Your 90-Day AI Launch Plan: Week by Week

You've scored your use cases. You've picked your first project. Now you need to stop planning and start shipping. Ninety days. From "approved" to "running in production." Not a roadmap. A launch plan.

This plan is designed for a Tier 1 or straightforward Tier 2 project using a commercial product. Building custom? Double the timeline. And maybe reconsider.

Four phases. Clear deliverables. Hard decision points. No fluff. Let's go.

Phase 1: Foundation (Weeks 1-3)

Week 1: Define the Box

Gather your project owner, technical lead, and one representative from the end-user team. In a single 90-minute session, answer these questions and write them down:

• •What specific task is this AI replacing or augmenting?
• •Who does this task today, and how many hours per week?
• •What data does the AI need, and where does it live?
• •What does "good enough" look like for a first version?
• •What's the one metric you'll use to judge success at 90 days?
• •Who is the single person accountable for this project?

Write a one-page brief. Not a 30-page requirements document. One page. If you can't describe the project in one page, the scope is too big. Cut it down. Then cut it again.

Week 2: Audit the Data

This is where most timelines die. Here's the thing. Before you talk to vendors, have your technical lead pull a sample of the actual data the AI will work with. Not a description. Not a schema diagram. The data itself. Check for:

• •Completeness: Are the fields you need actually populated?
• •Consistency: Is the same information formatted the same way? "United States" vs "US" vs "USA" vs blank might seem trivial. For AI, it's three different values.
• •Volume: Most vendor products need 3-6 months of data minimum.
• •Access: Can you actually export this data from where it lives?

If the data isn't ready, stop. Full stop. Fix the data first. Deploy AI second. There is no shortcut here. Anyone who tells you otherwise is selling something.

Week 3: Select Your Vendor

Request a proof-of-concept using your actual data. Not demo data. Your data. Any vendor who won't do a POC with your data is a vendor you should skip. No exceptions. Finalize scope, deliverables, timeline, and success criteria in writing.

Phase 2: Build and Configure (Weeks 4-8)

Weeks 4-5 are infrastructure. If buying: provision the vendor environment, set up SSO, configure data connections, get your data flowing. The goal by end of week 5: data is flowing and you can run the AI on a sample of real inputs.

Weeks 6-7 are configuration and customization. Tune the system for your use case. Configure business rules and thresholds. Test with edge cases from your actual operations. Set up the human-in-the-loop workflows. Build the output formats your team needs.

Week 8 is shadow mode. Run the AI in parallel with the humans. The AI processes real inputs, but humans still do the work. Compare outputs. Track accuracy, edge cases, speed, and confidence levels. This week will reveal problems. That's the point.

Phase 3: Pilot (Weeks 9-11)

Week 9: Deploy to 5-10 end users. Ideally including the most skeptical person on the team. Especially that person. Give them a 30-minute hands-on walkthrough with their actual data. Their job: use the system for real work and report everything that breaks.

Weeks 10-11: Iterate on three types of feedback. Bugs get fixed immediately. Nothing kills adoption faster than a known bug that persists. Nothing. Workflow issues get adjusted (adapt the process, not the people). Feature requests get logged but not acted on yet.

By end of week 11, your pilot group should be using the system consistently with measurably better outcomes. If they're not, extend the pilot. Don't launch to the full team with a system that isn't working for the pilot group.

Phase 4: Full Deployment (Weeks 12-13)

Week 12: Roll out to all intended users. Run live walkthroughs for each team. Not a recorded video. Live. Have your pilot users present alongside you. Peer credibility beats executive mandates for adoption every time. Set up a support channel, weekly office hours, and automated usage tracking.

Week 13: Pull the numbers. Compare against your success metric from Week 1. Write a one-page summary: what you deployed, the metric you set, the result at 90 days, what you learned, and what's next. Share it with leadership. If it worked, this is your ammunition for the next AI project.

The Week-by-Week Overview

When You Fall Behind (You Will)

The most common delays: data issues in Week 2 push everything back 2-3 weeks. This is normal. Vendor implementation takes longer than promised. Also normal. Build 2 weeks of buffer into the contract. Pilot feedback reveals a fundamental issue? Loop back to Phase 2. Don't launch a broken system on schedule. A launched failure is still a failure.

The 90-day target is a forcing function. Not a death march. A 120-day launch that works is infinitely better than a 90-day launch that gets rolled back. Ship right. Not fast.