Customer support has come a long way in recent years. What once was dominated by simple chatbots following rigid scripts has now evolved into intelligent, autonomous AI agents that truly understand context and can take meaningful action. These advanced AI systems don’t just respond—they triage issues, escalate when needed, summarise conversations, and even resolve problems on their own. This evolution is changing how companies handle support and, ultimately, how customers experience service.
At DevRev’s recent roundtable, leaders from Dhruv Agrawal-Co-Founder and COO at Shipsy, Srinivasa Rao Boniga-Director of Engineering at Phenom, Connor Wells-Strategic Operations at Velocity Global, Chelsey Fewer-Principal Support Engineer at Bolt, Elec Boothe-Support Manager at Bolt, Matt Boyden-Sr. Technical Support Engineer at Nooks, Alan Peterson-Senior Trading Operations Analyst at Integral Development Inc and our own product and support teams came together to discuss how this new generation of AI-powered agents is reshaping enterprise customer support from the inside out. Here’s what emerged as the key ways AI is already making a difference.
1. AI Agents Are More Than Scripts
In the past, chatbots worked based on decision trees and static scripts that could only handle straightforward questions. Today’s AI agents are designed to be much smarter—they understand the context behind each interaction, can adapt to changing circumstances, and collaborate seamlessly with human agents. This shift means customers get faster, more accurate responses, and support teams can focus on solving complex problems instead of repeating the same tasks.
The AI ‘thank you’ detector has been a small but powerful feature, making a big difference in how quickly we resolve tickets and reduce noise in the queue,” shared Connor Wells-Strategic Operations at Velocity Global
2. Smarter Workflows Reduce Resolution Times
One of the biggest benefits of AI in support is intelligent ticket routing. Instead of random or manual assignment, AI systems analyze factors like agent expertise, current backlog, and even time zones to make sure every ticket lands with the right person. At DevRev, this means engineers get involved early when needed, speeding up resolutions. Additionally, simple but powerful features like an AI-powered “thank you” detector can spot when customers have confirmed their issue is resolved and automatically close tickets. This helps reduce backlog by up to 60%, allowing support teams to stay on top of demand without burning out.
“Automation has transformed how our support agents spend their time. They’re no longer bogged down with mundane tasks but can engage meaningfully with customers,” explained Chelsey Fewer-Principal Support Engineer at Bolt.
3. Automation Creates Space for Human Connection
While AI takes over repetitive, low-value tasks such as data entry or routine replies, human agents are freed up to engage in conversations that require empathy, creativity, and critical thinking. This balance creates more meaningful moments with customers. Instead of being bogged down by mundane tasks, agents can focus on listening, problem-solving, and building real relationships that drive satisfaction and loyalty.
4. Breaking Down Silos With Unified Knowledge
Many support teams struggle with fragmented information spread across multiple systems - Jira for engineering issues, Salesforce for customer data, internal knowledge bases, and more. AI helps bring all these pieces together by surfacing the most relevant knowledge and resources right when agents need them. This unified, context-rich view eliminates the need to jump between platforms and empowers teams to deliver quicker and more accurate solutions.
5. Proactive Support Prevents Problems Before They Escalate
Sentiment analysis is one of the more powerful AI tools in support today. By reading between the lines of customer messages, AI can detect early signs of frustration or dissatisfaction and alert agents before issues spiral out of control. This lets teams act proactively, resolving concerns before they become bigger problems and ultimately strengthening customer trust.
Srinivasa Rao Boniga-Director of Engineering at Phenom shared how sentiment insights give agents critical context, empowering them to address problems before they grow.
6. Support as a Source of Product Intelligence
Support isn’t just about fixing problems, it’s also a valuable source of insights for product teams. At Shipsy, for example, they built an AI-powered ticket quality validator that reviews tickets before they reach product managers, ensuring only well-formed, actionable reports get through. This means engineering and product teams receive cleaner data that can directly inform product roadmaps, catch regression patterns, and track customer sentiment in a structured way. Treating support data as a product signal rather than noise opens the door to smarter product development driven by real user feedback.
7. Moving From Reaction to Proactive Engagement
The traditional view of support as a reactive, cost-centered function is shifting. With AI providing deeper insights and automations, support teams are now engaging customers more proactively. Instead of waiting for problems to arise, teams can anticipate issues, prioritize high-impact tickets, and build stronger, longer-lasting customer relationships.
Looking Ahead
The roundtable made it clear: support is no longer just a place to fix problems, it’s becoming a strategic function powered by AI and led by human insight. Companies are moving away from measuring success solely by speed or deflection, focusing instead on real outcomes—did the solution actually work? Did the customer’s experience improve? Did the product evolve?
This evolution is just beginning. As AI continues to improve, support teams will be empowered to deliver even more personalised, effective service while also driving product innovation and business growth.
The future of customer support is bright. It’s human-led, AI-powered, and deeply connected to what customers need most.
