Today’s customer support teams are faced with the impossible task of managing high volumes of support requests while also providing a high level of customer service. Have you been there? I know I have.
With AI’s ability to create personalized experiences, find efficiencies, and deploy automations, customer support teams are quickly adopting tools like AI agents in their workflows.
While around 45% of customer support teams are already leveraging AI today, that number is expected to grow. Gartner 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.
Are you ready to explore how AI agents can assist customer support teams? In this post I’ll share expert insights, discuss the current AI landscape, and share what I think are the best AI agents for customer support.
In this article:
- What the Rapid Adoption of AI Means for Customer Support Teams
- How Customer Support Reps Use AI
- The 5 Best AI Agents for Customer Support
- AI for Customer Support Agents Continues to Grow
What the Rapid Adoption of AI Means for Customer Support Teams
While it’s normal to worry that AI might put you out of a job, both CX leaders and support reps see the positive potential of using AI for customer support reps. Because when AI manages more “Tier 1” interactions, support reps are able to help with more complex interactions that require human intervention.
In fact, 75% of CX leaders 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’re realizing that using AI for automation frees them up to do more of the work they really enjoy.
I spoke to Kellen Brown, a customer support specialist at Textla, and he echoes this sentiment. He told me, “What I’ve found is that AI helps me actually do my job better. With the help of AI, I’m able to deliver more white glove treatment to customers.”
In other words, what we’re seeing is that equipping your support reps with AI-powered customer service software enables them to handle more support requests while delivering an even better customer experience.
How Customer Support Reps Use AI
The data shows that AI can help reps deliver better service and improve CX, but if you’re like me, you might be wondering: How? Let’s look at a few key use cases for implementing AI into customer support.
1. Automating Manual Tasks
Support reps often have to look in multiple places to find the right documentation or manually complete multi-step requests for customers.
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.
Brown has seen the advantage here.
He tells me that using AI tools “frees 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.”
Reps are using AI to help with things like:
- Answering basic customer questions, gathering customer details, and helping your customers self-serve.
- Analyzing or merging data and quickly finding the information they need to answer a customer‘s questions in real time. (If you’ve ever used Generative AI to get help with a question, you’ll know how powerful this could be for reps to have access to during a live conversation.)
- Surfacing themes and topics that can help you identify knowledge gaps or implement updated support flows.
- Solving multi-step problems. AI agents, specifically, are great at this when they’re integrated into your tech stack and can autonomously complete various tasks or assist reps with task completion.
I’ve 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, resolving customer issues 44% faster, and experiencing a 35% increase in the quality and consistency of support.
2. Expediting Onboarding for New Reps
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.
Ben Gardner, VP of customer care at AvidXchange, told me that “AI 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.”
Here are a few ways that using AI can help your support reps jump into the queue more quickly:
- Allow reps to easily reference previous responses from more tenured reps to help them answer customer questions.
- Automatically surface help docs and articles that are relevant to the topic at hand.
- Analyze previous conversations and offer suggested replies to help reps quickly respond to customers, whether it’s email or live chat.
- AI Agents can even suggest next steps or automatically perform tasks to help reps solve multi-step problems. This can be especially helpful for new reps who may not know how to process a refund or initiate an exchange, for example.
This sort of AI functionality significantly reduces employee ramp time and brings them up to speed much more efficiently.
3. Creating a Consistent Customer Experience at Scale
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.
Here are some areas where I’ve seen AI help with CX at scale:
- By leveraging AI, you can provide 24/7 support to your customers and offer service in a variety of languages. 90% of consumers expect an immediate response to their support questions, so this also benefits the customer by providing a faster time to resolution.
- AI tools allow your team to tackle more high-volume tickets without needing to add more headcount.
- AI also helps you create consistency in responses. When the agent and your human reps are using the same information to provide answers, customers receive consistent responses and support across the board.
- AI can analyze data and surface themes that can help you make important decisions. For example, an AI tool can analyze multiple systems and datasets to show you where customers are typically getting stuck or frustrated, allowing you to make improvements to the customer journey.
- Predictive modeling in AI tooling can help you make decisions about the future — whether it’s running a simulation to see the possible outcomes of changing a customer support flow or predicting trends in customer behavior.
The 5 Best AI Agents for Customer Support
I’ve 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’re in alphabetical order, so no favoritism here!)
1. Ada’s AI Agent
Ada’s AI Agent empowers organizations to offer “instant, proactive, personalized, and effortless support.” By leveraging GPT models, Ada’s 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.
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).
Ada’s AI Agent translates into an impressive 50 languages and supports multiple customer channels, including messaging, voice or email. Ada’s platform allows you to launch proactive support that’s personalized and behavior-based, making it feel like an authentic support interaction.
For example, in the screenshot below, the agent offers support to this customer when it recognizes that they’re setting up their first report.
My favorite features:
- The option to segment your customers and tailor your agent’s responses by geography, channel, and more.
- Support voice, chat, SMS, and email channels.
My overall thoughts: The level of personalization Ada offers excites me. Customers have come to expect 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.
2. Hubspot’s Breeze Customer Agent
Hubspot’s 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.
Breeze Agents are a natural extension of Hubspot’s AI-powered customer service software, adding a layer of automation and front-line support that seamlessly integrates with your existing workflows.
Breeze Agents can help support teams by tackling repetitive or common requests, even those that require an additional step.
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.
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.
Hubspot’s agent promises easy setup and training, and 95% of customers agree that Hubspot’s AI capabilities are easy to use.
My favorite features:
- Breeze Copilot, Hubspot’s AI-powered virtual assistant, can help support reps quickly find information, generate content (or responses), and complete routine tasks.
- Agents cite their sources when they provide a response, which I think is great for transparency.
My overall thoughts: If you’re already using HubSpot, utilizing the Breeze agents is a no-brainer. I really like how they’re built into the software to help at certain touchpoints.
3. MavenAGI’s AI Solution
Harnessing the power of GPT-4, MavenAGI’s agent delivers an elevated support experience in a variety of ways.
MavenAGI’s solution taps into GPT’s 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.
This agent can also assist a customer with things like upgrading their plan, adding more licenses to their subscription, or rebooking their reservation.
In the screenshot below, MavenAGI’s agent has changed a hotel reservation for a customer.
After the task is completed, the agent can also ask intelligent follow-up questions, like asking the customer if they’d like to add a spa package to their hotel reservation.
My favorite features:
- For support reps, MavenAGI can automatically summarize, translate, guide, and suggest solutions, equipping CX teams with the insights they need to assist customers.
- You can train Maven using documentation in any form and format — no need to structure or organize it beforehand.
My overall thoughts: 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’s going to naturally excel at handling robust and nuanced requests from customers and I think it’s sure to drive major efficiencies for businesses via its autonomous task completion.
4. Nice’s AI Agent Platform
Nice’s 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’m going to quickly review two of Nice’s agents, Autopilot and Copilot.
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 — no manual work required.
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.
Nice’s 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.
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.
In the example below, the Copilot suggests adding proactive notifications for orders that are identified as delayed.
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.
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.
My favorite features:
- My favorite feature in this agent is its ability to identify areas of opportunity, create a suggested change, run a simulation to test the change, and fully implement it. This level of automation takes a significant amount of work off of a CX professional’s plate.
- Autopilot’s ability to detect intent and prioritize by ROI.
My overall thoughts: As someone who’s worked in the chatbot space, this platform’s 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.
5. Zendesk’s AI Agent
Zendesk’s AI agent is designed to solve both simple and complex customer issues from end to end. By utilizing Generative AI, Zendesk’s agent can understand a customer’s questions and scan your internal documentation to find the best answer.
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.
Agents can adapt to the conversation in real time and can call on other systems for more information when needed.
In the event that the agent needs to route the conversation to a rep, it uses “Intelligent Triage” 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.
Zendesk’s Co-pilot feature proactively guides human agents through each interaction and can anticipate a customer’s next steps. Copilot can also offer suggestions to the human rep and complete tasks on their behalf.
My favorite features:
- When replying on their own, support reps can type a few bullet points and have the agent change the formatting from bullet points into a few sentences.
- Zendesk’s AI platform offers a variety of reporting, including their Generative AI dashboard that surfaces trending topics to address content updates and training opportunities for the agent.
My overall thoughts: Zendesk’s AI agent has all the bells and whistles that you’d 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’re in a live conversation.
AI for Customer Support Agents Continues to Grow
After digging into these AI agents for customer support, I’m impressed that each agent on this list has its own unique feature that sets it apart. The features I found the most compelling are the agent’s ability to autonomously process CX platform updates and the personalization and segmentation capabilities.
While the AI agent space is growing and changing rapidly, I hope this list of AI agents highlights some new features or use cases to help you leverage AI in your customer support teams.
