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AI agents and AI for business

Conversational AI: how it works and how to set it up

Conversational AI is software that understands a message written or spoken in ordinary language and replies in kind, rather than offering a menu of buttons. On the levelpartner.ai platform it takes the form of AI agents that talk to your leads and clients across chat, SMS, WhatsApp, social messages and the phone, and act on what they hear: booking, tagging, updating the CRM, handing over to a person. This guide explains what conversational AI for business actually does, gives examples, and shows how to switch it on properly.

How it works, without the jargon

Three things happen in every exchange. The agent reads the message and works out what the person wants. It looks up the answer in the knowledge base you gave it, along with anything known about the contact. Then it replies and, where your rules allow, takes an action such as offering a meeting time.

What makes this different from older chat tools is that nobody drew a flowchart. You describe the agent's job and give it material; it handles the phrasing. That is why it copes with "can I come in Thursday after 4" as easily as "book appointment".

Conversational AI examples in a service firm

  • A prospect on your website asks whether you work with firms their size. The agent answers, asks two qualifying questions and books a call.
  • A client texts to move a meeting. The agent offers new times and updates the calendar.
  • A caller rings after hours about a listing. The voice agent answers questions and books a viewing.
  • A lead who went quiet replies to a follow-up email. The agent picks up the thread and offers a call.

Each example ends in a CRM record and, usually, a booked next step. That is the test of whether conversational AI is doing business work or just chatting.

Before you start

  • The channels you want covered, connected to your account.
  • A knowledge base: your services, process, locations, common questions and approved answers.
  • A clear goal for each agent, such as booking new enquiries or answering client logistics.
  • Hand-off rules for complaints, pricing negotiations and regulated topics.
  • An owner who reads a sample of conversations every week.

How to set it up

  1. Go to AI Agents > Conversation AI and click + Create Bot.
  2. Select Guided Form Setup, then click Create New Bot.
  3. Choose the bot type: General Q&A if its job is answering questions, Appointment Booking if it should also offer meeting times.
  4. Select or create a Brand Voice that sounds like your team at its best.
  5. Configure Bot Settings with the agent's single job and the topics it must hand over.
  6. Configure Bot Goals: the calendar it books into and the questions it asks before offering a time.
  7. Save the bot.
  8. On the Bot Training tab, add your written answers and check each one in Test your Bot.
  9. Choose Off, Suggestive or Auto-Pilot as the bot's mode, starting with Suggestive.

In Suggestive mode the agent drafts each reply and a person approves it before it goes out. Auto-Pilot sends without that check. Stay in Suggestive until your team is sending drafts almost untouched on a channel, then switch that channel alone.

Conversational AI for business: what it replaces

For a firm of 10 to 250 people, it replaces three weak points: the autoresponder that says nothing useful, the shared inbox checked twice a day and the hours when nobody answers. It also replaces some of the manual qualifying salespeople do on first calls. It does not replace people who advise, negotiate or manage relationships.

Illustration: a 35-person consultancy using one agent on two channels

Suppose the firm gets 90 enquiries a month by web chat and email, a partner replies within a day on average, and about 35 of those enquiries turn into calls. If an agent replying in under a minute and offering times lifted that to around 50 calls from the same 90 enquiries, that would be 15 more first conversations a month without a single extra lead. Your own before-and-after count is the figure that matters.

Running time

Expect a first agent with one clear job to take about a day once your knowledge base is written. After that, budget roughly an hour a week per agent for reading conversations, fixing answers and checking hand-offs. Upkeep matters because your services, prices and people change, and the agent only knows what you tell it.

The common mistake

Firms build one agent to do everything: sales, support, booking and complaints. It does each poorly. Build one agent per job, each with a narrow goal and its own instructions.

When not to use it

Skip conversational AI where every conversation needs a qualified person, or where volume is so low that a person can reply quickly anyway. Keep it away from regulated advice; the conversational AI for banking guide shows where that line sits. If you are trying to choose between a simple chat widget and a full agent, read chatbot conversational AI. For the voice side, see AI receptionist, and for designing an agent's instructions, the conversational AI bot guide.

Troubleshooting

Answers are vague. The knowledge base is thin on that topic. Add a direct written answer rather than a long document.

The agent sounds stiff. The instructions are written like a policy. Rewrite them in the voice you want the agent to use.

It ignores your rules. The rule is buried in a long instruction block. Put must-never rules at the top in short sentences.

People ask for a human straight away. The greeting is unclear about what the agent can do. Say in one line what it can help with.

Frequently asked questions

Is conversational AI online the same as a chatbot app?

No. Consumer chat apps answer general questions. A business agent answers from your material, on your channels, and acts in your CRM. The AI sales agent article shows that difference in a sales setting.

Which channels does it work on?

Web chat, SMS, WhatsApp, social direct messages and phone calls through a voice agent. All share contact records, so one person has one history.

Do we need training data?

No. You need a clear knowledge base and good instructions. The work is writing, not data science.

How do we measure it?

Track time to first reply, booking rate from conversations, escalations per week and the share of conversations resolved without a person. Review them monthly.