Industries that are facing consumers are moving the fastest to put AI agents to work. Retailers, travel providers, hospitality companies and financial services organizations are deploying autonomous agents across customer journeys—since that’s where the immediate payoff is most tangible and quantifiable.
Updated data from Salesforce’s Agentic Enterprise Index indicates a dramatic shift: Agent creation among first movers has more than doubled, and the average volume of customer service conversations handled by an AI agent has spiked more than twentyfold. The throughline here is fairly straightforward—high-frequency transactions and sophisticated data pipelines are a natural home for AI autonomy.
Why consumer-facing sectors are leading AI agent adoption
These industries succeed or fail through their ability to respond, personalize and maintain consistency at scale. When a shopper inquires about a return policy, a traveler tries to rebook after a delay or a cardholder disputes an item on their bill, speed and accuracy are valued over novelty — and AI agents can provide both 24 hours a day.
According to Salesforce, consumers are becoming more accustomed to automation and rely on AI when presented with the option. That’s comforting, and as with everything scarily new, it sows a long tail of repetitive questions and defined workflows for them to follow. Brands take a low-risk path to high-impact automation.
What the numbers show about accelerating adoption
Travel and hospitality are showing the steepest increases each month in the monthly index of agent actions, followed closely by retail and financial services. These are triple-digit growth numbers, indicating that adoption is accelerating as use cases broaden from simple FAQs to multi-step and complex tasks.
Employee engagement with agents is also growing. Salesforce cites consistent upticks in the back-and-forth of conversations and an increase in the number of actions agents take per interaction — a sign that organizations are trusting them with more responsibility, and integrating them into real workflows rather than isolated pilots.
How brands are using agents across key journeys
Agents are retail’s big assistants around the pre-purchase and post-purchase journeys: guided shopping, size-and-fit advice, order tracking and returns orchestration. Walmart has experimented with generative assistants in its app; Instacart’s “Ask Instacart” feature responds to product and recipe questions; Carrefour’s Hopla supports list planning; and Amazon’s Rufus embeds product insight right into the shopping experience.
For travel and hospitality, agents support questions about changes to itineraries, compensation policies, and loyalty servicing. Booking.com and Expedia have introduced artificial intelligence trip planners, KLM’s BlueBot has evolved from basic chat to transactional assistance, and hotel chains are experimenting with digital concierges for on-property requests such as late checkouts or room amenities.
Money services are melding automation with stringent rules. Bank of America’s Erica virtual assistant is being used as an entry point for balances, bill payments and to initiate disputes. Capital One’s Eno and Morgan Stanley’s advisor assistant provide examples of how agents can complement both consumers and professionals, accelerating tasks while adhering to compliance guardrails.
The most eye-popping proof point: Klarna says that its AI assistant now manages more customer service chats than humans, doing many of the jobs of hundreds of human agents while reducing resolution times and maintaining quality of service. It’s that kind of result that has CFOs underwriting expansion.
Finding the happy medium between automation and humanity
Early adopters aren’t displacing people; they are orchestrating them. The agents work the first pass of all repetitive requests, contextualize them and route them intelligently. Escalations to humans are also increasing as systems improve at when expertise and empathy are called for—so that promising the containment of escalation is not the only measure of success, Salesforce says.
So as to keep risk at bay, organizations are using retrieval-augmented generation for grounded responses (answers), role-based access controls on sensitive data, and audit trails of each agent decision. Others are using “supervisor” models and human-in-the-loop reviews for high-stakes actions such as refunds, rebookings, or credit decisions.
The ROI story and what is likely to follow next
The economics are hard to overlook. In customer service, containment rates, average handle times, and first-contact resolution are climbing; in sales, conversion rate ticks up (as does basket size) when agents personalize shopping; and in finance, autonomous triage is reducing manual backlog. McKinsey estimates that generative AI could unlock between $2.6 trillion and $4.4 trillion a year in value across functions, with customer operations, sales and marketing as the top beneficiaries.
The next lap shifts from single-turn chat to multi-agent workflows, dynamic bundling in retail, proactive re-accommodation in travel, on-property operations in hotels, and so forth. Leaders will manage this transformation with clear policy, real-time monitoring and metrics that balance efficiency with customer experience and brand trust.
The rest of the bottom line: consumer-facing industries are sprinting ahead because they have numerous use cases, actionable data and customers who reward speed. The competitive distance between the two will only widen as early movers scale their agents from help desk to full journey — and laggards come to realize that meeting modern expectations is an ever steeper proposition without AI.
