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Salesforce Announces Einstein GPT for Field Service

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The Salesforce logo on an office building.
Image: Sundry Photography/Adobe Stock

Salesforce’s Einstein GPT and Data Cloud are now available in beta in the Field Service app, giving field service workers access to artificial intelligence features such as real-time data, automation and summarization.

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Who is Einstein GPT for Field Service for?

Salesforce says its addition of Einstein GPT into the Field Service app can help workers more efficiently communicate with their contact center, save time taking notes and generate service reports. Field service workers may be home nurses, technicians, contractors, workers in the public sector,  in manufacturing, and more. For example, Einstein GPT can help home nurses automate the process of writing up their notes after a home visit.

Salesforce partnered with different LLM partners including OpenAI, Cohere and Anthropic, said Taksina Eammano, the executive vice president and general manager of Salesforce Field Service, in an interview with TechRepublic.

Benefits of Einstein GPT for the Field Service app

The AI will complement the Field Service app’s ability to manage field workers’ tasks, manage assets and equipment, schedule and optimize travel and improve the customer experience, Eammano said. The AI functionality is made with part-time contractors in mind, allowing contact centers to see when contractors who only do certain tasks or work limited hours are available.

“Service swarming”

Field Service Mobile with Einstein GPT will enable teams to “service swarm” customer issues and work orders in Slack; service swarming is a Salesforce support model in which a worker can bring team members from across the organization into a conversation. Field Service mobile users can also use pre-built solutions from Salesforce’s Component Library to build custom mobile experiences for tasks like finding nearby spare parts or managing timesheets.

SEE: Salesforce revealed the collaboration with OpenAI on Einstein GPT in March.

Efficiency features with Einstein GPT on the Field Service app

Einstein GPT on the Field Service app can be used for on-the-job training or other communication between workers. Einstein GPT offers pre-work summarization, which makes sure the technician is ready and well-informed about what the previous worker to visit that site encountered and did.

Eammano said this is part of an overall philosophy of extracting more value from each site visit. For instance, the AI-enabled app may recommend other products that the customer might be interested in based on the most recent job a technician performed for them.

“Why this is so interesting [is] we have heard from our customers we’re sitting on their sales and service and marketing and commerce data,” said Eammano. “To have a way to unify that, to have our customers trust us to be that, we’re very concerned about that.”

Tutorials and guides

Another way in which AI is being added to the Field Service app is that Einstein GPT enables workers to search for step-by-step guides or to find instructions tailored to their specific tasks. These might be based on public knowledge or internal information shared with Salesforce.

“We are also looking to trust the data is coming from your CRM data,” Eammano said. “The corpus of data is within your environment and is substitutive and additive to the public data. That might include weather, maps, data and external product knowledge.”

Field service is just beginning the AI journey

Eammano pointed out that field service is well-positioned to benefit from an AI product because many smaller companies are still working on getting up to speed with digitization.

“These companies are still going through their digital transformation,” Eammano said. “Operations is still catching up to be able to drive automation.”

Some companies that use Field Service today are asking, “What data do I want, and what data will I get?” Eammano said. She sees an opportunity to make those decisions at the same time as housing all of the data from the workforce in the same service — namely, Salesforce and its companion apps.

Field service operators could benefit from greater safety with AI, Salesforce claimed, with real-time monitoring enabling companies to be sure technicians get to work and back home as expected.

Eammano sees AI as augmenting, not replacing, jobs in field service. Some field service jobs may move closer to the contact center, she predicted. Looking further in the future, she sees customers being able to service their own equipment more often. Even further into the future, she predicts a blended “autonomous apprentice” model where human technicians train bots to augment their work.

How AI will change field service management

In a world where a technician team might be made up of both people and the bots they’ve trained, managers might look for different markers for success.

“One of the areas I’m very excited (about) is around thinking about what outcomes enterprise software really wants to measure,” Eammano said. “How about your service outcomes? How do you measure success? Today we have customer satisfaction/NPS, but the future is: how do tech providers demonstrate much more of that outcome and create that outcome well together?”

Eammano sees CRM, data and AI as the future of how enterprise work works — and how Salesforce can serve it.

Salesforce is working on unifying the Field Service mobile app and Salesforce mobile app’s functionalities so that some AI features, such as conversational layers, in-app summarization and content generation, can cross over between both.

Data Cloud and Flex Worker Management enhancements

In other Salesforce news, Data Cloud for Asset Service Management has been enhanced with real-time data and predictive, usage-based maintenance. Ideally, this will help field technicians and other workers who monitor heavy machinery or infrastructure prevent machinery from failing before it actually happens.

For managers, Flex Worker Management has been enhanced with AI that can analyze when and where it’s best to send field workers based on their skills, their distance from the work site and the available tools.

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