Building an AI centre of excellence
Give an internal AI team a way to deliver useful work
An anonymized enterprise engagement covering team formation, operating responsibilities and hands-on delivery practices.
The business challenge
The organization wanted to develop AI capability internally, but lacked a dedicated team and a defined way to select, build and operate projects. Hiring individuals alone would not settle how business teams, central IT and AI specialists should work together.
What NeoBram delivered
The published account describes an AI centre of excellence operating model, role and hiring profiles, onboarding, governance and practical developer training. Delivery playbooks connected discovery, engineering, deployment and operation. Responsibilities were aligned with the customer's existing enterprise controls, with the operating model and working knowledge retained internally.
What the engagement reported
The brief reports first hires and an operating model within eight weeks, followed by a dedicated team of 35 within six months. It describes ongoing developer AI use and self-sufficient delivery capability. The customer, staffing records and outcome measures are not public. Team size is an organizational result; it does not establish a particular financial return or justify the same structure elsewhere.
Choose the scale your business needs
A manufacturer starting its first AI workflow may need an accountable business owner and external engineering support rather than a large department. An internal programme becomes relevant when repeat demand, operating responsibilities and investment justify it. Before choosing a structure, map upcoming projects, skills gaps, recurring costs and the decisions the team must own. Agree support, updates and transition responsibilities before the work begins.
More clarity
Questions and answers
Do we need a CoE before our first project?
No. Start with the smallest team and responsibility model that can deliver and operate the intended workflow.
Does a larger AI team prove value?
No. Measure adoption, delivery quality, operating reliability and business results alongside capability development.
Start with one business problem