AI agents are coming: Is digital commerce ready for business-to-agent interactions?

If you follow industry news, you’ve probably heard the buzz about AI agents, which promise to bring autonomous AI commerce and capabilities to everything from sales and service to analytics and customer experience.

What is business-to-agent commerce?

Business-to-agent commerce refers to the use of intelligent AI agents that autonomously facilitate transactions between customers and sellers within e-commerce systems. Initially applied to sell-side commerce applications like merchandising, this technology will soon expand to buy-side commerce, where AI agents act on behalf of buyers to make purchasing decisions, negotiate deals, and streamline the procurement process.

So expect to see a new acronym added to the familiar B2C, B2B, and B2B2C commerce scenarios: B2A, or business-to-agent commerce. Sounds promising, and for some scenarios it will be, but it’s also worth remembering an old adage, “Be careful what you wish for, you just may get it.”

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AI agents: Welcome to the do-it-for-me era

The idea of AI agents and B2A commerce isn’t new. In fact, I wrote about the topic on this site almost a decade ago. At the time, I called the concept Virtual Personal Assistants. (I’ll admit “agents” is objectively cooler.) While that look into the future put the plausible ahead of the practical and possible, advances in technology have now made the concept a reality.

AI agents are essentially software programs imbued with performance-enhancing machine learning. These autonomous entities can understand their environment to make decisions and take action. This makes them capable of far more complex tasks than the bots we’re familiar with.

The potential seems to be sky high. But don’t take my word for it. According to Sam Altman, co-founder and CEO of OpenAI, “AI agents are going to be a fundamental shift in how we interact with technology. They’ll be able to understand context, learn from experience, and adapt to our needs in ways we can’t yet imagine.”

So, AI agents can act independently, are capable of learning, and are able to refine how they function over time. We’ve suddenly entered the era of do-it-for-me (DIFM) AI.

When put in the hands of businesses and consumers, this may fundamentally alter buy-side behavior and the ecosystems that come along with it.

Modernizing procurement for better B2B commerce

AI agents are the answer to a long-standing question in B2B: how do we make our jobs easier? They have the potential to create a sweet spot, overcoming deficiencies inherent in electronic data interchange (EDI), subscription, and manual purchasing processes. This can unlock massive value.

EDI has been the go-to tech to enable bulk purchasing and B2B commerce automation since the late 1960s. For this very reason, there’s a need for a more modern, efficient alternative that brings procurement into the 21^st century.

Subscriptions would seem like an ideal middle ground for the acquisition of raw materials, parts, and consumables, but any variance in consumption results in either a lack or surplus of inventory. In B2B, manual purchasing isn’t, or should not be, anyone’s full-time job.

Applying AI agents to purchasing addresses these deficiencies. Creating AI agents that are well-integrated with a company’s ERP system will create efficiencies of scale. They can enable even more automation and error-free bulk transactions to move orders through the supply chain, replacing antiquated EDI systems.

With site and SKU-level visibility across the enterprise, AI agents can perform just-in-time ordering, preventing stockouts and maintaining the lean inventories that are most profitable. Most ordering use cases are accounted for, reducing manual ordering to one-off and spot purchases to address immediate business needs.

With B2B commerce driven solely by need, AI agents are a solution to a range of problems that businesses could not solve until now.

The brave new world of B2C commerce

In the hands of consumers, the convenience AI agents offer is undeniable. When the agent knows a person’s preferences, physical characteristics, household makeup, past order history, and budget, turning over purchasing authority comes down to trust. Will consumers have confidence that AI agents will act in their best interest?

Consumer use cases, however, may create more problems than they solve. Imagine zero UI commerce where there’s no direct human involvement in either side of the transaction.

How do you inspire and convert a super intelligent, emotionless agent? It’s like trying to sell to the Terminator: “I’ll be back…when the hunter green V-neck cashmere cardigan in medium goes on sale at a rate equal to or greater than 15%.”

The potential impact of AI agents on the commerce ecosystem

Now, imagine the ripple effect AI may have across the commerce ecosystem, including merchandising and marketing.

1. Product discovery—It’s well-documented that the majority of product searches begin on Amazon. With AI agents, initial search queries will begin within an agent’s interface, not incumbent retail or search sites. This will lead to massive downstream impacts.
2. Paid media & SEO—While retail is not directly broken out, consider that Google has approximately a 35% market share of U.S. digital ad spend, and their 2023 global ad revenue was $238 billion. Without even factoring in search traffic already diverted to generative AI chatbots, just a little disruption here could have seismic impacts running into the tens of billions of dollars.
3. Cross & upselling—It’s estimated that retailers generate between 10% to 30% of their revenue from merchandising and suggestive selling. When AI agents are tasked with completing a single objective and no more, how will brands and retailers make up for this shortfall?
4. Retail apps—With AI agents productized as apps for personal use, this threatens to cut into direct consumer-brand engagement across a broad swatch of retailers and brands.
5. Retargeting—Is it possible to retarget a product to a person who may or may not have ever seen it?
6. Social selling—As “digital third-places” that already capture so much consumer attention, social media brands could be big winners in this brave new world.

How will the retail and tech giants respond to all these potential buying behavior changes? With so much money at stake, they’ll take steps to slow the rollout and adoption of consumer AI agents while working tirelessly to build and perfect their own.

AI agents represent an evolutionary step in commerce. While the full extent of their impact is yet to be seen, commerce leaders should prepare for massive change.