You are championing an initiative and AI is key to success. You’ve hired a CPMAI to help your teams deliver. What comes next?
Business Understanding is the first of six phases in the CPMAI approach. Engaging fully with this phase saves the cost and disruption of adopting a new tool in the wrong way. It also avoids issues erupting when you are otherwise close to market or already in production. If something does happen, you will be better prepared.
As a practice, this phase applies systems thinking. You will review who will be affected by the initiative and the processes it impacts, in addition to the technology involved. The key outputs are a formal problem definition, a project plan to address it, and a decision whether to continue.
This article covers problem definition, solution planning, and establishing success criteria. Throughout we use the example of business understanding for Morty, the mortgage research agent. The next article addresses the go/no-go decision.
Technical Debt. All those tradeoffs and delayed changes done to meet deadlines. Who has time to even keep track though, when everything not due today was due yesterday? Let's hope it doesn't erupt as a costly emergency later.
Enter AI assistants, which can now make documentation a side-effect of the work: Trackable choices checked into GitHub. Fast and detail-oriented collation of needs from over the project's full history, quickly delivering useful work that rarely gets attention.
Let's look at how to take advantage.
Getting ready for an AI project at your business? Cool, what kind? An essential step towards AI success is to understand which usage pattern will address your business need. There are seven key patterns, summarized below.
The CPMAI framework is a methodology for success with AI projects. It helps prevent you from rushing off without a proper grounding in your business needs, data safeguards, and other key factors. A CPMAI certificate holder can guide your organization through these pitfalls to a successful delivery.
