Conversational AI Chatbot vs. Assistants: Exploring Key Differences

Companies that embrace AI technologies are ahead of the curve. According to Harvard Business School research, employees who use generative AI experience a 40% boost in performance compared to those who do not.

One significant way generative AI supports businesses, including helping them scale, is through conversational chatbots and virtual assistants. While both tools use AI, they function differently. As you decide which is best for your needs — conversational AI chatbot versus assistants — it’s important to understand how each is used.

We’ll compare these tools and explore how they can support your teams and your business.

What are conversational AI chatbots?

Conversational AI chatbots are a type of artificial intelligence that uses natural language processing (NLP) to simulate human conversations. They interact with users through conversational interfaces , or chat boxes, where people ask questions and receive instant replies. These AI bots excel at handling high-volume, repetitive tasks common in customer service, incident response, and HR departments.

However, not all AI chatbots are created equal. Their features and capabilities depend on the technologies they’re built with and how vendors design conversational interfaces. Aspects of conversational AI include:

• Natural language processing (NLP) translates human language so bots can form a reply. NLP is great for basic FAQs but may struggle with complex or ambiguous questions.
• Natural language understanding (NLU) allows the AI bot to interpret intent and understand context, making interactions more accurate and human-like.
• Machine learning (ML) helps AI bots recognize patterns, learn from past interactions, and improve their ability to respond to more complex topic nuances over time.

Key features of conversational AI chatbots

When selecting a conversational AI chatbot, focus on features that align with your team’s goals. Some common capabilities of AI chatbots include:

• Task automation. With automated workflows in place, AI bots can complete tasks, such as updating a billing address or resetting a password, without human assistance. This can accelerate productivity and cut down on errors.
• Context management. If a user must leave a conversation with a bot before their issue is resolved, they can jump back into it later without having to repeat their situation. The bot will remember who they are and where they left off, which can improve the user experience.
• Multilingual assistance. This advanced chatbot feature is especially helpful for multilingual customer interactions and can make customer support more accessible.
• Sentiment analysis. This is the process of analyzing digital text to determine a user’s mood. From there, bots can adjust the tone of their responses or transfer the case to a human assistant if the situation escalates.
• Integrations. Choosing tools that can connect with CRMs, HR platforms, and other work operating systems lets AI chatbots access important data, such as a customer’s order status or low inventory levels.
• Omnichannel support. By implementing AI chatbots across channels, you help ensure a consistent user experience whether customers reach out on social media, mobile apps, or help desk systems.
• Personalization. AI chatbots use machine learning to tailor responses based on user data, such as purchase history or account details.

 

What are AI virtual assistants?

An AI virtual assistant uses artificial intelligence, natural language processing, and conversational interfaces to perform tasks and provide information to users. Think of them as digital teammates designed to make your life easier.

If you’ve ever asked a smart device to find a recipe, make a grocery list, or turn on your thermostat, you’ve used a virtual assistant. Now imagine the same concept applied to the workplace. An AI virtual assistant can schedule meetings, analyze large amounts of data, and even suggest next steps based on your campaign and sales data.

Like conversational chatbots, AI assistants come in many shapes and forms, from general digital helpers to specialized sales agents. Their capabilities vary based on technology implementation and conversational interfaces. Here are some examples of AI virtual assistants:

• Generalized AI assistants. These tools can coordinate your workday by managing calendars, emails, and reminders. They may also suggest ideal meeting times or other actions based on your preferences and behavior patterns. For example, speech-activated assistants for smart devices can monitor upcoming events.
• Task-specific assistants. AI assistants can handle specialized workflows, such as for finance, marketing, or sales, when integrated with the tools teams already use. This enhances operational efficiency while eliminating the need to constantly switch between platforms. Consider a digital assistant integrated with a CRM that automates lead scoring, follow-up emails, and reporting.
• Collaborative assistants. If you need to find information quickly, an AI assistant can help. Rather than manually searching through conversations, emails, or files, team members can type questions into a conversational interface and get fast answers with generative AI. For example, a virtual assistant can research a topic and provide sources for you before you head into a meeting. They can also summarize conversations you missed while you were away.
• Autonomous AI agents. Capable of performing complex tasks independently by interacting with their environment and learning from it, these bots can do things like analyze large volumes of data and suggest next steps. They can also be used as digital marketing assistants to send targeted emails or enhance customer support by guiding shoppers through buying decisions.

Key features of AI virtual assistants

When considering an AI assistant, think about the processes and tasks you’d like to automate or get extra support with to boost productivity and enhance business operations. Here are some to consider:

• Personalization. AI virtual assistants learn user habits and preferences to improve proactive support and task management. For example, machine learning analyzes preferences, so over time, AI can learn if a user prefers calendar notifications over email alerts.  Natural language processing also helps the assistant understand whether a user prefers a casual tone over a formal one. Additionally, virtual assistants can anticipate needs or suggest actions, such as following up with a lead or proposing meeting times.
• Advanced conversational interfaces. Consider whether voice- or text-based tools best support your needs and those of your customers. This may depend on the channel and type of support required. Unlike AI chatbots, which are often built into specific apps, software, or websites, an AI assistant can support users across all integrated applications.
• Contextual intelligence. This allows AI virtual assistants to recall conversation details, handle follow-up questions, suggest next steps, and adjust responses for a seamless user experience. Since the AI assistant adapts over time, discussions can feel more natural compared to chatbots, which typically treat each conversation as a stand-alone interaction.
• Task management. These tools simplify administrative work by organizing files, tracking deadlines and appointments, and managing action items across multiple channels and departments. Autonomous assistants can suggest and complete more complex tasks, such as requesting new hardware or generating a campaign brief, which chatbots typically cannot.
• Other AI-powered tools. Simplify routine tasks with additional AI tools built into conversational interfaces. For example, Slack AI includes note-taking and conversation summary features that speed up resolution times for various support scenarios. A virtual assistant can also organize and review data from connected systems to generate insights, create reports, and suggest next steps.

 

Conversational AI chatbot vs assistants: Understanding the differences

An AI chatbot is an efficient digital worker that manages high-volume, repetitive tasks. An AI virtual agent works just as fast but is more strategic and proactive, providing data and resources to help teams work smarter. Here are some key differences to help you choose the right fit for your team:

• Interaction complexity: AI chatbots can surface relevant information, such as account details or a help desk answer, whenever you or your customers need it. However, they are typically better suited for lower-complexity interactions compared to AI assistants. For example, AI assistants can respond to questions using company data, offer insights on improving outreach with specific customers, and maintain a conversation even when topics change.
• Range of tasks: Conversational AI bots are great at managing straightforward tasks, such as guiding new hires through onboarding activities and providing on-demand customer service. AI assistants can step into more advanced roles, from coaching sales teams through CRM-based role-playing activities to coordinating meetings and follow-up messages for managers.
• Adaptability and learning: AI chatbots can learn from interactions and improve over time for their task-specific roles, but their abilities are limited. For example, a chatbot can get better at recognizing different phrases related to customer issues and respond appropriately, but it can’t offer solutions beyond predefined tasks. In contrast, AI assistants can help scale workflow automation across your organization and suggest improvements, making them more dynamic and able to grow with your team.

 

Analyzing use cases and industries

So where can companies actually use these tools? Because the effectiveness of conversational AI chatbot versus assistants can depend on the use case, understanding where they can help you the most is key. Let’s explore examples to see how chatbots, assistants, and Slack AI help move work forward faster.

Use cases for conversational AI chatbots

Salesforce’s State of Service report found that service organizations most commonly use AI in customer-facing intelligent assistants. But it’s important to understand the differences in scope and functionality between conversational chatbots and AI assistants, especially for teams aiming to automate workflows while maintaining high customer interaction and satisfaction levels.

Let’s look at some specific ways teams use chatbots:

• Workforce coordination: AI-powered chatbots can connect to HR or project management databases to help leaders coordinate projects and resources. One advertising agency with thousands of distributed team members uses a custom bot with Slack to find the right people for various tasks.
• Case management: Bots can coordinate incident response teams and help prioritize caseloads. For instance, a large e-commerce platform with 1,700 engineers and developers uses bots and support channels on Slack to automatically alert teams to issues, thereby resolving cases faster.
• Product management: Chatbots can help companies handle inventory and product listings across multiple channels. A grocery and pharmacy provider built a custom, internal Slack app to provide real-time product availability insights, alert teams of pricing errors, and answer questions about stores or stock changes.

Use cases for AI assistants

With the rise of AI and automation and tool availability, leaders are discovering new ways to improve areas such as customer service and operational efficiency. Early generative AI adopters are already reporting meaningful cost reductions and revenue increases across every line of business, and autonomous agents are expected to contribute to increased revenue through productivity gains.

Here are areas where AI assistants can support your teams:

• Sales: With help from integrated AI assistants, sales teams get data-driven recommendations, track leads, and automate sales processes. A contract lifecycle management platform doubled its productivity and sped up deal closures by adding a digital teammate that collaborates with employees in Slack, providing deal guidance and sharing industry knowledge.
• Project management: AI virtual assistants can help teams improve workflows by analyzing data, identifying bottlenecks, and suggesting optimizations. For example, teams can access their company’s collective knowledge and resources in Slack while working alongside Asana’s project management assistant.
• Customer success: An AI assistant could be invaluable for companies that rely on real-time data. Consider how one construction and engineering services company is preparing for Slack’s Agentforce integration. Agentforce is the agentic layer of the Salesforce platform for deploying autonomous AI agents across any business function. This addition will ensure teams have real-time insights on equipment availability, enabling faster responses and enhancing customer service.

 

How to choose the right AI tool for your business

When it’s time to choose an AI tool, focus on matching the technology to your specific business needs. Let’s look at a few key factors to consider when choosing between conversational AI chatbots and AI assistants.

• Long-term goals: Think about the future you envision for your company, and choose technology that can grow with you. To support business growth, consider tools like Slack AI and Agentforce, which help teams make faster, data-driven decisions.
• Task complexity: Identify your needs — whether simple tasks or intricate workflows — and pick the right tool to get results. For example, consider embedding chatbots in HR and customer service workflows to manage high-volume requests while delegating complex, multistep processes to AI assistants.
• System integration: Ensure your tools connect with existing systems so teams can surface data faster and automate workflows between apps. For instance, when companies centralize operations in Slack’s work OS, teams can work side by side with Slack AI, Agentforce, and third-party assistance tools to get things done without switching apps.
• Automation needs: What level of automation does your company need? A combination of AI bots and assistants could be the solution if you want to become more agile and efficient in various areas. Consider using custom Slack bots to automate approvals and incident responses while your integrated AI assistant analyzes campaign performance and suggests improvements.

 

Support team efficiency with virtual AI assistants

Choosing between conversational AI chatbots and AI assistants depends on your business needs. For simple, high-volume tasks, consider an AI chatbot. When looking for a strategic, adaptable digital teammate to help with high-impact goals, an AI virtual assistant can add value to your team. Combining both tools can boost revenue and operational efficiency while lowering costs. Where conversational chatbots streamline customer service and internal support, AI assistants provide data-driven insights to help teams make smarter decisions.

Learn how Slack AI can support your team.