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<\/a><\/p>\nWhile around 45%<\/a> of customer support teams are already leveraging AI today, that number is expected to grow. Gartner<\/a> predicts that in 2025, AI will be involved in 80% of customer interactions. And companies that embrace AI can benefit from more than just efficiency.<\/p>\n Are you ready to explore how AI agents can assist customer support teams? In this post I\u2019ll share expert insights, discuss the current AI landscape, and share what I think are the best AI agents for customer support.<\/p>\n In this article:<\/strong><\/p>\n <\/a> <\/p>\n While it\u2019s normal to worry that AI might put you out of a job<\/a>, both CX leaders and support reps see the positive potential of using AI for customer support reps. Because when AI manages more \u201cTier 1\u201d interactions, support reps are able to help with more complex interactions that require human intervention.<\/p>\n In fact, 75% of CX leaders<\/a> see AI as a force for amplifying human intelligence, not replacing it. And as customer-facing reps (like me!) lean more into using AI in their daily workflows, they\u2019re realizing that using AI for automation frees them up to do more of the work they really enjoy.<\/p>\n I spoke to Kellen Brown<\/a>, a customer support specialist at Textla<\/a>, and he echoes this sentiment. He told me, \u201cWhat I\u2019ve found is that AI helps me actually do my job better. With the help of AI, I\u2019m able to deliver more white glove treatment to customers.\u201d<\/p>\n In other words, what we\u2019re seeing is that equipping your support reps with AI-powered customer service software<\/a> enables them to handle more support requests while delivering an even better customer experience.<\/p>\n <\/a> <\/p>\n The data shows that AI can help reps deliver better service and improve CX, but if you\u2019re like me, you might be wondering: How<\/em>? Let\u2019s look at a few key use cases for implementing AI into customer support.<\/p>\n Support reps often have to look in multiple places to find the right documentation or manually complete multi-step requests for customers.<\/p>\n Implementing AI in support workflows can help with managing the more time-consuming or repetitive parts of customer support, which frees up your reps for more complex support cases.<\/p>\n Brown has seen the advantage here.<\/p>\n He tells me that using AI tools \u201cfrees me up to be more hands-on with customers that have more complex problems. I really want to help customers solve those nuanced problems, and when I have the capacity to do that instead of just sending them instructions on how to do it on their own, our customers really remember that and appreciate it.\u201d<\/p>\n Reps are using AI to help with things like:<\/strong><\/p>\n I\u2019ve seen how efficiencies like these add up to tangible outcomes. Data shows that AI-enabled customer service teams have reported saving 45% of the time spent on calls<\/a>, resolving customer issues 44% faster, and experiencing a 35% increase in the quality and consistency of support.<\/p>\n A new support rep often faces a steep learning curve when joining a new company. CX leaders are leveraging AI to help their support reps ramp faster and provide a consistent customer experience.<\/p>\n Ben Gardner<\/a>, VP of customer care at AvidXchange<\/a>, told me that \u201cAI Agents enable faster ramp time for teammates because they help with finding answers and validating information more quickly. They also help with things like calls and training for new team members.\u201d<\/p>\n Here are<\/strong> a few ways that using AI can help your support reps jump into the queue more quickly:<\/strong><\/p>\n This sort of AI functionality significantly reduces employee ramp time and brings them up to speed much more efficiently.<\/p>\n Having AI serve as the front line in your customer support strategy allows you to scale your customer support function in a multitude of ways.<\/p>\n Here are some areas where I\u2019ve seen AI help with CX at scale:<\/strong><\/p>\n <\/a> <\/p>\n I\u2019ve talked a lot about how AI agents can help your customer support teams, but now the rubber meets the road. Here are five AI agents built for customer service that are at the top of my list right now. (They\u2019re in alphabetical order, so no favoritism here!)<\/p>\n Ada\u2019s AI Agent empowers organizations to offer \u201cinstant, proactive, personalized, and effortless support.\u201d By leveraging GPT models, Ada\u2019s agent is able to have robust conversations, understand nuance and sentiment, and continuously learn and adapt. It surfaces key insights like conversation topics so you can efficiently train your model.<\/p>\n You can test your agent with simulations, coach your agent to follow rules and guidance, and set it up to complete multi-step processes (like processing a return, in this example).<\/p>\n Source<\/em><\/a><\/p>\n Ada\u2019s AI Agent translates into an impressive 50 languages and supports multiple customer channels, including messaging, voice or email. Ada\u2019s platform allows you to launch proactive support that\u2019s personalized and behavior-based, making it feel like an authentic support interaction.<\/p>\n For example, in the screenshot below, the agent offers support to this customer when it recognizes that they\u2019re setting up their first report.<\/p>\n Source<\/em><\/a><\/p>\n My favorite features:<\/strong><\/p>\n My overall thoughts:<\/strong> The level of personalization Ada offers excites me. Customers have come to expect<\/a> personalization and data proves that personalized engagements drive better results. I think using an AI Agent like Ada to drive proactive and segmented support could be a game changer for CX leaders.<\/p>\n Hubspot\u2019s Breeze agents are AI-powered specialists designed to dive deep into a specific subset of tasks and automate workflows. Using Generative AI, these agents engage in natural conversations with your customers on your website and provide instant answers, 24\/7.<\/p>\n Breeze Agents are a natural extension of Hubspot\u2019s AI-powered customer service software<\/a>, adding a layer of automation and front-line support that seamlessly integrates with your existing workflows.<\/p>\n Breeze Agents can help support teams by tackling repetitive or common requests, even those that require an additional step.<\/p>\n Source<\/em><\/a><\/p>\n When creating a workflow for your agent, you can tell it how to evaluate the inputs it receives and then how to categorize those inputs. From there, you can trigger automations for each relevant category, like automatically sending a password reset email to a customer when the agent labels them as locked out of their account.<\/p>\n Or if your agent identifies that a customer is interested in adding more seats to their plan, you could trigger an automation to help the customer complete their upgrade, then trigger an additional action to notify internal teams, like a Slack update or a push to your CRM.<\/p>\n Hubspot\u2019s agent promises easy setup and training, and 95% of customers<\/a> agree that Hubspot\u2019s AI capabilities are easy to use.<\/p>\n Source<\/em><\/a><\/p>\n My favorite<\/strong> features:<\/strong><\/p>\n My overall thoughts:<\/strong> If you\u2019re already using HubSpot, utilizing the Breeze agents is a no-brainer. I really like how they\u2019re built into the software to help at certain touchpoints.<\/p>\n Harnessing the power of GPT-4<\/a>, MavenAGI\u2019s agent delivers an elevated support experience in a variety of ways.<\/p>\n MavenAGI\u2019s solution taps into GPT\u2019s capacity for natural conversation to guide customers to quickly find the answers to many questions on their own, while also being capable of providing personalized answers, taking actions on behalf of the customer and handing off the conversation to a live agent.<\/p>\n This agent can also assist a customer with things like upgrading their plan, adding more licenses to their subscription, or rebooking their reservation.<\/p>\n In the screenshot below, MavenAGI\u2019s agent has changed a hotel reservation for a customer.<\/p>\n Source<\/em><\/a><\/p>\n After the task is completed, the agent can also ask intelligent follow-up questions, like asking the customer if they\u2019d like to add a spa package to their hotel reservation.<\/p>\n My favorite<\/strong> features:<\/strong><\/p>\n My overall thoughts: <\/strong>With backing from OpenAI and their platform being built on GPT-4, I can tell from my research that MavenAGI is a powerhouse of an AI Agent. It\u2019s going to naturally excel at handling robust and nuanced requests from customers and I think it\u2019s sure to drive major efficiencies for businesses via its autonomous task completion.<\/p>\n Nice\u2019s CXone Mpower platform allows businesses to orchestrate and scale customer service workflows, agents, and knowledge. With Nice, Automation is the name of the game. I\u2019m going to quickly review two of Nice\u2019s agents, Autopilot and Copilot.<\/p>\n Autopilot uncovers customer intent, prioritizes that intent by ROI, and then identifies and suggests new paths for optimal outcomes. Autopilot can then take it a step further and actually build out those new paths as botflows \u2014 no manual work required.<\/p>\n The Autopilot agent can completely resolve customer issues by helping customers do things like schedule an appointment, transfer money, or as in the screenshot below, sign up for a subscription package and schedule installation.<\/p>\n Source<\/em><\/a><\/p>\n Nice\u2019s other agent, Copilot, is designed for support reps, giving them AI-driven knowledge to drive faster resolutions for customers. Copilot guides reps through conversations, automatically generating suggested replies, surfacing relevant knowledge articles and providing the rep with real-time intent. Copilot can even detect and initiate upsell opportunities and can support multi-step solutions.<\/p>\n What I think makes the CXone Mpower platform really unique is its ability to find opportunities, propose solutions, and implement changes. The platform will automatically analyze data and suggest changes that could lead to better outcomes.<\/p>\n In the example below, the Copilot suggests adding proactive notifications for orders that are identified as delayed.<\/p>\n Source<\/em><\/a><\/p>\n If the admin accepts the proposed changes, the platform can use predictive modeling to run a simulation and show the potential outcomes of making the change.<\/p>\n Source<\/em><\/a><\/p>\n From here, if the admin agrees, then the Copilot will automatically implement the changes and update the flows. Or, the admin can request edits (using natural language) and the model will adapt to the request.<\/p>\n My favorite features:<\/strong><\/p>\n My overall thoughts:<\/strong> As someone who\u2019s worked in the chatbot space, this platform\u2019s ability to identify new paths and flows and make the changes for you is incredibly impressive. If I was a CX leader, this is a feature that would excite me. I think the combination of predictive modeling and autonomous task completion makes this agent a powerful partner for internal teams.<\/p>\n Zendesk\u2019s AI agent is designed to solve both simple and complex customer issues from end to end. By utilizing Generative AI, Zendesk\u2019s agent can understand a customer\u2019s questions and scan your internal documentation to find the best answer.<\/p>\n If the customer needs to take an action, the agent can complete autonomous tasks on behalf of the customer, like purchasing concert tickets and then sending the customer the receipt. It can then go a step further and update the internal order management system on the backend.<\/p>\n Source<\/em><\/a><\/p>\n Agents can adapt to the conversation in real time and can call on other systems for more information when needed.<\/p>\n In the event that the agent needs to route the conversation to a rep, it uses \u201cIntelligent Triage\u201d to connect the customer with the best representative for their specific problem. The agent also provides customer intent, sentiment, and a summary of the ticket for the rep upon transfer.<\/p>\n Source<\/em><\/a><\/p>\n Zendesk\u2019s Co-pilot feature proactively guides human agents through each interaction and can anticipate a customer\u2019s next steps. Copilot can also offer suggestions to the human rep and complete tasks on their behalf.<\/p>\n My favorite features:<\/strong><\/p>\n My overall thoughts:<\/strong> Zendesk\u2019s AI agent has all the bells and whistles that you\u2019d want in a customer support agent. I like that the co-pilot feature still functions as an agent with autonomous capabilities but is designed to support reps when they\u2019re in a live conversation.<\/p>\n\n
What the Rapid Adoption of AI Means for Customer Support Teams<\/h2>\n
How Customer Support Reps Use AI<\/h2>\n
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<\/p>\n1. Automating Manual Tasks<\/h3>\n
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2. Expediting Onboarding for New Reps<\/h3>\n
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<\/p>\n3. Creating a Consistent Customer Experience at Scale<\/h3>\n
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The 5 Best AI Agents for Customer Support<\/h2>\n
1. Ada\u2019s AI Agent<\/a><\/h3>\n
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<\/p>\n![\"interface](\"http:\/\/www.backstagelenses.com\/wp-content\/uploads\/2025\/05\/ai-for-customer-support-agents-5-20250515-2260857.webp\" "\\"\\"")
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2. Hubspot\u2019s Breeze Customer Agent<\/a><\/h3>\n
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<\/p>\n![\"ai](\"http:\/\/www.backstagelenses.com\/wp-content\/uploads\/2025\/05\/ai-for-customer-support-agents-7-20250515-1757565.webp\" "\\"\\"")
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3. MavenAGI’s AI Solution<\/a><\/h3>\n
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4. Nice’s AI Agent Platform<\/a><\/h3>\n
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<\/p>\n![\"ai](\"http:\/\/www.backstagelenses.com\/wp-content\/uploads\/2025\/05\/ai-for-customer-support-agents-10-20250515-866564.webp\" "\\"\\"")
<\/p>\n![\"ai](\"http:\/\/www.backstagelenses.com\/wp-content\/uploads\/2025\/05\/ai-for-customer-support-agents-11-20250515-7008386.webp\" "\\"\\"")
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5. Zendesk’s AI Agent<\/a><\/h3>\n
![\"example](\"http:\/\/www.backstagelenses.com\/wp-content\/uploads\/2025\/05\/ai-for-customer-support-agents-12-20250515-2347586.webp\" "\\"\\"")
<\/p>\n![\"example](\"http:\/\/www.backstagelenses.com\/wp-content\/uploads\/2025\/05\/ai-for-customer-support-agents-13-20250515-4373118.webp\" "\\"\\"")
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