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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We manage as one budget for 2 main reasons; investments follow the right approach not following the AI-hype or budget pot, AI does not work in isolation and co-exists with more traditional data, integration and automation technologies. The main drawback is AI is competing with other initiatives so doesn't get (rightly or not) dedicated focus.
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.
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 decided to take the cost for the first year on our innovation budget as we are still builiding up experience. Once the project has landed and we have a clear view, the next year the budget goes in the traditional bucket of infra and cloud costs. We keep an eye on the cloud cost within Azure with alarms and have a monthly reporting on resource use.