From AI to Agency: What Are We Building and Who Does it Serve?
AI is no longer experimental in the consumer markets. It’s gone operational.
According to a 2026 study from IBM and the NRF, global usage of AI applications such as ChatGPT and other chatbots has grown 62% in the last two years. Nearly half of consumers now use AI to assist in the shopping journey. Forty-one percent use AI to research products. Thirty-three percent use it to synthesize reviews. Thirty-one percent use it to find deals. This suggests we’ve gone well beyond novelty to systemic utility.
At the same time, households continue to remain under pressure. One in three consumers report trading down to cheaper alternatives. Thirty-two percent are buying more private label. Yet, 25% still choose trusted brands even when they cost more. Value is no longer fixed. For many today, shopping involves precise calculations and trade-offs made in real time.
What Happens When Calculation Is Delegated
OpenAI has introduced instant checkout inside ChatGPT, with PayPal integration announced for 2026. AI is moving from assisting discovery to executing transactions. From advisor to agent. This is the moment where most commentary swings to extremes. Either AI will replace entire functions, or it is dangerously overhyped. Both miss the point.
The more serious question is not whether AI will be used. The real question is whether we are designing systems that deserve to scale, and that scale to human-centric requirements.
Deloitte’s latest State of AI research offers a sobering counterweight to consumer enthusiasm. Nearly three in four companies say they plan to deploy agentic AI within two years. Yet only one in five report having a mature governance model in place for autonomous systems. Speed is accelerating faster than oversight.
The Gap Where Risk Lives
The central danger is not artificial intelligence. It is artificial certainty. AI can generate plausible answers with remarkable fluency. It can synthesize conflicting sources into a coherent narrative. It can surface recommendations that appear data-driven and neutral. But it does not know when it’s wrong. It does not understand context beyond its training data. And here is the crux: AI does not own outcomes. We do.
For manufacturers and retailers, that matters. A flawed product claim amplified by an AI assistant becomes a feedback loop. A distorted value comparison becomes a shift in consideration. A misinterpreted demand signal becomes a production forecast. When decision velocity exceeds verification, error compounds.
Trust is already fragile. Only 24% of consumers say they trust AI recommendations outright. The majority take a “trust but verify” stance. Meanwhile, 83% express concerns about how their data is used, stored or shared.
If consumers are cautious, we should be as well. Yet caution shouldn’t signal retreat, because the opportunity is real.
Agentic systems have the potential to compress cycle time, surface trade-offs faster and connect consumer intent to execution with unprecedented clarity. They can monitor product data across channels in real time. They can identify inconsistencies before they erode trust. They can help align pricing logic, inventory status, loyalty economics and fulfillment rules within a single decision loop. But there is a shift that receives less attention.
Agentic Commerce Does Not Respect Organizational Boundaries … Not yet
AI agents ingest consumer signals, pricing rules, product attributes, promotion mechanics and supply constraints simultaneously. They collapse what were once sequential conversations between marketing, sales, engineering and operations into a single evaluative moment. If those constituencies remain misaligned, AI will amplify the fracture. If they share structured, trusted data and clear decision rights, AI becomes a translator.
AI can convert consumer preference into manufacturable demand. It can expose trade-offs between sustainability and cost before launch. It can clarify how brand promise aligns with operational feasibility. It can surface tension between margin goals and shopper value in ways that force better decisions. The technology is not the bottleneck, coordination is.
Deloitte’s research shows many organizations are scaling AI experiments into production at speed. But scaling tools without scaling alignment will only accelerate inconsistency. The next competitive frontier, then, will not be who deploys the most advanced model. It will be who builds the most coherent system around it. That system requires:
- Verifiable product truth that is consistent, structured and machine-readable.
- Transparent data governance that satisfies both human expectations and algorithmic scrutiny.
- Explicit decision rights for when agents act autonomously and when humans intervene.
- Cross-functional accountability for outcomes.
In this environment, brand building evolves. It’s no longer only about emotional connection with people. It’s also about credibility with algorithms that will filter, rank and purchase on their behalf. We are not entering the age of artificial intelligence. We are entering the age of amplified consequences. This is the point where commercial ambition meets human responsibility. It will not resolve itself.
AI Will Shop, Compare, Negotiate and Increasingly Transact — Leadership Remains Human
In the consumer markets, advantage has always belonged to those who listen well. The agentic era forces us to listen together, across silos, across partners and across the value chain that connects manufacturers, retailers and the shoppers they serve.
The future will not be decided by which model we deploy. It will be decided by how intentionally we design the systems around it and by the decisions that shape what gets made, stocked, priced and purchased.
Michael Forhez is the VP, executive industry advisor for the retail and consumer goods industry for Cambridge Design Partnership. He is a strategist in the retail and CG sectors, with leadership experience spanning sales, marketing, product and solution development, and consulting. He writes and speaks frequently on the forces shaping modern consumer markets, with a focus on strategy, technology and shopper behavior.
