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AI Agent vs AI Chatbot: Understanding Their Roles in Modern Customer Support
AI Agent vs AI Chatbot: Understanding Their Roles in Modern Customer Support
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AI chatbots and AI agents—have increasingly become instrumental in reducing ticket queues, streamlining support delivery, and enhancing overall customer experience.
That’s unsurprising, given that AI chatbots can resolve as much as 80% of your routine queries, and 47% of CS specialists believe AI agents can bolster operational workflow. However, it’s quite easy to mix up both solutions and assign them to the wrong roles.
While AI chatbots handle basic requests such as “where is my order?” or “how do I reset my password?”, AI agents are designed to manage more nuanced interactions.
This includes making critical situation analysis based on provided data, handling multi-step processes, and adapting to new contexts.
In this article, we’ll explore their differences and when to use each to modernize your customer support.
What is an AI Chatbot?
An AI chatbot is a program designed to simulate human-like interactions with customers and provide helpful answers to questions. It uses NLP to understand and respond to customers’ queries.
However, AI chatbots are primarily trained on structured datasets and hooked on each end by a stock of rules that define how they respond to user inputs. This makes their responses static, preprogrammed, and lacking in depth of autonomy or self-thinking.
Of course, these restrictions do not make chatbots any inferior to AI agents in helping brands achieve their customer support goals. According to Hubspot’s State of Customer Service report, 91% of CS leaders consider chatbots effective, and 36% consider them essential for making customer service available 24/7.
You can find cases of AI chatbots used in customer service for basic IT support, sales assistance, learning and development, etc.
- Basic IT support: AT&T uses an openAI-powered chatbot to help its employees find quick predefined answers based on the company’s database. The chatbot also simplifies and translates brand documents for easy reading.
- Sales assistance: Sephora uses its chatbot to provide product recommendations, which has helped drive sales by 35% while reducing response time by 40%.
- Learning and development: Duolingo uses AI-powered chatbots to simulate conversations with users in order to enhance interactive language learning and provide real-time feedback.
Amazon and H&M also implement some of the best AI chatbots to reduce ticket load and improve customer service experience.
What is an AI Agent?
An AI agent is a more sophisticated software program designed to execute complex tasks and achieve set goals with minimal help from your support team. Like AI chatbots, AI agents leverage NLP to understand the context of customer input.
However, they also use ML to process requests, engage in complex interactions, and autonomously make accurate decisions like processing refunds.
The cherry on top is that AI agents can utilize reinforcement learning and other adaptive algorithms to grow continuously.
That means they learn from previous interactions to become better at handling tasks and helping your support team scale with increasing levels of difficulty.
According to 8x8’s State of Conversational AI, 54% of organizations say this AI solution has helped streamline their internal workflow and 39% say it has decreased repetitive tasks that are done manually.
AI agents are useful for triaging tickets, escalating complex issues, analyzing customer sentiment, personalizing responses, and streamlining workflow automatically.
- Intelligent ticketing: AI-powered ticketing agents can understand the urgency and difficulty level of each customer complaint. This is useful for setting ticket priority, assigning tickets to the right service rep, or escalating them when necessary.
- Predictive AI: Predictive AI agents can autonomously analyze customer data for patterns and deduce future behaviors, preferences, and potential issues. This enables proactive support delivery.
Outside of customer support, AI agents from brands like Please help users make restaurant reservations by accessing booking websites in real time and confirming their availability, costs, and menu.
AI Agent vs. AI Chatbot: 6 key differences
Let’s see how AI agents and AI chatbots differ.
It’s easy to think of AI chatbots like ChatGPT as AI agents; however, that might not be true.
ChatGPT is semi-agentic; that is, it is an advanced AI chatbot capable of multitasking and performing complex interactions. However, it is not fully autonomous since it cannot make decisions without explicit prompts from users—and that’s the takeaway difference between these two solutions.
When to use AI Chatbots
87% of contact center and IT leaders believe chatbots increase productivity and 63% somewhat agree it will help boost their business’s revenue. But how do you know when to use it to achieve these results?
Scaling first-line support
Most L1 queries are routine and monotonous—and you’ve likely gotten them more than a dozen times. You can use AI chatbots to manage these requests while assigning your service reps to higher-level (L2 and L3) complaints.
Cost efficiency in handling high volumes
The amount of tickets you log increases as your business grows. And that means hiring more hands to sustain delivery, which might be cost ineffective. In this case, you can employ AI chatbots to do the heavy-lifting and save your business over 30% in recruitment costs.
Enhancing response time & customer satisfaction
Consumers now want an immediate response. According to a valuable report from Hubspot, “immediate” can be 10 minutes or even less. If you’re struggling to achieve that, then it’s time to implement an AI chatbot.
Ensuring 24/7 automated support
The clock strikes 9 pm. Your customers are having issues initiating a product refund. And your service reps are off to bed, leaving them with no one to talk to. That’s one of the fastest ways to lose your customers.
If this sounds familiar, getting an AI chatbot may be your next go-to to provide round the clock support.
When to use AI Agents
When you need a self-thinking AI solution that can autonomously handle nuanced tasks rather than a bot that solely depends on prompts, AI agents are your best bet.
Ticket categorization
Logging, sorting, and labeling each ticket manually is draining. Assessing the priority level of each complaint before routing it to the appropriate support tier and rep can also be quite difficult.
If this is you, you might want to use an AI-powered ticketing agent. These agents can autonomously log, categorize, and prioritize incoming tickets using NLP and sentiment analysis without human prompt or intervention.
They also learn from past interactions, refine classification accuracy, and route issues to the right support tier based on urgency, expertise, and workload.
Handling personalized and context-aware interactions
A customer logs a ticket and is frustrated about transferring funds to the wrong account. Your chatbot replies, “We’re sorry this happened. Please check out these articleson how to transfer funds to the right account.”
For an already frustrated customer, things could turn ugly.
Thanks to sentiment analysis, reinforcement learning, and adaptive algorithms, you can use AI agents to avert such situations. AI agents can understand the customers' emotions, dig up the necessary data, and walk them through personalized assistance.
In fact, 76% of consumers say personalization is essential in deciding whether to repurchase from a brand or not.
Automating end-to-end customer workflows
Customer workflows for escalating hard-to-resolve queries and providing proactive customer service are often disconnected. They’re usually a bunch of triggers and branched flows. This results in siloed lapses which can delay support delivery and cap your productivity.
In this case, it is crucial to use AI agents to unify and automate these systems. AI agents can autonomously utilize APIs to fetch customers’ real-time data, analyze ticket status and priority, synchronize with existing workflows, and use the resulting analysis to trigger escalation or predictive and proactive support.
AI Agents vs. AI Chatbots: Which one should you use?
Both! You can use AI chatbots to resolve the majority of your routine requests and give back time to your human agents so they can focus on core tasks.
At the same time, you can integrate AI agents to automate your workflows, make real-time decisions, and integrate seamlessly with backend systems for complex issue resolution, escalations, and proactive support.
Combining both solutions ensures no gap is left in your customer support.
It’s also important to note that advanced AI chatbots, not simple rule-based and scripted models, can function as an AI agent.
For instance, Plivo CX’s openAI-powered AI chatbot can leverage your database in real-time to make decisions, autonomously handle refund requests, modify orders, and make personalized recommendations.
Modernizing your customer support with Plivo CX’s AI agents
AI is at the heart of every scalable customer support. But finding the right AI agents to use can be daunting.
And that’s where Plivo CX comes in. This all-in-one omnichannel communication platform offers openAI-powered agentic chatbots, automated workflow builders for escalations, and proactive support solutions—seamlessly integrating AI agents to optimize every customer interaction.
We also offer:
- Unified communication: Manage all customer conversations across channels like email, voice, SMS, WhatsApp, and live chat from a single, agent-friendly platform.
- Seamless integrations: Connect Plivo CX with your existing tools, including CRM, ERP, helpdesk, and more.
- Data-driven optimization: Track real-time analytics and generate custom reports to gain insights into customer interactions and agent performance.
- AI-enhanced efficiency: Prioritize urgent tickets, ensure brand consistency, and adapt quickly to changes with AI-powered support.
- Rich communication: Enhance interactions with multimedia support, including images, videos, and documents.
- Increased productivity: Streamline workflows with message templates, internal notes, and skills-based routing.
- Comprehensive features: Leverage call recording, IVR, multi-language support, and robust security features for a complete solution.
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