If you still haven’t explored the evolving use cases for AI agents in customer service – now’s the time to dive in. More than just a new flavor of conversational or generative AI, AI agents allow companies to build bots that can set goals, make decisions, and adapt proactively to various situations. You can probably see why that’s so beneficial in the customer service space.
Unlike your standard chatbots, AI agent solutions can automate everything from resolving complex queries at lightning speed to predicting customer pain points before they arise. Agentic tools can even handle multi-stage onboarding tasks.
- Ready to learn more about AI agent’s potential? Check out our guide to AI agents’ impact on employee productivity here. Alternatively, start your journey into the future of artificial intelligence with our guide to successfully integrating AI agents into your workflows.
Now that plenty of platforms and tools are available to help companies build the ideal AI agent team, there’s never been a better time to start diving into the opportunities. Here’s your guide to the evolving impact of AI agents in customer service.
Use Cases for AI Agents in Customer Service
AI agents are a major step forward in the world of artificial intelligence. Even the most advanced generative AI and conversational AI bots are primarily “reactive” tools, responding to specific requests and prompts. AI agents are autonomous, goal-oriented, and proactive.
It can create plans to reach specific goals (and adapt them in real time), work with other tools and applications in your ecosystem, like your CRM platform or databases, and even handle a full step-by-step process without input, such as identifying and implementing supply chain optimization strategies. Here’s a quick rundown of some example use cases for AI agents in customer service.
Answering Common Queries
Traditional chatbots can answer FAQs, but they’re limited in what they can actually “do” for a customer. AI agents offer more flexibility, interpreting nuanced customer inquiries, learning from past conversations, and even adjusting their tone to match a customer’s emotional state.
Agents can even act “proactively”. For instance, in the healthcare industry, an AI tool could monitor a customer’s records and send reminders for them to book a check-up or appointment.
Troubleshooting Technical Issues
While traditional AI systems rely on decision trees or pre-set workflows, AI agents can autonomously diagnose and resolve complex issues. For example, Vodafone uses Agentic AI to assist customers with internet or device connectivity problems.
Instead of merely following a script, the system can dynamically adapt its approach, running diagnostics, suggesting tailored solutions, or even remotely resolving issues without human intervention.
Completing Repetitive Tasks
While many standard AI chatbots can answer common questions, they often need to hand an issue over to an agent to initiate action. Since AI agent tools can integrate with payment processing systems, and other business tools, they can complete tasks autonomously.
For instance, an AI agent system can assess claims made by an ecommerce customer about damaged goods and late delivery times, identify evidence, and issue refunds immediately. They can also use guardrails to determine when to flag issues for human review – reducing the risk of mistakes.
Enabling Personalization at Scale
Customers today expect personalization, but it’s often difficult for companies to deliver at scale. AI agents can help, integrating with existing CRM systems and data platforms, to personalize each discussion with every customer.
For instance, the AAA group used Salesforces’ Agentforce platform to create an agent capable of not only handling support requests, but making relevant product suggestions. The agent can look at a user’s account and identify services they might be interested in exploring, such as a safe driving school service for a learner driver.
Supporting Human Agents
AI agents in customer service isn’t just a powerful tool for boosting customer experiences. It can augment and support agents, too. AI agent tools can help customer service teams plan schedules, automate specific tasks, and even access real-time guidance during calls and chats.
As an example, if an agent is dealing with a particularly complex issue, the AI can surface relevant knowledgebase articles, suggest troubleshooting tips, or notify a supervisor that help is needed. All of this speeds up resolution times and improves agent engagement.
Benefits of AI Agents in Customer Service
AI agents aren’t just a new trend – it’s a game-changer, particularly in the customer service space. Unlike traditional AI, agentic AI brings autonomy, proactivity, and constant learning into customer service strategies; companies benefit from:
Faster Response Times and 24/7 Availability
While most forms of AI can accelerate issue resolution times and support customers 24/7, AI agents in customer service take things to the next level. AI agent solutions don’t just answer questions; they troubleshoot issues, complete tasks, and deliver incredible results.
For instance, HappyFox used AI agent tools powered by Amazon Bedrock to automate ticket resolution by 40%, boost agent productivity by 30%, and enhance customer experiences.
Improving Agent Efficiency
Just like most types of artificial intelligence, agentic AI is great for automating repetitive tasks in customer service. However, unlike old-fashioned AI tools, agentic solutions can automate multi-stage processes, without human intervention – from processing refunds to updating account details.
McKinsey, for example, created an agent with Copilot Studio that speeds up the client onboarding process, reducing lead times by 90% and administrative work by 30%. Thomson Reuters created an agent that automates various elements of the legal due diligence workflow, meaning many tasks can now be completed in half the time.
Enhancing Customer Satisfaction
With its ability to provide faster, more accurate, and highly personalized responses, AI agents in customer service has a massive impact on satisfaction rates. AI agent tools can immediately draw from CRM data to personalize customer conversations at scale, suggest relevant products and services to each customer, and even deliver proactive customer support.
Plus, since AI agents can support agents in real-time, helping them to resolve issues faster and automate tasks, these tools reduce problem resolution times too.
Enabling Scalability for Growing Businesses
With AI agents in customer service, scaling is much easier. Companies don’t need to invest in additional employees to offer multilingual 24/7 service to customers, handle data processing tasks, and more. They can accomplish “more with less”.
For example, Twitch used Amazon Bedrock to create AI agents to help its teams scale after discovering customers had to wait hours for answers to questions. The AI agent technology allowed the company to scale its service strategy and even increase its revenue by 25%.
Providing Access to Data-Driven Insights
Finally, agentic AI tools can help companies get more value from their data. Agentic systems can analyze every interaction based on a company’s goals, uncovering trends, pain points, and opportunities for improvement.
With AI agents, organizations can quickly uncover opportunities to improve customer support strategies, enhance sales and marketing campaigns, and even produce more effective products. The result is faster, more efficient growth and innovation.
Embracing AI Agents in Customer Service
The challenges facing today’s customer service teams are constantly evolving. Customers want faster, more personalized, more efficient interactions across every channel. AI agents offer companies a way to live up to these new expectations.
With its ability to draw from existing data, use business tools, and complete a number of multi-stage tasks autonomously, agentic AI is becoming the ultimate powerhouse for customer-facing teams.
