AI agents can create real value, but the risk changes when AI moves from answering to acting. As agents gain access to data, systems and business processes, retailers need to think as carefully about the authority around the model as the capability of the model itself.
By Simon Cruddas of arcretail.technology and Validify
Retail leaders from
Agentic AI is already appearing inside CRM, commerce, customer-service, marketing, productivity and enterprise platforms. The same capability that makes an agent useful, its ability to access data, use tools and take action, also changes the consequences when it gets something wrong.
This report looks beyond the AI demonstration to the controls around it. It explores how retailers can judge the level of authority an agent actually needs, where deterministic safeguards should sit, who needs to own the process and what leaders should ask before relying on an agent in a live business environment.
Discover the key findings from our latest research, and how retail leaders are preparing for what’s next.
Why the risk changes when AI moves from answering to acting
How two systems described as the same “returns agent” can carry very different levels of authority and exposure
Why more autonomy does not automatically mean a better or more mature solution
Where hard limits should sit outside the model
Why agentic capability may already be entering the business through technology you use today
Seven practical questions to ask before trusting an AI agent
Why ownership, monitoring and the ability to stop an agent need to be designed in from the start
The question retailers need to answer
The important question is no longer simply: can the agent do this?
It is: should it be allowed to do it, under what conditions, and what happens when it gets it wrong?
Simon Cruddas is a consultant at arcretail.technology with 25 years’ experience across retail technology, data, security, integrations, legacy systems, digital platforms and infrastructure.
Validify helps retailers and consumer brands make better technology investment decisions by bringing together current retail intelligence, technology matching, expert judgement and direct insight from the people choosing and implementing technology in retail.
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