Common AI Budgeting Pitfalls and How to Avoid Them

I hate to be the one that tells you this but, your AI total cost of ownership (TCO) calculation is wrong*

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As banks, credit unions, and FinTechs dive into budget planning, "Figure out AI" is a top priority. But chances are your calculations might be missing a few key (and costly) elements of TCO.

If your budget looks something like this:

• 1 DATA SCIENTIST: to prep data, build and deploy models
• 1 CLOUD: pricing column 267, subsection 12A, which claims training models on alternate Tuesdays between 3:04 - 4:12 AM CT, your costs are "approximately" $500 per model
• 1 SHARED ChatGPT LICENSE
• 100 MS COPILOT UPGRADES

You have woefully underestimated your needs.

Without understanding TCO, organizations risk underestimating costs of AI projects and facing unwelcome surprises, like escalating expenses for maintenance, governance, infrastructure, or new hires - and a very unhappy C-Suite.

Common AI Budgeting Pitfalls

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Focusing Solely on Model Development
Too often, organizations focus narrowly on the first step: building a model. While that’s a win, it doesn’t actually get the models into production (Pro-Tip: not your 1 Data Scientist’s job). Ongoing management, monitoring, and infrastructure are critical to long-term success and unlocking continuous improvement. Those costs can quickly escalate as you move a model to production.

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Assuming Models Scale Themselves
Scaling AI systems isn’t as simple as adding servers or resources. (Pro-Tip: Cloud costs climbed 30% in many orgs last year, CFOs are panicking. Where there is mystery, there is margin…for cloud providers). Delivering ROI requires robust, cost-effective processes for inference (aka. serving the models). Without proper planning, models risk sitting unused or with massive cost overruns. None of this can deliver the ROI you promised.

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Underestimating Human Resources - not the department, the people.
AI systems require more than just technology, they need people. Whether building AI in-house or outsourcing, you should invest in change management and education. Without buy-in, even the best AI tools will collect dust.

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AI doesn’t have to be expensive and complicated, but only if you plan correctly. As you set budgets, take a hard look at TCO to avoid unexpected costs and ensure your AI initiatives deliver real, sustainable value.

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* I am sure YOU are a very meticulous budgeter, but there are a few unknowns that many organizations - especially those new to AI - fail to consider when budgeting.

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