Customers gravitate to brands that offer high quality products within digital ecosystems that are fast and attuned to their needs.
This is why agentic AI is so critical. According to research by Salesforce, 43% say they are already piloting autonomous AI, with use cases spanning the business. It’s easy to see why. Analysts at McKinsey believe that agentic AI will disrupt the retail industry faster than the internet and smartphones, and predict a global opportunity of up to $5 trillion by 2030.
The promise of agentic in retail
Contact centre transformation is a key use case. Agentic systems can process a range of common enquiries including product information, warranty requests, order-status updates, delivery issues, cancellations and more.
According to Kulvinder Hari, Senior Director Solution Engineering at Salesforce, retailers can thereby expect to deflect around 40% to 60% of inbound end-to-end customer service queries to AI agents. “By removing these high-volume, lower-complexity tasks from contact centre queues, human agents will be freed to concentrate on interactions that require empathy, context and judgement, as well as on cross- and upsell opportunities. This shift helps lift the contact centre from being a cost centre to a source of value,” he says.
AI agents will also reshape shopping experiences. Consumers will increasingly use AI agents as their go-to search engines, replacing traditional browsers. This means the commerce journey will begin and end inside AI assistants.
Hari adds: “Agents can interpret the purpose of a purchase, the sentiment behind it, and even the relationship between buyer and recipient. This awareness allows retailers to deliver suggestions that are thoughtful and relevant.”
Luxury and premium brands are already exploring the opportunities this presents for offering “white glove” experiences. Gemma, Pandora’s personal shopping agent, is currently live in Australia. Powered by Agentforce, Gemma gets to know what each shopper is looking for and makes recommendations based on the occasion, who the gift is for and the shopper’s budget. The agent understands the scenario, filters the product catalogue and presents a curated selection that matches the occasion.
Agentic AI will also enable retailers to open new entry points for customer engagement, transforming any digital interaction point into a potential commerce channel. Hari comments, “For example, a listener who hears a food-focused podcast might ask, ‘How do I make that recipe?’ and be guided by an AI agent to identify the necessary cookware, check which items they already own and purchase what they need.”
Preparing for agentic
With so much to gain, many retailers are already setting out on their agentic journeys. Hari recommends they take the following steps:
- Unify customer data across systems. Use tools such as Salesforce Data 360 to unify data from sales, service, marketing and commerce platforms.
- Optimise data for AI discoverability. Ensure product and content data are structured so that large language models can easily interpret and surface them.
- Focus on value-based use cases first. Start with use cases that demonstrate measurable business impact such as product information, service-centre automation, or personalised shopping journeys.
- Stay agile and cloud-ready. Keep your infrastructure cloud-centric so you can rapidly integrate emerging capabilities and updates from technology partners.
- Enable interoperability across agents. As more agentic systems emerge across functions, prioritise connectivity between them to create cohesive, end-to-end customer experiences.
Retailers that act soonest to harness agentic AI will define the next era of customer experience and set the standard for personalised digital commerce. It’s vital IT leaders identify revenue opportunities and begin to build a powerful engine for growth using agentic AI.