24% of consumers – and 32% of Gen Z – now comfortable with AI agents making purchases

AI agents are fundamentally changing how purchasing decisions are made, threatening traditional brand loyalty and marketing strategies as machines increasingly shop on behalf of humans. According to Salesforce research, 24% of consumers are already comfortable with agents making purchases for them, rising to 32% among Gen Z, signaling a shift toward algorithm-driven buying decisions that prioritize data over emotional connections.

The big picture: Unlike human shoppers who respond to emotional appeals and brand storytelling, AI agents evaluate purchases through structured data, price comparisons, feature lists, and review scores rather than lifestyle aspirations or brand loyalty.

What’s driving this change: Research indicates that AI agents process buying signals differently than humans, focusing on logical analysis rather than psychological triggers.

• Agents don’t browse influencer content, build emotional connections with brands, or make impulse purchases based on clever copywriting.
• They analyze products as structured data points that can be organized into tables and patterns.
• Models like OpenAI’s Operator show preference for ads with structured, machine-readable information.

Why traditional marketing may fail: Current marketing strategies rely heavily on human psychology and emotional responses that don’t translate to machine decision-making.

• Brand storylines and lifestyle positioning developed over decades may become irrelevant to AI shoppers.
• Agents operating within budget restrictions or ethical parameters won’t feel greed, FOMO, or brand loyalty.
• Machine-to-machine commerce may bypass traditional marketing channels entirely.

The technical challenge: Marketers face complex questions about how AI agents will process customer preferences and communicate trust signals.

• Agents may disguise their non-human nature by communicating through email rather than APIs (application programming interfaces, the standard way software programs communicate with each other).
• Marketing systems will need to distinguish between human and machine interactions to respond appropriately.
• Businesses must learn to “win” negotiations with buying agents transparently without compromising consumer trust.

What smart brands should do now: Companies need to prepare for agentic search impact and restructure their digital presence for machine consumption.

• Businesses should explore agentic AI as a marketing channel while building awareness of its capabilities.
• Product information must be structured into machine-readable formats with real-time data feeds for pricing and availability.
• Extensive API access to product and services data will become essential for visibility to AI agents.

The collaboration imperative: Rising to this challenge requires coordination beyond marketing teams, involving data, product, and digital teams to ensure agents receive aligned, on-message information when evaluating businesses.