How Capital One built production multi-agent AI workflows to power enterprise use cases

Compared to non-users, daily AI users are more likely to report “very good” when it comes to productivity (64%) focus (58%) and job satisfaction (81%). According to the Index, Millennials are emerging as the surprise AI power user at work as 30% of this cohort say they thoroughly understand AI agents. Sixty-eight percent Millennials use AI for strategic work like drafting, summarizing, and ideating as 43% of executives report daily AI use, compared to 35% of senior managers and 23% of middle managers. The most recent survey ss a departure from earlier trends those had shown were slower to adopt AI than executives. But in the past few months, 60% of desk workers now using AI and 40% using AI agents. The partnership reflects broader trends in both the AI and identity verification industries.

Call Center Leaders Don’t Listen to Agents, Enough

The platform now resolves 84% of customer queries autonomously, has led to a 5% reduction in support case volume, and enabled the company to redeploy 500 human support engineers to higher-value roles. The partnership comes amid broader scrutiny of AI’s role in education, with institutions grappling with questions of academic integrity and the appropriate use of AI tools. By requiring verification and emphasizing accuracy, both companies aim to address these concerns while expanding access to AI capabilities. However, the company sees strategic value in building relationships with academic users. Unlike many tech companies that monetize through advertising, Dwyer said ads represent “less than a half of a percent of our revenue” and the company doesn’t sell user data. Based on their intuition of how human agents reason while responding to customers, researchers at Capital One developed  a framework in which  a team of expert AI agents, each with different expertise, come together and solve a problem.

Voice interfaces and multilingual support drive Salesforce’s next phase of AI agent evolution

The company’s CEO, Misha Laskin, says the ideal way to build supersmart AI agents is to have them truly master coding, since this is the simplest, most natural way for them to interact with the world. While other companies are building agents that use human user interfaces and browse the web, Laskin, who previously worked on Gemini and agents at Google DeepMind, says this hardly comes naturally to a large language model. Laskin adds that teaching AI to make sense of software development will also produce much more useful coding assistants. If leaders want successful AI integration, they must shift from automation at all costs to collaboration with purpose—communicating clearly, training intentionally and building AI that serves both customers and agents. The call center of the future depends not just on smarter machines, but on smarter leadership. Where AI certainly has enormous potential and has produced real results in the customer service and support arena, it’s a tender moment for the contact center agents who have to execute these marketing and technology promises of AI in customer experience.

Call Center Jobs Aren’t Disappearing—They’re Evolving

His expertise training AI models to reason and play games is being applied to having them build code and do other useful chores. Daniel Jackson, a computer scientist at Massachusetts Institute of Technology, says Reflection’s approach seems promising given the broader scope of its information gathering. Jackson adds, however, that the benefits of the approach remain to be seen, and the company’s survey is not enough to convince him of broad benefits. He notes that the approach could also increase computation costs and potentially create new security issues. Another call center worker described the monotonous nature of routine B2B inquiries and the increasing reliance on low-cost, outsourced labor that often feels disconnected and underqualified.

Conveyor Raises $20M B2B for Agentic AI Development

More recently, AI-driven voice bots have started handling some of these calls with surprisingly fluent language mimicry, signaling how far automation has come. “I hate to say, but employees will likely prefer the AI vs. slanted evaluators who may perceive things differently call to call,” one Reddit commenter, be_just_this, posted on a thread about how long it will take for AI to replace contact center agents.” We give you the inside scoop on what companies are doing with generative AI, from regulatory shifts to practical deployments, so you can share insights for maximum ROI. Salesforce’s experience also revealed critical lessons about content management that many enterprises overlook when deploying AI. Despite having 740,000 pieces of content across multiple languages, the company discovered that abundance created its own problems.

The Fear Is Real—and Grounded in Experience

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• Their first multi-agentic workflow was Chat Concierge, deployed through the company’s auto business.
• Like many other AI agents — an often more capable and autonomous assistant, compared to a chatbot — Zoom’s newly upgraded AI Companion is being promoted to businesses and working professionals as a tool that can help streamline day-to-day work routines.
• The company has already expanded Agentforce to support Japanese using an innovative approach—rather than translating content, the system translates customer queries to English, retrieves relevant information, and translates responses back.
• In this VB Transform session, Milind Naphade, SVP, technology, of AI Foundations at Capital One, offered best practices and lessons learned from real-world experiments and applications for deploying and scaling an agentic workflow.

Here’s a summary of key themes and direct quotes from Reddit conversations about AI in call centers. These insights capture how frontline employees are experiencing and thinking about AI—not just as a tool, but as a force reshaping their careers, workplaces and mental wellbeing. The problem for your contact center agents isn’t artificial intelligence. Some of his frustration stems from his employer demanding that workers stick to a script unerringly, under punishment of losing their job. Seth, another US-based Concentrix employee, estimated to Bloomberg that he’s asked if he’s an AI once a week. One customer grilled him for 20 minutes to see if he was a bot, asking questions about his hobbies.

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Rather than learning to win at a game like Go, the model learns how to build a finished piece of software. Tapping into more data across a company provides more information that will help the AI agent eventually build good quality coding independently. Reflection uses data from human annotators and also generates its own synthetic data. Today the CMSWire community consists of over 5 million influential customer experience, customer service and digital experience leaders, the majority of whom are based in North America and employed by medium to large organizations. Explore the future of AI on August 5 in San Francisco—join Block, GSK, and SAP at Autonomous Workforces to discover how enterprises are scaling multi-agent systems with real-world results. The verification process begins with basic information like name, date of birth, and university.

“I’m approaching about 40 years of being on this journey of operating and financial roles in different industries,” she told Cooper. Many workers are fine with AI that helps—like suggesting next steps or summarizing notes—but object strongly to AI tools that feel invasive or judgmental. “This inability to tell if you’re talking to a human or not is only going to grow,” Nir Eisikovits, professor of philosophy and director of the Applied Ethics Center at the University of Massachusetts, told Bloomberg.

Reflection’s ultimate goal is building superintelligent AI—something that other leading AI labs say they are working toward. Meta recently created a new Superintelligence Lab, promising huge sums to researchers interested in joining its new effort. A minority of agents are already working with AI or proactively training for what’s next. While few believe AI is eliminating jobs wholesale yet, many workers say it’s increasing their workload through inefficiencies, AI hallucinations and broken workflows. I’d be surprised if there was anyone left by this time next year,” u/HausWife88 said.