For product and data teams building consumer-facing AI, this research is a concrete signal that agent delegation is now a design requirement rather than a hypothetical: nearly a third of consumers already want an agent to choose within bounded parameters, and Accenture frames structuring product data for machine evaluation, a discipline it calls agentic engine optimization, as a new competitive layer alongside SEO.
What happened
Accenture's 2026 Consumer Pulse Research, surveying 25,590 consumers across 16 countries between January 7-22, 2026, found that 74% of respondents would trust a personal AI agent more than their best friend to make a purchase on their behalf, according to the report "Talk to My AI Agent: The New Rules of Brand Value," published June 3, 2026. The survey found 74% would delegate routine tasks (negotiation, complaint resolution, subscription renewals, reorders) to an agent acting strictly on instruction, 32% would let an agent choose within defined parameters like budget and brand, and 9% are open to fully autonomous purchasing. Accenture introduces a "delegation dial" concept: the same consumer who delegates grocery restocking might withhold authority over travel bookings, with payments remaining the biggest sticking point (only 12% are open to agent-led payment decisions). Consumers also want to keep a voice in brand choice: 56% would tell an agent which brands to consider, while 37% of behaviorally loyal shoppers would still let an agent switch brands for a better fit.
For practitioners
Accenture frames this as a new discipline it calls agentic engine optimization (AEO): product data, pricing, availability, and claims need to be structured and machine-verifiable so agents can evaluate and select a brand, not just persuade a human. The report also found 71% of consumers expect generative AI to influence at least half of their spending decisions within 12 months, and that among weekly gen-AI users, AI has already overtaken physical stores as the leading discovery channel, a signal that discovery and recommendation systems should treat agent-readability of product data as a ranking factor.
What to watch
Track whether delegation broadens beyond low-stakes categories like groceries and subscriptions into higher-consideration purchases like travel, and whether payment-stage autonomy (currently just 12%) rises as agents build a track record. Also watch adoption of AEO-style structured data standards among retailers, and follow-on studies that validate these self-reported delegation percentages against actual agent transaction data.
Editorial analysis
These are self-reported survey results, not observed agent transaction data, so actual delegation behavior in production commerce systems may differ from what consumers say they would accept in a survey. Accenture, a management consultancy with a commercial interest in agentic-commerce advisory work, both conducted and published the research.
Key Points
- 1Accenture's survey of 25,590 consumers across 16 countries found 74% would trust a personal AI agent more than a close friend for purchases.
- 2Only 12% of consumers accept agent autonomy at the payment stage, showing delegation is broad for routine tasks but narrow for money decisions.
- 3Accenture urges brands to make product data machine-verifiable via agentic engine optimization, since agents increasingly evaluate and select brands before consumers see them.
Scoring Rationale
A large, methodologically documented survey (25,590 consumers, 16 countries) from a major consultancy, corroborated by independent trade coverage, that introduces an actionable framework (agentic engine optimization) practitioners are already discussing; notable but not a technical or product breakthrough.
Sources
Public references used for this report.
Practice with real Retail & eCommerce data
90 SQL & Python problems · 15 industry datasets
250 free problems · No credit card
See all Retail & eCommerce problems
