How long does it take to build an AI agent?
By Irshad Memon|Updated
Short answer
A first agent scoped to one task with one or two system integrations typically takes six to twelve weeks from discovery to production. Discovery takes days, a working prototype a few weeks, and piloting and hardening a few more. Access to your systems and data usually decides the pace more than the model does.
Key takeaways
- A first agent for one task with one or two integrations: typically six to twelve weeks from discovery to production.
- Discovery takes days. A working prototype takes a few weeks. Piloting and hardening take a few more.
- Access to systems and data, approvals and unclear goals cause most delays, not the model.
- Written success criteria before the build stop a pilot from running on with no finish line.
- After launch, plan ongoing time for monitoring, updates and retesting.
How long does each stage of an AI agent project take?
Discovery takes days, a working prototype a few weeks, and piloting and hardening a few more, which comes to six to twelve weeks for a first agent with one or two integrations. A private agent that runs on your own hardware has a 3-5 day discovery and a 2-4 week pilot.
| Stage | What happens | Typical time |
|---|---|---|
| First call | Your goals, systems and constraints, and whether AI is the right tool | One call |
| Discovery | Pick one task, check data and access, write down what success looks like | Days |
| Prototype and pilot | Build for that one task in your accounts, on your own data | A few weeks |
| Evaluate and decide | Score the pilot against the success criteria, including the failures | Days |
| Production and hardening | Integrations, limits, approvals, logging, monitoring and handover | A few weeks |
Typical ranges, not promises. The whole path is typically six to twelve weeks for one task with one or two integrations. Our how we build page describes each step.
What slows an AI agent project down?
Waiting, mostly. Waiting for access to systems and data, for security and data protection approvals, and for decisions about what the agent may do. Unclear goals and growing scope come next. The model itself is rarely the bottleneck.
- Access: accounts, API keys and test environments that take weeks to approve.
- Data: documents that are out of date, contradictory or locked in systems without APIs.
- Approvals: security review, and in the UK a data protection impact assessment, which the ICO says most AI uses of personal data legally require (ICO).
- Decisions: nobody on your side can say which actions the agent may take alone.
- Scope: new tasks and channels added before the first one works.
How can you speed up an AI agent project?
Prepare access and data before the build starts, name one person who can make decisions, and keep to one task until it works. Agree a test set of real requests early, so progress is measured, not argued about.
- Start the access and security paperwork during discovery, not after it.
- Collect a set of real requests with agreed answers to use as the test set.
- Name one decision-maker who can approve scope and the agent's limits.
- Start with one task and one or two systems.
- Use a workflow with fixed steps where you can. Published agent-building guidance recommends the simplest solution possible (agent-building guidance).
- Adapt a pre-trained agent from our Bot Store where one fits. It can be quicker than a new build.
Why do AI pilots run on without finishing?
Usually because nobody agreed what finished looks like. Write the success criteria down before building: the accuracy to reach on a test set of real requests, the response time, and who reviews the outputs. Then the pilot ends with a clear decision.
MIT research, as reported in the business press, found that about 95% of enterprise generative AI pilots produce little measurable profit impact (report). A pilot without an agreed finish line is hard to judge, and easy to extend forever.
- 1
Agree the criteria
Accuracy on your test set, response time, and who reviews the outputs.
- 2
Build the pilot
One task, your own data, the permissions the agent needs and no more.
- 3
Run the test set
Report the scores, including the failures.
- 4
Decide
Production, a change of scope, or a stop.
What happens after an AI agent goes live?
The work changes rather than stops. Someone reviews samples of conversations, updates content and rules, and retests after every change to a prompt, a model or a tool. By our planning estimates, an agent needs 20 to 40 hours a month in the first months.
- Monitoring: answer quality, cost, speed, errors and misuse.
- Updates: new products, policies and integrations, each retested.
- Model changes: providers retire older models, so plan time to migrate and retest.
Where does Webify.AI fit?
We build AI agents, so we have an interest in this guide. The first call is free, success criteria are agreed in writing before any build, and our AI / LLM engineers cost $45 an hour.
- Pilots are built in your accounts and repositories, on your own data.
- We report the test scores, including the failures, and you decide what happens next.
- At every stage you can change scope or stop, and what we have built so far is yours.
- We hold no ISO 27001 or SOC 2 certification. Our security page explains what we do instead.
Frequently asked questions
Can an AI agent be built in a week?
A rough prototype sometimes can. An agent that works with your systems, has limits and approvals, and has been tested on real requests usually takes six to twelve weeks for one task with one or two integrations.
What is the fastest way to get an AI agent live?
Pick one task, have access and data ready on day one, and name one decision-maker. Adapting a pre-trained agent can also be quicker than building a new one.
How long is an AI pilot?
A few weeks for most first agents. For private agents on your own hardware, our pilots run two to four weeks after a 3-5 day discovery.
What do you need from us to start?
One task, a person who can make decisions, access to the systems involved, and a set of real requests with agreed answers to test against.
Does a multi-agent system take longer?
Usually, yes. Each extra agent, system and action adds design and testing time. Start with one agent on one task, then add more once it meets its success criteria.
Sources
Checked on 30 October 2026. Webify.AI figures are our published prices.
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