What is a managed AI agent?
A managed AI agent is an AI system that performs real tasks inside a business's own tools while an external vendor operates, maintains and supervises it. It differs from a chatbot because it takes action rather than only generating text, and it differs from a self hosted agent because the vendor, not the customer, is responsible for keeping it running.
What is the difference between a managed AI agent and a chatbot?
A chatbot produces text and a managed AI agent produces outcomes. When asked to clean a contact list, a chatbot explains how and an agent does it, then reports what changed. The practical consequence is that agents hold credentials and touch live systems, so they require approval gates and action logs that a chatbot does not need.
What is the difference between a managed AI agent and building your own?
The difference is who carries the maintenance. Building your own gives maximum control and makes every broken credential, changed API and drifted output format your team's problem. A managed agent trades some control for the vendor absorbing that operational burden. Build when the agent is core to your product or must live inside your own compliance boundary. Buy managed when the agent supports the business rather than being the business.
What can a managed AI agent do?
It performs scoped, repeatable operational jobs. Common examples are triaging a shared inbox, assembling recurring reports, cleaning and enriching lists, monitoring systems and drafting routine outbound communication for human approval. The limit is not intelligence, it is access and scope: an agent can only act in systems it has been granted and on jobs it has been contracted to run.
How much does a managed AI agent cost?
Published pricing for managed AI agents generally runs from several hundred to a few thousand dollars per month depending on how many distinct jobs the agent performs. Steward publishes 500 dollars per month for one skill, 1500 for up to three and 2500 for up to five, billed monthly. Per seat and per task alternatives exist and are harder to forecast because the bill moves with headcount or volume.
Is a managed AI agent safe to give access to business systems?
It is as safe as its scope, its approval gates and its logging, and unsafe without all three. Access should be granted per system and limited to what the contracted skills require. Actions that leave the organization, spend money or delete data should stop for human approval. Every action should produce a reviewable record, because an agent whose work cannot be inspected cannot be supervised.
Who is a managed AI agent right for?
Teams with recurring operational work and no one to own it, typically between five and a few hundred people, that lack the engineering capacity or the appetite to build and maintain agent infrastructure. It is the wrong choice for teams that need the agent inside their own cloud under their own models and compliance boundary, which is a self hosted deployment rather than a subscription.
Frequently asked questions
What is the difference between a managed AI agent and a chatbot?
A chatbot produces text and a managed AI agent produces outcomes. When asked to clean a contact list, a chatbot explains how and an agent does it, then reports what changed. The practical consequence is that agents hold credentials and touch live systems, so they require approval gates and action logs that a chatbot does not need.
What is the difference between a managed AI agent and building your own?
The difference is who carries the maintenance. Building your own gives maximum control and makes every broken credential, changed API and drifted output format your team's problem. A managed agent trades some control for the vendor absorbing that operational burden. Build when the agent is core to your product or must live inside your own compliance boundary. Buy managed when the agent supports the business rather than being the business.
What can a managed AI agent do?
It performs scoped, repeatable operational jobs. Common examples are triaging a shared inbox, assembling recurring reports, cleaning and enriching lists, monitoring systems and drafting routine outbound communication for human approval. The limit is not intelligence, it is access and scope: an agent can only act in systems it has been granted and on jobs it has been contracted to run.
How much does a managed AI agent cost?
Published pricing for managed AI agents generally runs from several hundred to a few thousand dollars per month depending on how many distinct jobs the agent performs. Steward publishes 500 dollars per month for one skill, 1500 for up to three and 2500 for up to five, billed monthly. Per seat and per task alternatives exist and are harder to forecast because the bill moves with headcount or volume.
Is a managed AI agent safe to give access to business systems?
It is as safe as its scope, its approval gates and its logging, and unsafe without all three. Access should be granted per system and limited to what the contracted skills require. Actions that leave the organization, spend money or delete data should stop for human approval. Every action should produce a reviewable record, because an agent whose work cannot be inspected cannot be supervised.
Who is a managed AI agent right for?
Teams with recurring operational work and no one to own it, typically between five and a few hundred people, that lack the engineering capacity or the appetite to build and maintain agent infrastructure. It is the wrong choice for teams that need the agent inside their own cloud under their own models and compliance boundary, which is a self hosted deployment rather than a subscription.