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?

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Director of IT2 days ago

AI and traditional investment portfolios tend to fall into two buckets. Early on, when experimenting, there is a separate budget for AI project bets. As some of those bets pay off and move into production, they become part of the budget run rate for the business. Also, many existing products in your portfolio may include AI capabilities at the next renewal. So if you're approaching a renewal, consider the potential for new AI capabilities to be included or available for incremental cost.

Head, Software Engineering, Cloud and Digital Transformation3 days ago

“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).

IT Manager3 days ago

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

3 days ago

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.

CIO3 days ago

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.

1 Reply
no title3 days ago

Technical debt is well understood, but I’m interested in how it maps to data in the era of AI. It’s an area that needs more exploration and language to guide boards and business leaders.

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