Agentic AI introduces a new dynamic to the consumer-brand relationship, particularly as autonomous shopping agents interact directly with brand marketing agents. In the past, AI systems primarily supported recommendations based on user preferences. Now, agentic AI can shortlist options and make purchase decisions on a consumer’s behalf.
This shift moves decision-making away from the human and toward the AI system itself — changing how a product or service is selected. Below are key areas where agentic AI is already influencing marketing and commerce, along with where its impact is expected to grow in the months ahead.
Holiday 2025 as a glimpse into the agentic future
Data from Salesforce’s 2025 Cyber Week — the peak of the holiday shopping season — shows that AI agents have evolved from passive service tools into active commercial engines, creating a competitive advantage for retailers that deploy them. Several areas highlight where AI, and agentic AI in particular, stood out.
AI agents as revenue accelerators
AI and agents influenced 20% of all Cyber Week orders, accounting for $67 billion in global sales. This positions them as more than a cost-saving measure — they are a primary driver of top-line growth. During Cyber Week, retailers that deployed branded shopping agents on their websites saw sales grow 32% faster than those that did not.
High-intent discovery leads to stronger conversion
Traffic referred by third-party AI channels, such as ChatGPT and Perplexity, is proving significantly more valuable than traffic from traditional social media channels. Volume from these AI-driven sources tripled compared with 2024. During Cyber Weekend, consumers arriving via AI agent channels showed significantly stronger buying intent, converting at a rate eight times higher than those coming from social platforms.
Agentic means action
During Cyber Week 2025, the volume of tasks completed by agents on behalf of shoppers, such as initiating returns or updating delivery addresses, increased 70% compared with 2024. On Black Friday, the number of tasks completed by agents jumped 84%, allowing brands to manage traffic volumes that might have brought some retailers to a standstill in previous years.
What marketing leaders need to do: Rather than functioning solely as chatbots for basic inquiries, agentic AI is now driving meaningful revenue growth and performing complex operational tasks. This creates a clear performance gap between retailers that deploy these agents and those that do not.
While the 2026 holiday shopping season may feel distant, it is approaching quickly. Combined with the shift toward year-round shopping, this leaves little time for brands to delay action if they want to keep pace with early adopters.
Brands need to move beyond viewing AI as a digital store directory and toward treating it as a personal concierge. The speed and convenience of this model were tested at scale during Cyber Week and are likely to define how commerce operates in the seasons ahead.
Dig deeper: Why agentic AI is the next big shift in CX strategy
GEO is the new SEO
Before considering the broader implications of agentic AI, it is worth starting with an area already seeing direct impact.
Just as search engine optimization became critical to website visibility as the web matured, a new form of optimization is emerging for agentic AI systems. Generative engine optimization, or GEO, shares similarities with SEO but introduces important differences that require a distinct approach.
IDC predicts that by 2029, companies will spend up to five times more on GEO than on search optimization to influence generative AI systems and improve brand prioritization and ranking. As consumers increasingly rely on AI agents, the importance of this form of optimization will continue to grow.
When AI agents autonomously perform searches and carry out purchasing, scheduling and other actions on behalf of consumers, visibility on human-facing search results pages becomes less critical. Instead, brands must be positioned to surface directly within the systems guiding agent decision-making.
What marketing leaders need to do: Businesses will need to work with AI providers and invest in GEO to ensure their products and services are visible and prioritized by consumer agentic AI systems.
Dig deeper: Your website isn’t ready for AI agents — here’s what needs to change
Agents with agency
Agentic AI’s ability to operate autonomously and make decisions faster than humans introduces both opportunity and risk. If a consumer or brand agent makes a misstep, the impact can cascade with unintended consequences. As a result, human intervention — such as time delays or decision checkpoints — may be required to ensure outcomes align with brand values and maintain consumer trust.
One useful principle is to view agentic AI as a value maximizer. Through its use of retrieval-augmented generation, agentic AI can unlock institutional knowledge to optimize engagement. In practice, this allows a brand’s marketing agent to draw on deeper insights when interacting with a consumer’s shopping agent—for example, by delivering offers or information aligned with learned preferences and brand objectives.
Agents can also learn from one another over time, improving performance with limited human involvement. This creates the potential for brand marketing agents to learn from repeated interactions with consumer shopping agents, helping them better anticipate decision logic and preferences.
What marketing leaders need to do: This shift requires a fundamental change in marketing strategy. The traditional target — the human consumer — is increasingly being intermediated by an AI agent. As a result, marketers must reconsider how influence works when an AI system, not a person, determines which product or service is selected.
Dig deeper: 3 actions you must take to thrive in the agentic era of marketing
Several conclusions emerge from current consumer behavior and brand adoption:
- Consumer shopping agents are increasingly making purchasing decisions, requiring brands to adapt their marketing strategies.
- Brands need to invest quickly — and in some cases heavily — in generative engine optimization to influence AI agents and maintain visibility.
- Interactions between brand and consumer agents will require careful governance and, in some cases, human oversight to manage risk.
- Brand agents can use their data and reasoning capabilities to engage more effectively with consumer agents.
This remains a fast-moving space. The only certainty is that the landscape 12 months from now will look very different.
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