This article is part of VentureBeat's special issue, “AI at Scale: From Vision to Viability.” Read more from this special issue here.
This article is part of VentureBeat's special issue, “AI at Scale: From Vision to Viability.” Read more from the magazine here.
Just seven or eight months ago, when a customer called or emailed Barrier Systems with a service query, a human agent handling the query would start looking for similar issues in the system and analyzing technical documentation.
This process would take about five to seven minutes; then the agent could offer the “first meaningful response” and finally begin problem solving.
But now, with AI Agents directed by Sales forcethat time is shortened to as little as five to 10 seconds.
“That's a big downsizing,” Andrew Russo, enterprise architect at Baca Systems, told VentureBeat. He emphasized, “for us, it's not about how do we lay off people, do we reduce staff. It's is our goal, how do we make sure the customer is back to work as quickly as possible?”
Closing time gaps, delivering faster time to resolution
BACA Systems, a Michigan-based robotics manufacturing company, first implemented Salesforce in 2014, eventually adding Cloud service instead of “vanilla, or maybe more like strawberry ice cream, a basic service cloud,” Russo explained. The company then underwent a “major digital transformation” in 2021, rolling out Salesforce's enterprise resource planning (ERP) platform.
Team members soon began working with predictive AI for sales and manufacturing projections; then the company became AI producers, implementing Salesforce's Task force within the past year.
The main use case was service calls. Russo explained that about 57% of incoming customer inquiries are hardware-related (for example, a device crashes or needs calibration).
Now, instead of trawling through databases for previous customer calls and similar issues, human agents can ask the I have an agent to find the relevant information. The AI runs in the background and allows humans to respond immediately, Russo noted.
AI can also support preventive maintenance. For example, a circuit breaker may constantly trip, indicating a short in the wire that should be checked, Russo explained. This may help eliminate previously unresolved ongoing issues.
“It's about how we deliver faster time to resolution for customers,” Russo said.
AI agents generate sales leads, handle customer inquiries
Another pressing use case is sales, because as a small company, Baca naturally doesn't have hundreds or even dozens of salespeople (actually they have less than 10).
“We have a lot of boats that we haven't had time to reach,” Russo said. “Our goal is: How do we start engaging them?”
AI can act as a sales development representative (SDR) to send out general calls and emails, communicate back and forth, then send the prospect to a member of the sales team, Russo explained. Bringing on additional salespeople to handle such tasks would require tens of thousands of dollars in wages, but if AI can develop new contracts, its upfront cost is “very easy to justify.” .”
In the coming months, the company plans to use the face of customers service representatives which can interact with human users via text message to open and handle cases without the initial need for human intervention. If the AI agent cannot solve a problem, it escalates the issue to a human representative.
The mission is, “How do we continue to deliver more value to customers on the service side and create more deals on the sales side?” Russo noted.
Outside of sales and service, Baca is using AI to generate emails, create available items and create “very tight cover letters” when needed. Russo, for his part, uses the technology for partial duplication analysis, taking advantage of regenerative-enhanced generation (RAG) with quick builders to find duplicates to prevent bad data from being including Salesforce.
There has not been much from employees, he reports: The company started small, initially giving access to a select group of users. Others then quickly started asking. “They actually started begging (us) to give them a chance,” Russo said. “No one is afraid; they like using it because it helps them do their jobs better.”
The company is taking a deliberate, gradual approach as it incorporates more AI so it can stay nimble. “Our goals don't change, it's just how we get there and the road we're taking,” said Russo. “It's another road, it's a better road – it's the highway.”
AI serving savings for ezCater
Corporate procurement is more complicated than it might sound. There may be changes in headcounts, food preferences and dietary restrictions, as well as other logistical challenges.
ezCater continues to grow in this space, and as it is, the level of high-touch service required to solve customer needs can be difficult to scale without use of technology, Erin DeCesare, CTO of the workplace procurement platform, told VentureBeat.
But once the company implements Salesforce's Agentforce, a customer who needs a change order will be able to communicate their needs with AI in natural language, and the agent will Center AI changes automatically. When more complex issues arise – such as rescheduling an order or changing an outdoor location – the AI agent quickly pushes the issue up to a human representative.
“This is a huge cost savings for us,” DeCesare said.
Another intended use case is “restaurant discovery” – that is, AI Agents they will be able to direct users to the best place based on information about their food preferences, budget, location and other factors. This is supported by data from millions of workplace food orders. “This is what NLP and AI are perfect for,” DeCesare said.
ezCater is the first to bring in-house AI agents to help concierge agents, and the human agents love it, she reports. “We're giving them tools to be better, and to be able to handle more calls. “
There has also been a change in the comfort level of engineers, as they are able to imagine agents in a more structured way. “They can test and trust in a way that feels like software development,” DeCesare said. “It's more like what they would expect in the software development life cycle.”
Business partners are also excited about the possibilities for activities such as business analysis or process maps. “The technology has become so accessible in the last six months,” DeCesare said. “You can easily see how this will quickly become the norm. We are going to be in a very different world 12 months from now.”
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