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From Pilot to Production: What an AI Implementation Partner Should Actually Do

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From Pilot to Production: What an AI Implementation Partner Should Actually Do

Choosing an AI implementation partner? Here is what a good engagement looks like, from assessment to pilot to rollout, and the questions to ask before you sign.

AI
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Once you have decided to invest in AI, the next question is who builds it. Plenty of firms will sell you a strategy deck. Fewer will put working software in front of your users and stay until it is adopted.

Here is what a strong AI implementation engagement looks like, and the questions that separate partners who ship from partners who advise.

Phase 1: Assessment, ending in a decision

A good assessment is short and ends with choices, not a report that sits on a shelf. You should come out with a ranked list of use cases, an honest read on your data, and a pilot plan with a scope and a date.

Ask: “What will we have in hand at the end of the assessment?”

Phase 2: Data and integration work

This is the unglamorous part, and the part that decides whether the AI works. Your partner should know your core platforms well enough to fix fields, map permissions, and connect systems without creating a new maintenance burden.

Ask: “Have you built integrations for the systems we run? Can we see examples?”

Phase 3: A pilot with real users and a real baseline

The pilot should run inside your systems, with a small group of real users, measured against how the work was done before. It should include a way for users to flag wrong answers, and those flags should improve the system.

Ask: “How will we know the pilot worked?”

Phase 4: Rollout, support, and the next use case

AI systems need care after launch. Prompts, data sources, and models change. Your partner should hand over documentation, train your team, and offer ongoing support so the tool keeps working as your business changes.

Ask: “Who supports this after go-live, and how?”

Five questions to ask any AI partner

  • Which AI platforms do you build on, and why?
  • How do you keep our data out of model training and inside our controls?
  • How do your AI tools show where an answer came from?
  • What security certifications does your delivery team hold?
  • Can you show AI work you have taken to production, not only demos?

How BRIO approaches it

BRIO has spent more than 20 years building and integrating business systems, including Salesforce, Litify, and custom software, for 280+ clients. We are a Claude Partner and a SOC 2 compliant team. Our AI work runs on that foundation: a Litify expert that cites its sources, and governed KPIs that leaders can question in plain language and trust to match the dashboard.

We start with an assessment, ship a focused pilot, and stay through rollout.

Book an AI Efficiency Assessment and leave with a ranked list of use cases and a pilot plan.

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