Three years ago, one of the largest U.S. retailers told Vue.ai CEO Ashwini Asokan that its pricing process involved having 10 to 15 websites open with an Excel sheet, manually cross-referencing the same product across all platforms.
“All of that is out the window today,” said Asokan, whose company has provided AI solutions to major retailers for nearly a decade.
This transformation represents more than efficiency gains. With shifting tariffs changing sourcing costs overnight, supply chains requiring constant rebalancing, and pricing decisions needed in real time rather than quarterly cycles, retailers face unprecedented operational demands. Traditional manual processes and basic AI tools simply can’t keep up.
The solution many in the retail industry are testing is agentic AI – autonomous systems that don’t just analyze data but take action without human oversight.
Unlike basic chatbots or AI copilots that require manual inputs for every decision, these agents can analyze market conditions, develop strategies, and execute complex tasks independently. For retailers balancing current uncertainty with future curveballs, this technology represents the difference between reactive survival and proactive growth.
Speed as strategy
The operational acceleration is dramatic. Traditional pricing cycles used to take three to six months for planning, data collection, analysis, and execution across specialized teams. Now AI agents dynamically adjust prices, messaging, and inventory allocation in real time.
“We don’t need AI to run everything,” said Matthew Mayes, Director of Product Management at Salesforce. “We need it to make things more relevant to customers based on how they actually behave.”
When container prices spike or supply chains are disrupted, these agents instantly recalibrate everything from pricing strategies to inventory allocation across stores.
This speed matters because retail’s current challenges demand unprecedented agility. Major retailers have preemptively pulled forward massive amounts of inventory ahead of potential tariff increases, creating a divide between companies with cash reserves and those running leaner operations.
The biggest priority right now is the bottom line. Retailers are optimizing what inventory they already have and leaning hard into loyalty and owned channels to maintain margins.
Michelle Grant, Director of Industry Insights at Salesforce.
“The biggest priority right now is the bottom line,” said Michelle Grant, Director of Industry Insights at Salesforce. “Retailers are optimizing what inventory they already have and leaning hard into loyalty and owned channels to maintain margins.”
For retailers without similar cash reserves, AI agents provide a competitive equalizer through faster, smarter decision-making across pricing, inventory management, and marketing spend allocation.
Widespread adoption
The retail industry’s willingness to embrace new technology is driving rapid AI adoption. More than nine in 10 retailers are investing in AI, and during the 2024 holiday season alone, $229 billion in sales were influenced by AI.
“Retail has historically been a pretty agile industry, and embracing new technology has always been how retailers stay ahead of shifting consumer demands,” said Caroline Reppert, Director of AI and Technology Policy at the National Retail Federation.
Retailers have long been early adopters of new technology — from barcode scanners in the 1970s to ecommerce in the 1990s to contactless payments and mobile checkout in the 2000s.
However, most of the industry’s current AI implementations remain limited to basic automation, like copilots requiring manual inputs for every decision and chatbots that only respond to predetermined scripts.
Salesforce’s agentic AI solution, Agentforce, moves beyond these limitations. The digital labor platform allows companies to build AI agents that autonomously analyze data, develop action plans, and execute tasks using existing company data to manage everything from dynamic pricing to inventory rebalancing across multiple locations.
The bridge that a lot of our customers aren’t able to traverse is how to turn insights into action. With Agentforce, you can build a data analysis agent that actually acts on that data.
Matthew Mayes, Director of Product Management at Salesforce
“The bridge that a lot of our customers aren’t able to traverse is how to turn insights into action,” said Mayes. “With Agentforce, you can build a data analysis agent that actually acts on that data.”
Implementation guardrails
However, deploying autonomous AI systems raises legitimate concerns about control and brand integrity.
“If I’m a luxury clothing retailer, for example, I’m very cautious about the experience,” said Mayes. “Giving up too much control could degrade my brand.”
To address these concerns, successful implementations embed business rules around pricing, profit margins, and brand standards directly into the AI agent’s framework. The agent draws on real-time data — sales, inventory, competitor pricing — to make informed, up-to-the-minute decisions. Meanwhile, human teams define escalation processes so they can review any flagged issues or anomalies, ensuring efficiency without compromising their control.
Common implementation pitfalls include deploying agentic AI without proper data governance or failing to set clear performance metrics. The National Retail Federation has launched AI working groups to help retailers share best practices and avoid these mistakes.
“There’s definitely a learning curve,” Reppert said. “Many retailers are still figuring out how to evaluate what’s real and what will work for their business.”
Building for what’s next
The true advantage of agentic AI extends beyond solving current operational challenges. The technology creates an adaptive foundation for future disruptions while helping retailers maximize value from existing customer relationships — a critical strategy as acquisition costs continue to rise.
As retailers face continued uncertainty, those implementing agentic AI aren’t just surviving current pressures — they’re building the operational capabilities needed for whatever comes next. In an industry where change is the only constant, the ability to turn uncertainty into a competitive advantage through autonomous, intelligent systems may prove decisive.
“The retailers succeeding right now aren’t just surviving the current pressures — they’re using AI to build the operational foundation for what comes next,” Grant said.
Go deeper:
- Read why AI is pushing commerce to a major inflection point
- Uncover more data about agentic AI’s impact in retail
