Are Chatbots AI? How to Differentiate Chatbots From Conversational AI

How do rule-based chatbots and conversational AI compare?

Here’s an at-a-glance comparison of the similarities and differences between rule-based and conversational AI chatbots.

Both technologies aim to assist users through automated communication in response to language input. Both can answer customer queries and provide general information to website visitors and clients.

However, conversational AI continuously adapts and improves, learning from experience and understanding natural language, context and intent. In contrast, rule-based chatbots follow fixed, scripted responses without the ability to learn or evolve.

Rule-based vs. conversational AI in action

Here are examples of how each technology handles typical scenarios:

Rule-based chatbots handle basic, structured tasks efficiently but are limited to predefined scripts. In contrast, conversational AI chatbots are dynamic, context-aware and adaptive, making them ideal for complex interactions.

What is a rule-based chatbot?

A rule-based chatbot is an automated, programmed system that answers user inputs using “if-then” queries. Rule-based chatbots recognize specific keywords and phrases and then choose from predefined replies to answer questions. They’re often used on websites to answer simple queries regarding a store’s hours, product return policies and more.

These bots can only perform predefined functions and can’t veer away from these set rules. “Rule-based chatbots’ predefined decision trees limit their ability to handle complex or unexpected queries,” explained Deon Nicholas, founder, president and executive chairman at AI-agent ticketing firm Forethought. “They often frustrate users by failing to recognize nuances in language or context, leading to repetitive responses and unresolved issues.”

Though limited, rule-based chatbots have impressive functions. For example, many of the best CRM software platforms can link to website chatbots to access basic customer information like names or recent orders. Still, they can’t remember past conversations or interpret customer data. 

Typical business uses for rule-based chatbots

Implementing rule-based chatbots on your website requires programming “if-then” decision tree paths so the bots know how to respond to queries. You’ll also need to consider your customers’ most frequently asked questions. 

Here are six ways businesses can use rule-based chatbots:

1. Basic FAQs and contact details: Rule-based chatbots are ideal for handling queries about store hours, shipping costs or return policies. They’ll recognize a keyword, such as “hours,” and send a standard reply. However, if the query includes an unrecognized topic, the bot won’t be able to help. 
2. On-site pop-ups: On-site pop-up windows appear in the corner of a website screen with predefined choices like “browse products” and “ask a question.” They’re a proactive way to take users through simple paths. However, they won’t be able to help with nuanced questions. 
3. Appointment or callback requests: Rule-based chatbots can help with simple appointment requests via a step-by-step process. However, it may get stuck if all times are booked unless another decision tree provides alternative options. 
4. Internal help desk for routine tasks: Many organizations use chatbots to log IT tickets or request password resets. However, this requires extensive programming. For example, if someone asks, “How do I connect my phone to the virtual private network?” and this question isn’t programmed into the bot’s decision tree, it won’t be able to assist. 
5. Customer support triage: Like interactive voice response (IVR) systems, rule-based chatbots can help route customer inquiries by asking questions like “Are you calling about a billing or service issue?” However, they struggle with unusual or multi-part requests, such as “I need help with both!” [Related article: Could IVR Systems Improve Your Marketing Company?]
6. Customer feedback: Rule-based chatbots can help collect basic customer feedback, including ratings and short comments. However, they can’t interpret detailed feedback or manage multi-issue complaints. 

What is a conversational AI chatbot?

A conversational AI chatbot is a computer program that mimics human conversation to interact with and answer user questions. Unlike rule-based chatbots, it relies on large language models (LLMs) like ChatGPT to understand and generate responses.

Shauli Mizrahi, co-founder and chief technology officer (CTO) of chatbot provider Rep AI, emphasized that conversational AI tools can respond to a vast range of topics using real-world knowledge. “AI-based chatbots are built based on LLMs, which are trained over the entire content of the internet,” Mizrahi explained.

Vlad Shatalo, customer support and billing team manager at Omnisend, highlighted their advanced language abilities. “[LLMs] can understand and process context, as well as respond to human language in a nuanced manner.”

Conversational AI can go far beyond the capabilities of rule-based chatbots. For example, if a customer asked: “Where is my order? I tried changing the shipping address, but I’m not sure if it worked,” here’s how both technologies might respond: 

• Rule-based chatbot: “I’m sorry, I don’t understand. Please visit our shipping page or contact support.”
• Conversational AI: “I see you placed an order for a pair of running shoes on Tuesday. You changed the address to 22 High Street yesterday and the shipment is en route. Would you like me to confirm any other details?”

Conversational AI tools can also remember past interactions. When integrated with a customer’s order history and service records, AI chatbots allow users to resume conversations from weeks or even months ago, helping create a great customer experience.

Typical business uses for AI chatbots

Businesses train their conversational AI systems by feeding them crucial company data, including product databases, shipping and handling rules, refund policies and more. Since AI chatbots pull responses directly from this data, customers and employees receive accurate, up-to-date information.

Here are some ways businesses are using conversational AI to improve e-commerce functions, appointment-setting, customer service, social media management, HR and employee management and business operations.

E-commerce functions

• Reduce abandoned shopping carts: Conversational AI chatbots detect when shoppers abandon their carts and can proactively reengage them by offering assistance or discounts, answering product questions or sending follow-up reminders via email or chat. Mizrahi, whose firm provides digital assistants, emphasized how these tools can drive sales. “[A] conversational sales concierge behaves like a skilled sales rep, only it’s available 24/7, guiding shoppers who are on the verge of abandoning their carts,” Mizrahi explained. “The result has been an uplift in conversions, average order values and sales volumes.” 
• Recommend products: When a shopper hovers over an item, conversational AI can suggest similar products based on the store’s inventory. Nicholas noted that AI can also track previously viewed items to enhance upselling and cross-selling. “A retail chatbot can suggest accessories like memory cards when a customer buys a camera, boosting upsell and cross-sell opportunities,” Nicholas explained. “These interactions drive customer satisfaction by streamlining and improving the customer journey.” 
• Offer personalized sales assistance: Daryle Serrant of byteSolid Solutions noted that chatbots can mimic in-person sales assistance. “For example, a hardware store customer who needs assistance with a do-it-yourself project could interact with a chatbot that offers personalized advice, recommends specific products and answers follow-up questions,” Serrant explained.
• Optimize product descriptions: Poor product descriptions are a leading cause of e-commerce returns. AI chatbots can help by providing detailed product specifications, instructions and more, helping reduce return rates.

Online appointment-setting

• Automate scheduling: Conversational AI chatbots can engage website and social media visitors, collect details about their needs and schedule meetings or product demos for customers with your sales team.
• Qualify leads and prioritize high-value prospects: Conversational AI chatbots can assess conversations based on predefined criteria, such as budget range, and automatically transfer high-value leads to a human sales rep for immediate follow-up.

Customer service functions

• Provide 24/7 customer support: Conversational AI chatbots ensure continuous assistance, handling inquiries on order status, password resets, delivery instructions and more. “The one area where they really have traditional customer service beat is that they’re available 24/7, 365 days of the year,” noted Brianna Mills, founder and CEO of lead generation firm I Bot Time Automations. “So, even if you’re shopping online on Christmas, there is still ‘someone’ there to answer your questions about a product.”
• Resolve issues without human intervention: Chatbots can handle many support tasks independently, reducing wait times and human workload. “[Our platform] resolves 13 percent of contacts with no human intervention,” Shatalo noted. Nick Smith, president, CEO and founder of AI prospecting tool Sailes, added that chatbots “reduce the burden of repetitive responses from your human team, freeing up agents for higher-value tasks.”
• Optimize call center efficiency: Conversational AI can collect details before escalating to a live agent, reducing handling time. Ilya Smirnov, head of the AI department at business software developer Usetech, shared an example where a chatbot gathered shipment details before transferring a call, “reducing live operator time to just 5 minutes after 30 minutes of chatbot interaction, achieving an 85 percent efficiency rate.”

Social media management

• Automate social media responses: AI chatbots can reply instantly to comments and direct messages on social media platforms, ensuring round-the-clock engagement with customers and followers. They can also handle inquiries about store locations, product availability and promotions via your brand’s social channels, keeping potential customers informed without delay.
• Monitor brand mentions and key phrases: AI tools can track social media conversations, detecting when users mention your brand or related topics. Chatbots can then step in with pre-set responses or direct users to relevant resources.
• Seamlessly transition to private messaging: Many AI-enabled CRMs integrate with private messaging apps like WhatsApp and Facebook Messenger, enabling chatbots to move conversations off social platforms when sensitive customer details are needed in a more private setting.
• Support social media marketing teams: By handling routine interactions, AI chatbots free up social media managers to focus on high-impact social media marketing tasks like campaign strategy, content creation and audience engagement.

HR and employee management

• Streamline hiring: AI chatbots can streamline the hiring process by helping recruit new employees. “In the hiring and talent acquisition space, chatbots can assist candidates by answering questions about company policies, job requirements or the status of their applications,” explained Lindsey Zuloaga, chief data scientist at AI-powered HR platform Hirevue.
• Simplify onboarding: Conversational AI can also help manage the onboarding process by connecting their chatbot to their HR and IT systems and uploading documents like employment contracts and employee manuals. 
• Enhance training: AI chatbots can assist with training and report back to managers what new hires are asking to identify any potential gaps in their knowledge.
• Support HR, IT teams and managers: Employees can consult AI chatbots for routine inquiries, such as remaining vacation days or IT troubleshooting, reducing workload for HR, IT and department managers while ensuring instant responses.

Business operation functions

• Personalize pitches: Sales reps and managers can use enriched data and customer histories in AI-powered CRM platforms to tailor sales pitches for complex deals involving multiple decision-makers.
• Streamline business processes: Operations directors and managers can use AI-powered CRM tools to identify inefficiencies, optimize workflows and resolve bottlenecks that lead to delays, excess costs or customer dissatisfaction.
• Assist with decision-making: Business owners can converse with AI chatbots to analyze company-wide data, forecast trends and explore strategic opportunities. While AI won’t replace human judgment, it helps leaders assess multiple scenarios quickly, accelerating the decision-making process.

The future of AI-powered chatbots

The future of AI-powered chatbots looks bright as they evolve into deeply sophisticated tools that can handle complex tasks and serve multiple audiences simultaneously. Consider the following areas expected to grow. 

• Conversational AI in insurance: Pradeep Ganapathryraj, senior VP of product at communications platform Sinch, envisioned the following scenario: “Instead of clicking through five screens to submit an insurance claim and not knowing if it will be approved, you can attach a picture to a WhatsApp chat and the chatbot can instantly recognize the make or model of your car, identify the reason for the claim, ask for needed clarifications and submit the claim faster, with more accuracy.”
• Agentic AI: Agentic AI operates without constant human oversight, autonomously planning, executing and refining workflows with real “agency.” OpenAI, Meta and Anthropic are heavily investing in this model, enabling AI to independently select actions, conduct research, use tools and self-correct. “These advanced models promise capabilities far beyond traditional chatbots, able to drive complex enterprise processes while ensuring accuracy and alignment through embedded ‘verifiers’ and human collaboration,” explained Mike Finley, CTO of generative AI analytics platform AnswerRocket. 
• AI agents: Quintova envisions chatbots evolving into fully autonomous digital assistants or AI agents. “AI agents represent the next evolution in chatbot technology, transitioning from basic support tools to autonomous task managers and proactive digital assistants,” Quintova explained. “These advanced systems will seamlessly handle end-to-end processes, such as scheduling interviews, managing supply chain issues or guiding job seekers through career transitions.”
• Enhanced recruitment and career development: Quintova predicts that AI bots will play a growing role in matching skills to roles by advising job seekers on the best positions to pursue based on both internal job openings and industry trends. These bots will also recommend training courses and business certifications by analyzing real-time demand for specific qualifications.