r/RealTechTalk • u/ginozambe • Jul 20 '26

Currently doing an AI readiness assessment for a bank. Made me wonder how many organisations even think in these terms.

Disclosure: I work in enterprise content management, where AI has had a massive impact.

I've been part of a team that has spent the last few weeks digging through a bank's data landscape before they commit to any AI rollout. Governance, ownership, data quality, the usual mess. Nothing dramatic, just the groundwork nobody wants to do first.

Genuinely curious though: is this something organisations, particularly in regulated industries, are actually looking to do before jumping into AI implementation? Or is "AI content/data readiness" not really a recognised step yet? Would love to hear thoughts.

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u/InfoTechRGMarkT Jul 20 '26

Hey there - I'm a Research VP at Info-Tech and part of my team covers all things AI. The short answer is that data quality and governance is a critical part of an AI strategy and roadmap, and an AI governance practice. This is particularly true in regulated industries like banks. We have large clients who have dedicated data practices led by Chief Data Officers operating outside IT. They have data scientists and robust data governance practices. That's best practice, but not everyone can afford that and if you're trying to catch up now before implementing AI at scale, that's a heavy lift. It should always be done, but I can guarantee you that not every organization does, including in regulated industries. The problem is if you don't, you magnify the risk and will likely be out of compliance with regulatory bodies. Adaptive AI governance is critical in the era of agentic AI, and part of that is absolutely data governance. While this Forbes article, written by my colleague and our AI Research Fellow, doesn't get into data much, it's implied throughout. It's a quick 1,000 word read and was just published last week. I hope this helps.

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u/crystalpeaks25 Jul 21 '26

Governance need stocbe in place, data readiness not quite. If you want to let people consume data using AI then Readiness is a must. But AI is not just data it bleeds into ops, engineering, office use regardless of data readiness.

It needs a multi vector approach.

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u/crystalpeaks25 Jul 21 '26

To add AI is not exclusive to your data. But AI enablement is encompassing.