Over the last few years, I have worked on many AI solutions across different domains such as health care, HR, project management, customer support, and finance. One thing I have noticed is that when people think about AI, they immediately think about a chatbot.

Many teams start with the question “How can we add a chat interface?”

But in my experience, chat is not always the right answer. Sometimes users need to ask questions. Sometimes they need to see trends and insights. Sometimes they don’t want to interact with AI at all and want the work done automatically.

When I design AI solutions, I try to focus on the user’s goal first and then decide whether chat, a dashboard, or automation is the best experience.

In this blog, I will share a simple way to think about these three AI UX patterns and when to use each.

Three ways users interact with AI

1. Chat: Asking questions and getting answers
2. Dashboard: Viewing information and insights
3. Automation: Letting AI do the work

Chat: Asking questions and getting Answers

Chat is probably the most common AI experience today. Users type a question, and AI provides an answer. I usually use chat when users don’t know exactly where to find information or when they need quick guidance. Here are some examples:

• HR policy questions
• IT support requests
• Searching knowledge articles
• Product recommendations

The biggest advantage of the chat is that it feels natural and users can ask questions instead of navigating through multiple screens. However, not every problem should be solved with chat.

Dashboard: Viewing information and insights

The dashboard helps users see important information in one place. Instead of asking multiple questions, users can quickly understand what is happening by looking at charts, metrics, and trends. I often use dashboards for:

• Business reporting
• Project tracking
• Patient monitoring
• Sales performance

When users need visibility and want to compare data, a dashboard is usually a better choice than a chat interface.

Automation: letting AI do the work

Sometimes users do not need answers or reports; they want the task to be completed. This is where automation becomes useful. Here are a few examples:

• Extract information from documents
• Route support tickets
• Generate reports
• Send alerts automatically

In these cases, the best user experience is often no user interaction at all. The user gets the outcome without spending time on repetitive work.

When to use Chat, Dashboards or Automation

Over time, I started using a simple rule when I design AI solutions.

Use Chat when users need answers

If users have questions and need guidance, chat works well. For example:
An employee wants to know their leave balance; he types in the chat: “How many remaining leaves do I have?” The chatbot can provide the answer immediately—no need to search through multiple pages or documents.

Use Dashboards when users need visibility

If users need to monitor information and understand trends, dashboards are a better choice. For example – A finance manager may want to see:

• Revenue trends
• Budget variance
• Forecast performance

Showing all this information on a dashboard is much more effective than having users ask multiple questions via chat.

Use Automation when users need results

If users perform the same task repeatedly, I always look for opportunities to automate the task. For example – When a project request is submitted, AI can perform the following:

• Read the document
• Extract key information
• Create a project record
• Assign it to the right team

The user does not need to do anything manually. The work gets done by AI.

Common Mistakes in AI Design

• Trying to turn everything into an AI chatbot

This is probably the most common mistake today. Just because AI can chat does not mean it should be used everywhere.

I have seen situations where users needed to compare reports, track trends, and review metrics, but the solution was designed entirely as a chatbot.

A dashboard would have been much more effective.

• Missing Automation Opportunities

Many business processes still require users to perform repetitive tasks manually.

Whenever I see people copying data between systems, updating spreadsheets, or processing the same type of task repeatedly, I think about automation.

These are some of the great opportunities for AI.

• Showing insights without recommended actions

Many dashboards show end users what happened but do not show what action to take next.

I believe AI should not only provide insights but also show recommended actions. That is where the real value comes from.

Final thoughts

Whenever I start work on a new AI project. I don’t immediately think about using a chatbot, dashboard, or automation.
Instead, I always ask myself, “What is the simplest way for users to achieve their goal while giving them the best possible experience?”

The answer might be Chat, a dashboard, or automation.
Choosing the right approach is what makes a great AI experience.