Test, Learn, Iterate: Lessons from Six Real-World Agentforce Rollouts

Companies are under pressure to move through their AI deployments quickly so they can get to ROI as soon as possible. But technologies as powerful as AI and agents aren't always easy to roll out. Data needs to be organized. Guardrails need to be determined. Knowledge articles need to be created. Often, it's hard to know how well something works until the fail points make themselves known.

One key to success, said Peter Burns, Director of Marketing, Digital & eCommerce at Heathrow Airport, is data. "This may sound obvious, but of course it's an important one. And that's data. An agentic experience is only as good as the data that drives it. So in Agentforce, Salesforce brings a great front-end experience for us that continues to learn," he said. "But it's the business's responsibility to bring that data in a structured way and the right way to drive the right experience."

Heathrow's customer service agent, called Hallie, can answer questions about things like security checkpoint wait times, restaurant locations, and gate directions. One reason it works so well, said Burns, is that all of Heathrow's customer data sits in Data 360. "We spend a lot of time focusing on the quality of that data and ensuring it's matched to our customers to give them the information they want at the right stage of the journey."

These Salesforce customers faced challenges along the way to becoming Agentic Enterprises - but they treated them as valuable learning opportunities, making smart, iterative adjustments that ultimately strengthened their deployments. They're lessons that can help guide other companies along the Agentic Enterprise journey.

Engine: Overcoming Missed Connections

DeVry University: Learning How to Help Students Learn

The second challenge arose with one of DeVry's student portal agents designed to help current learners navigate the academic catalog. The issue wasn't accuracy but context. Without course history, the agent often recommended completed or irrelevant courses. DeVry's solution was to integrate structured data sources, giving the agent the awareness needed to personalize responses in real time.

These improvements marked another step in the university's evolution toward an AI-enabled, student-centered model - one that incorporates automation and human insight to deliver care when and where students need it most.

"Technology should enhance human connection, not replace it," said Campbell. "With Agentforce, we're able combine automated accuracy with human care - working together to support students whenever and however they need it."

Indeed: Understand That Agentic Implementations Are Like No Other

Indeed launched agents across the company's workflows to make the job search even faster, but the company quickly realized that three things make agent deployment different from other tech implementations. First, agent deployments require fundamentally changing team structures - who is involved in building these types of products - and modifying other internal processes.

Then there was the question of data sources. "The more context the agent has, the more powerful," said Linda West, VP of Business Automation. "Investing a lot of time in understanding what data sources are going to enrich the context for the agent is such a critical part of the process to ensure the agent is as powerful as it possibly can be."

Finally, Indeed found that alignment with human teams is essential. "You can't underestimate the fact that in most of these cases, you need humans and agents to work here hand in hand," said West. This alignment required clarity with the "human teams" on the vision and the problem set - a key element of any company's agentic implementation strategy.

Safari365: All in on Data 360

In the early days of Safari365, the company managed $30,000 custom trips with spreadsheets and Word docs. A single itinerary could involve 20 vendors across multiple destinations, and the tech stack was totally fragmented. Leads came from one tool, emails were sent from another, and availability lived elsewhere. "It was impossible to get a full picture of the customer journey," said Marcus Brain, Founder of Safari365, which is one of Africa's leading tour operators. "We had no way to track performance, spot bottlenecks, or understand where we were losing potential travelers."

When Safari365 initially got started with Salesforce, it was a big lift to rebuild all of the pricing logic into the system - the company had 3,000 different suppliers, each with different rules. (For example, what's the fee for sharing a room with a child versus with a partner?) But, said Brain, the focus on data was worth the effort. When Safari365 recently got started with Agentforce, it had actually just completed another major data cleanup. The timing was perfect. "Because our data is so clean and structured, we were in a great position to launch Agentforce," said Brain. "We could immediately take advantage of the automation because all the inputs were already there, deeply integrated into our workflows." Now, when customers book a trip, they get a personalized set of "day notes" telling them exactly what each day of their custom trip will look like. Or Agentforce can go back to a conversation with the customer from years ago and pull up the fact that the client's son loves elephants and suggest a close-up experience.

Next up? Safari365 is going all in on Data 360. "Right now, so much of our staff's time is spent calling small bush camps and digging through third-party sites. That's not structured Salesforce data," said Brain. With Data 360, "we'll be able to marry external data - like TripAdvisor reviews or Booking.com content - with our internal records. It'll help us vet new suppliers, enrich itineraries, and take our personalization to the next level."