Do you manage AI and traditional IT infrastructure investments as separate portfolios (budgets, governance and decision criteria) or do you combine them? What are the benefits and drawbacks of your approach?

“When we onboard a new or emerging technology or initiative, we typically begin under a Special Initiative Budget. This approach allows us to validate potential outcomes, justify returns, and more accurately forecast costs. It also helps us design an appropriate governance model, establish budget trends, and define success criteria.

Over time, once proven, the initiative is transitioned into the mainstream portfolio.

Benefits: This process strengthens justification, program management, success criteria, team structure, and governance.

Drawbacks: It takes time to get budget approved and after approval we have to continuously report the status (which is not a bad thing from enterprise investment point of view).

If it’s a new investment it’s separate - upon renewal it becomes bau and sits in the appropriate pot

My budget has a separate line item for AI discovery, reflecting our current stage. Pilots and proof-of-concept projects help demonstrate value to business partners, potentially leading to more investment as credibility grows.

We’ve traditionally managed everything under one budget, but with our AI readiness program, we’re starting to identify specific AI expenditures and discuss KPIs and OKRs. We’re in the early stages of defining measurement and outcomes. One thing to note is that every organization faces technical debt, and thoughtful investment today can prevent much higher costs tomorrow. The focus should be on how technology enables business objectives, not just the technology itself.

All investments roll up under the same budget, but I manage them somewhat separately to track ROI for AI projects. Many AI initiatives lack clear ROI, so guardrails are essential. The goal is to ensure resources are used effectively.