the agentic moon dead simple.

Catch Me at SXSW Next Week!

Are you going to be in Austin, TX next week for SXSW? Avenue Z is taking the stage with Profound to do live AEO audits for businesses revealing how ChatGPT, Gemini, Perplexity, and other AI-native platforms interpret and recommend companies in real time.

Learn More Here: https://schedule.sxsw.com/events/PP1162374

What I’m Listening to 🎧

Beats of the Week: SAMM (BE) & AJNA (BE) at Sonnbühel, Kitzbühel, Austria for MAJA (February 2026)

Samm & Ajna are rising. Been on my list to see them live but they don’t come to the US very often. Hopefully will check this off in 2026. This Après-ski set in Austria is a perfect blend of melodic vibes with their own unique recognizable style. Highly recommend.

You’re reading In The Snow, by Jonathan Snow.

This is where operators, media buyers, and digital execs stay ahead of the curve.

Feel free to reply directly with any thoughts or feedback.