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Everyone is talking about AI agents. But so far, a lot of that has just been, well, talk.
That is set to change in 2025, according to Salesforce — AI agents are finally getting real. According to a new survey from its integration and automation software company Mulesoft, 93% of enterprise IT leaders have implemented or planned to implement AI agents in the next two years.
Still, enterprises continue to struggle with delivery times — for instance, 29% missed their delivery goals in 2024 — and 80% say data integration is one of their biggest challenges when using AI.
“Integration challenges hinder companies from fully realizing the technology’s potential to create a limitless digital workforce,” Andrew Comstock, SVP and GM of MuleSoft, told VentureBeat. “Integration is incredibly foundational to making AI agents work because AI agent outputs depend on connected data that enables a comprehensive understanding of the context and nuances within user queries.”
Enterprises still struggle, but are seeing AI take shape
Salesforce’s 10th annual MuleSoft Connectivity Benchmark Report surveyed 1,050 enterprise IT leaders. One of the key findings was that organizations today use 897 apps on average. Further, the number of AI models organizations use has doubled (from nine in 2024 to 18 this year), and organizations using agents have roughly 22 AI models deployed, significantly more than those not yet using agents (15).
However, only about 29% of those apps are connected, and the majority of respondents (95%) say they struggle to integrate data across systems.
Comstock explained that such integration issues impact agent accuracy and usefulness; they need to gather structured and unstructured data from diverse sources, including enterprise resource planning (ERP), customer relationship management (CRM) and human capital management (HCM) platforms, as well as emails, PDFs, Slack and other systems to make decisions and take action.
IT leaders do see great value in application programming interfaces (APIs) — which allow different apps to talk to each other — saying they are beneficial when it comes to improving IT infrastructure, sharing data across teams and integrating disparate systems.
With correct integration and APIs, agents “can interact directly with their existing systems, automations and other agents across the enterprise, so that they don’t have to refit everything for the AI world,” said Comstock.
The survey also found that IT leaders are expecting an 18% increase in projects this year, and will spend an average of $16.9 million on IT staff in 2024, more than double the average in 2023. Yet nearly 40% of IT teams’ time is still spent on designing, building and testing new integrations between systems and data.
“That’s an incredibly high percentage to spend on cumbersome work,” Comstock pointed out. “Every IT [team] has more work to do than resources available, leading to backlogs, delays and inefficiencies. Agents, we believe, can close the IT delivery gap.”
Indeed, the vast majority of IT leaders polled (93%) say that AI will increase the productivity of their developers over the next three years.
“A digital labor workforce can act autonomously in a business to successfully carry out both simple and complex tasks, enabling increased productivity and efficiency,” said Comstock. He noted that enterprises will eventually move beyond simple AI agents to “super agents,” which don’t just respond to a single command, but pursue a goal and perform complex human tasks.
Bottom line: Enterprise leaders are already seeing — and experiencing — AI at work. As evidenced as recently as this week, “DeepSeek has changed the baseline of what we think we can do,” said Comstock.
“We’re seeing more readiness to talk about the things that AI is going to do, more than just sort of behind the scenes,” he said. “What we’re seeing from these benchmark studies is that IT leaders are ready for that conversation.”
How PenFed Credit Union and Adecco are using AI agents
PenFed Credit Union is one Salesforce customer already seeing the benefit of AI agents. In less than eight weeks, the country’s third-largest federal credit union set up two new support channels — live agent chat and chatbots built on Agentforce — with just one engineer.
The company is using Mulesoft to gather data into one unified platform. This gives service agents a 360-degree view of member data, Comstock explained, allowing them to provide better and faster support with live chat and self-service support options. Branch representatives can also handle multiple types of customer requests in a single window.
As a result, PenFed now resolves 20% of cases on first contact with AI-powered chatbots, increasing chat and chatbot activity by 223% in the past year. Coincidentally or not, the credit union has also increased membership by 31%.
“Members get channels of choice when they need help,” Comstock explained. “They’re enjoying short wait times because they’re not repeating the same information when they talk to service representatives, because the information is being connected together more effectively.”
Leading talent company Adecco, meanwhile, is using Agentforce, MuleSoft and Salesforce Data Cloud to centralize more than 40 disparate systems. The company processes 300 million applications a year and places 1 million people daily. However, with its traditional tooling, its recruiters can only respond to a fraction of the applications it receives, unintentionally ghosting a significant number of candidates.
To address this problem, Agentforce will autonomously and automatically sift through resumes and pull together shortlists of candidates based on preset criteria such as skills, experience or location. After passing that list off to human recruiters, the model will then notify candidates who weren’t a good fit and suggest alternative roles. The goal: to eventually respond to 100% of applicants, Comstock explained.
Similarly, Agentforce will help with job postings, identifying the most effective job boards and platforms based on past success rates and regional needs. This will remove the need for recruiters to manually publish listings.
“It’s about ‘How effective can we make our employees and free them up to do the most important part of their job, the pieces that are really differentiating and providing value?’,” Comstock noted.
He pointed to other examples where AI agents could reach out on behalf of a worker who is sick on a given day and needs to find a replacement. Or, a product agent can answer questions and provide documentation, and, when asked about something out of its purview, communicate with other agents to get the answer.
“You can attack customer service, you can attack employee success, you can attack a variety of different vectors,” said Comstock.
Feedback loops will speed up later adoption
As enterprises adopt AI agents, they’ll experience an accelerated feedback loop, Comstock noted: Their next set of deployed agents will only get faster and more intelligent.
“That cycle is something that we’re going to start seeing the best companies adopt, and it’s going to be an incredible differentiator for them as they’re thinking about how they build their business,” he said.
He pointed out that he doesn’t see agents — at least “as they’re currently constructed” — replacing people. Instead it’s an “incredible complement” to what humans are doing, allowing them to scale more effectively and do the work they’ve been wishing they could get to.
“It’s exciting, because this is where it’s real,” said Comstock. “This is where it’s moving beyond the conceptual. People are putting agents in place and are able to measure positive returns, whether from a top-line or bottom-line impact to their business.”
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