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Retail and consumer goods businesses are operating under intense pressure. Changing consumer expectations, margin constraints, and growing channel complexity are challenging traditional operating models. At the same time, agentic commerce is creating a new route to market: one in which autonomous agents can discover, compare, and purchase products on behalf of consumers.
Agentic AI offers more than another layer of automation. It can help organisations connect decisions and actions across the value chain — from product development and demand planning to commerce, fulfilment, and customer service. The opportunity is to redesign how work gets done, rather than add isolated AI tools to existing processes.
“Agentic AI can move organisations beyond individual use cases and towards a more connected model for creating value. The priority now is to redesign end-to-end workflows around clear business outcomes, supported by the data, governance, and human oversight needed to scale responsibly.”
David Lee, Partner and Chief Technology Officer, PwCThe playbook identifies eight enterprise value loops where agentic AI can address points of friction and unlock measurable value. These include accelerating innovation, improving supply-and-demand decisions, transforming customer engagement, and building more responsive commerce and service models. The common thread is orchestration: agents working across systems and functions, with people setting direction and retaining responsibility for judgement and oversight.
Preparing for agentic commerce
The relationship between brands and consumers is also changing. As people increasingly use AI to research and purchase products, businesses will need to make their propositions understandable and accessible not only to shoppers, but to the agents acting for them. This raises practical questions across product data, pricing, tax, payments, consumer protection, and the basis on which an agent makes recommendations.
“Agentic commerce will change more than the customer interface. As transactions become more autonomous and cross-border commerce develops, businesses will need to consider how their tax, trade, and compliance models support faster, more connected decisions without creating new risks.”
John O’Loughlin, Partner, Retail & Consumer Practice Lead, PwCThe brands best placed to respond will be those that treat agentic commerce as an enterprise issue rather than a standalone digital channel. They will need reliable product and customer data, interoperable platforms, and clear accountability across the commercial, technology, risk, and operational functions.
Build the foundations to scale
Scaling agentic AI requires a deliberate approach. Fragmented data, disconnected systems, and unclear ownership can limit the value of even promising pilots. Effective governance must therefore be designed into agentic workflows from the outset, with appropriate controls, escalation points, and human oversight.
“The real opportunity is not simply to deploy more agents. It’s to build an enterprise that can use them safely and effectively — connecting trusted data, modern platforms, and responsible governance so that innovation can move at pace without weakening control.”
Aisling Curtis, Partner, Strategic Alliances, PwCThe objective should not be autonomy for its own sake. Organisations need to determine where agents can act independently, where human review is required, and how performance, risk, and accountability will be monitored. This turns governance from a final approval stage into a practical licence to scale.
Redesign work alongside technology
Agentic AI will also change roles, processes, and decision rights. Employees may move from coordinating routine hand-offs to supervising agents, resolving exceptions, and applying judgement to higher-value decisions. That shift will require new skills, clear incentives, and operating models designed around collaboration between people and technology.
“The real impact of agentic AI is not technological but organisational. As agents take on more work, leaders must redesign operating models, clarify accountability, and equip people with the skills and confidence to apply human judgement where it matters most.”
Ruth McNamee, Partner, PwCOur playbook sets out five leadership priorities for turning experimentation into measurable performance. Start with the value loops that matter most, build the foundations for secure scaling, and treat workforce change as part of the transformation — not as an activity that follows it.
Move from experimentation to measurable value
Agentic AI can help consumer markets businesses respond faster, operate with greater resilience, and create more relevant customer experiences. Capturing that value requires more than investment in individual tools. It requires leaders to connect strategy, technology, governance, and workforce redesign around measurable outcomes.
Download the PwC and Microsoft playbook to explore the enterprise value loops, foundations and leadership priorities that can help your organisation move from AI pilots to performance.
Ready to move from pilots to performance?
Explore how agentic AI can reshape value creation.
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