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Webex has two separate AI workflows that are easy to confuse. Cisco AI Assistant for meetings is enabled by an administrator in Control Hub. Customer-service AI agents are built in Webex AI Agent Studio and then connected to Webex Contact Center voice or digital flows. They use different entitlements, configuration screens, testing steps, and deployment limits.
This guide, updated October 2026, walks through both setups, explains when to choose a scripted or autonomous agent, and shows how to connect an agent to voice and digital customer-service channels without promising features your organization may not be eligible to use.
Webex meeting AI and customer-service agents are different products
Start by identifying the job you need to automate. If people need to ask questions during a Webex meeting, or if your organization wants meeting summaries and related controls, configure Cisco AI Assistant in Control Hub. If customers need automated help through a contact center, create an agent in Webex AI Agent Studio and place it in a Contact Center flow.
| Capability | Meeting AI Assistant | Customer-service AI agent |
|---|---|---|
| Where it is configured | Control Hub, under organization AI and meeting settings | Webex AI Agent Studio, then Contact Center or Webex Connect flows |
| Primary users | Meeting participants and meeting hosts | Customers, contact-center flows, and human agents receiving handoffs |
| Content source | Meeting conversation and organization settings | Knowledge base for autonomous agents or a question-and-answer corpus for scripted agents |
| Channels | Webex meetings and related meeting-history surfaces | Contact Center voice plus digital channels such as chat, SMS, and email |
| Important availability caveat | Meeting summaries are currently supported in English | Autonomous voice access is limited to specific customers; eligibility must be confirmed with Cisco |
Do not expect an agent created in AI Agent Studio to appear as the in-meeting assistant. Conversely, enabling meeting AI Assistant does not create a customer-facing contact-center bot.
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Check access, licensing, and administrative responsibilities first
Requirements for meeting AI Assistant
- An organization using the Webex Suite meeting platform.
- A Control Hub administrator who can change organization AI settings.
- A decision about whether external participants, recording-related assistance, participant requests, spoken-language detection, meeting-history search, and audio announcements should be enabled.
Availability, language support, and any complimentary-use terms can change. Treat the current Control Hub page as the authority for your organization rather than assuming that every Webex plan includes every AI feature.
Requirements for customer-service agents
- An active Webex Contact Center trial or subscription.
- The AI Agent add-on for a Flex 3.0 Contact Center license, where that licensing model applies.
- Access to AI Agent Studio, either through Contact Center entitlements or through Webex Connect when that access has been provisioned.
- Channel assets and Contact Center or Webex Connect flows for the channels you intend to deploy.
- An administrator who can create agents, manage flows, and publish versions.
In Control Hub, the documented customer-service route is Services > Contact Center > Customer experience > AI Agent > Webex AI Agent. If the option is missing, the organization may not have the required entitlement or feature flag. Cisco’s administration guidance says to contact Cisco Support when the relevant feature must be enabled.
Assign roles deliberately
Webex distinguishes full administrators, Contact Center service administrators, provisioning administrators, read-only administrators, and supervisors. Give each person only the permissions needed for their work. Transcript access is not granted automatically: a customer organization’s full administrator must explicitly grant access before an authorized user can review conversation transcripts.
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The Cisco Webex AI Agent Studio Administration guide currently states that an organization can create up to 100 scripted and autonomous AI agents. This is an operational product limit, not a performance benchmark. Confirm the limit in the live guide before planning a large deployment because product limits can change.
Enable Cisco AI Assistant for Webex meetings
1. Open the organization AI settings
- Sign in to Control Hub with an administrator account.
- Open Organization Settings > Cisco AI Assistant & AI features.
- Select Customize AI Assistant and AI features.
The labels above are the organization-level path documented by Cisco. If your Control Hub layout differs, use the AI Assistant and AI features section rather than searching the Contact Center menus.
2. Turn on in-meeting assistance
- Find the meeting-features section.
- Enable AI Assistant in meeting.
- Review the additional controls before saving.
- Select Save.
Enabling this control allows the in-meeting question-and-answer experience. It does not automatically grant every participant access under every condition, so review the related settings below.
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3. Decide which meeting controls fit your policy
- AI Assistant while recording: decide whether the assistant can be used when a meeting is being recorded.
- External participants: choose whether people outside your organization may interact with AI Assistant. External access requires the relevant administrator setting.
- Participant requests: determine whether participants can request AI assistance during a meeting.
- Audio announcements: configure spoken notices that tell participants when AI-related features are active.
- Automatic spoken-language detection: review whether the service should detect the language being spoken automatically.
- Meetings tab: decide whether AI-related meeting content appears in the Meetings tab.
- Meeting-history search: decide whether users can search their available meeting history.
Some controls can also be set through templates or at user level. Organization settings should establish the default, while templates and user settings can provide narrower exceptions where your administration model permits them.
4. Set expectations about summaries and transcripts
Meeting summaries are currently supported in English. Cisco also states that post-meeting summaries and transcripts are available only for meetings within the organization. Do not promise an external attendee that they will receive an organizational post-meeting summary merely because they joined the call.
Before enabling the feature broadly, test a meeting with the participant types and recording state you actually use. Verify that the announcement, assistant interaction, summary language, and history visibility match your policy.
5. Validate the rollout
- Create a controlled test meeting on the Webex Suite meeting platform.
- Ask an in-meeting question and confirm that the assistant responds as expected.
- Repeat the test with an external participant if external interaction is allowed.
- Record a test meeting if recording-related assistance is enabled.
- After the meeting, confirm which summary and transcript surfaces are visible to internal participants.
- Document the settings and the date you validated them, because labels, availability, and terms can change.
Choose a customer-service agent type before building
AI Agent Studio supports two fundamentally different patterns. Make this decision before writing content or designing a flow, because the source material, configuration, and testing criteria differ.
| Decision point | Scripted agent | Autonomous agent |
|---|---|---|
| Best fit | Bounded, repeatable tasks where consistent answers matter | Broader language understanding, knowledge-based answers, and configured actions |
| Primary source | User-created question-and-answer training corpus | Knowledge base, ideally in the same language as the agent |
| Configuration emphasis | Scripts, intents, entities, responses, and handover behavior | Instructions, knowledge, actions, fulfillment, language, and conversation behavior |
| Main risk to control | Out-of-date or incomplete corpus and scripts | Scope that is too broad, unsafe actions, or unsupported language and voice combinations |
| Deployment caution | Keep the corpus and connected flows accurate and consistent | Keep the scope limited and verify action behavior before publication |
When a scripted agent is the better choice
Use a scripted agent for a narrow interaction such as answering a fixed set of billing questions, collecting a known set of details, or following a tightly controlled handover script. Prepare the question-and-answer training corpus first, then maintain it as policies and product information change. Configure the scripts, intents, entities, and responses that match the flow you will connect.
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When an autonomous agent is the better choice
Use an autonomous agent when customers may express the same need in many ways and the agent must retrieve information from a knowledge base or perform configured actions. Keep the scope intentionally narrow. Cisco’s Webex AI Agent Studio Administration guide states: Don’t create a single autonomous AI agent with a complex scope. Instead, create multiple AI agents with limited scopes.
Treat that as an architecture rule: separate billing, appointment changes, technical troubleshooting, and other materially different jobs when they need different knowledge or actions.
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Create and configure the customer-service agent in AI Agent Studio
1. Prepare the source material
For a scripted agent, assemble and review the question-and-answer corpus before you create the agent. Remove contradictory answers, define escalation wording, and identify the entities the script must collect, such as an account number or order reference.
For an autonomous agent, create or select the knowledge base first. Cisco recommends using a knowledge base in the same language as the agent for best performance. Separate authoritative customer-facing material from drafts, duplicate articles, and documents that the agent should never quote. Decide which actions are allowed, what information an action needs, and when the agent must transfer the interaction to a human.
2. Start the agent
- Open AI Agent Studio.
- Select Create agent.
- Choose Start from scratch or a predefined template.
- Select Scripted or Autonomous.
- Enter a name that identifies the business purpose and scope.
- Choose an available engine.
- Select Create.
Engine choices and supported languages vary. Do not promise a language, voice, or capability until it appears in the current list for the selected engine.
3. Configure the agent profile and conversation behavior
Complete the agent profile, language, response style, and welcome experience. Make the opening message clear about what the agent can do and how a customer can reach a person. For an autonomous agent, configure its instructions, knowledge, conversation settings, and actions. For a scripted agent, configure the corpus, scripts, intents, entities, responses, and handover rules.
Design the handover as part of the initial build rather than as an emergency fallback. Specify what information is collected before transfer, what context is passed to the flow or human agent, and what the customer hears if the transfer cannot be completed.
4. Configure actions conservatively
Autonomous agents can be configured to collect customer information and transfer it to a flow. Map each action to the fields and validation rules expected by that flow. Test missing, malformed, and refused values, not only the happy path. If an action changes a customer record or triggers an operational process, require the confirmation and authentication steps your service policy demands.
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5. Preview before publishing
- Open the agent’s preview experience.
- Test the welcome message, common requests, ambiguous wording, and unsupported requests.
- For autonomous agents, test knowledge retrieval, action calls, and the transfer path.
- For scripted agents, test every intent, entity prompt, response, and fallback branch.
- Repeat tests in the intended language and, for voice, with the intended voice configuration.
- Check that the agent’s disclosure and handover wording are suitable for the channels where it will run.
Previewing is not a substitute for testing the final Contact Center or Webex Connect flow. Session variables, channel metadata, routing, and timeouts can change the result after integration.
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- When the preview behavior is acceptable, select Publish.
- Enter a meaningful version name that identifies the change.
- Publish the changes.
- Open History to verify the version details.
Use version names that allow an operator to identify the knowledge, script, action, or disclosure change without opening every revision. Keep the previous known-good version available for rollback planning.
Connect an AI agent to Contact Center voice
Voice deployment has additional flow and eligibility requirements. Cisco currently limits autonomous AI-agent access for voice calls to specific customers and directs organizations to support for details. Confirm eligibility before designing a production voice deployment or promising voice automation to stakeholders.
1. Prepare the voice entry point and routing flow
Your Contact Center voice design needs a voice entry point and an assigned routing flow. Confirm that the entry point routes to the flow version you intend to test and publish.
2. Add Virtual Agent V2
- Open the voice routing flow.
- Add the Virtual Agent V2 activity.
- Select the AI agent you configured in AI Agent Studio.
- Choose the conversational settings appropriate to the agent and use case.
3. Set language and voice variables
Set the default input language and output voice through the flow’s global variables where required. The chosen voice must be supported by the selected AI engine. Cisco warns that an unsupported voice can send the call to the activity’s error path, so validate the combination before involving customers.
4. Define every outcome
- Handled: define what happens when the agent completes the customer’s request.
- Escalated: route the interaction to a human queue or another approved recovery path, carrying the context your agents need.
- Error: provide a safe fallback for engine, voice, timeout, or integration failures.
A flow that only handles successful conversations is not production-ready. Test an explicit request for a human, an unrecognized intent, a missing customer value, an unsupported language or voice, and a downstream flow failure.
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Connect an AI agent to digital channels
Cisco’s Webex Connect and Webex Contact Center integration documentation lists six digital channels: WhatsApp, SMS, email, Facebook Messenger, Apple Messages for Business, and Live Chat. The exact channel asset and flow setup varies, but the integration pattern is consistent.
1. Provision the channel asset
Configure the applicable channel asset and confirm that inbound messages reach the Webex Connect flow associated with the customer-service experience. Verify sender identity, message permissions, and any channel-specific retention or template requirements before testing the AI node.
2. Create the Webex Connect flow
- Create or open the flow for the selected digital channel.
- Add the AI Agent node.
- Select the agent to invoke.
- Map the incoming message, language, channel, and user identifier fields.
- Add any customer or message parameters required by the agent or downstream systems.
- Map the node’s response and session values to the channel’s reply and session handling.
The documented node can return response text, a full response payload, session information, and other values. Custom parameters and message parameters are available, but not every field applies to every agent type or channel. Cisco notes that some parameters and metadata are limited to scripted agents or particular channels.
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Send a sequence of related messages rather than a single question. Confirm that the user identifier and session information remain consistent, that the agent remembers the required context, and that a new session starts when your flow intends it to. Test channel-specific formatting, long responses, attachments where applicable, and the transition to a human flow.
Disclosure, language, and regional governance
Review transparency defaults by region
Cisco says AI transparency defaults differ by region: the feature is enabled by default in European regions and Cisco recommends enabling it elsewhere. Review the disclosure wording in the agent and connected flows, then preview it across the languages and channels you support. Do not assume that one regional default satisfies every organization’s policy.
Keep language settings aligned
For autonomous agents, align the knowledge-base language with the agent language whenever possible. For voice, align the flow’s input-language and output-voice variables with voices supported by the selected engine. Meeting summaries are currently English-only, which is a separate limitation from customer-service agent language support.
Check compliance dates independently
Some administration material contains references to dates for EU-facing customers that are already past. Treat those references as historical context, not as an upcoming deadline. Obtain current legal or regulatory guidance for your deployment instead of relying on an old date in a product guide.
Use this launch checklist
- The correct workflow is identified: Control Hub for meeting AI Assistant, or AI Agent Studio plus Contact Center/Webex Connect for customer service.
- Contact Center subscription or trial and the applicable AI Agent entitlement are active.
- The required administrator roles are assigned, including explicit transcript access where needed.
- The agent type matches the use case and its scope is limited enough to test and govern.
- The scripted corpus or autonomous knowledge base is current, consistent, and written in the intended language.
- Actions, required fields, authentication, confirmation, and human handover behavior are defined.
- Voice entry points, routing flows, Virtual Agent V2, language variables, output voice, and all outcomes are configured.
- Digital channel assets, Webex Connect flows, AI Agent node fields, user identifiers, and session handling are tested.
- Preview conversations cover normal, ambiguous, unsupported, multi-turn, escalation, and error cases.
- Disclosure wording is visible and appropriate for each region, language, and channel.
- A named version is published only after testing, and the version is recorded in History.
Troubleshoot common setup failures
| Symptom | Likely cause | What to check |
|---|---|---|
| AI Agent is missing in Control Hub | The Contact Center entitlement or feature flag is not provisioned | Confirm the trial or subscription, Flex 3.0 AI Agent add-on where applicable, and contact Cisco Support about the feature flag |
| A user can administer the agent but cannot read transcripts | Transcript access was not explicitly granted | Ask the customer organization’s full administrator to grant transcript access |
| The agent answers correctly in preview but not in the contact center | The published version, flow mapping, session values, or channel fields differ from preview | Verify the selected published version, mapped message and user identifier, session handling, and flow branch |
| Voice calls reach the error path immediately | The output voice is unsupported by the selected AI engine, or a required language variable is missing | Choose a supported voice and set the default input language and output voice global variables |
| Customers lose context between digital messages | The flow is not preserving the user identifier or session information | Map the identifier consistently and test a multi-turn conversation in the actual channel |
| The autonomous agent gives inconsistent or overly broad answers | The scope or knowledge base is too broad, conflicting, or poorly maintained | Split the workload into limited-scope agents, remove conflicting content, and retest the affected intents |
| External meeting participants cannot use AI Assistant | The organization setting does not allow external interaction | Review the external-participant control and any template or user-level override |
| A meeting summary is unavailable in the expected language | Meeting summaries are currently supported in English | Set expectations with participants and verify the current supported-language documentation |
Operate the two AI experiences separately
Use separate owners and change records for meeting AI Assistant and customer-service agents. Meeting settings affect organization-wide collaboration behavior, while customer-service agents affect contact-center routing, customer data, and human-agent workload. A change to one does not configure or test the other.
For meetings, review participant access, recording behavior, announcements, summary visibility, and history search after Control Hub changes. For customer service, review the agent version, knowledge or corpus changes, action permissions, flow outcomes, channel sessions, disclosures, and transcript access. Re-run the relevant preview and integrated-channel tests after any engine, language, voice, knowledge, or flow change.
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