My news feed is filled with “A Year in Review” of what happened in 2024 and the thing that stood out to me was 2024 was a bit of a mess for AI implementations.
- https://www.pcmag.com/articles/the-biggest-ai-failures-of-2024
- https://tech.co/news/list-ai-failures-mistakes-errors
- https://hbr.org/2025/01/6-ways-ai-changed-business-in-2024-according-to-executives?ab
- https://uk.pcmag.com/ai/156029/the-biggest-ai-failures-of-2024
From chat-bots giving illegal advice to fake content flooding our news and social media feeds (I’m pretty sure that I’m not the only ones who’ve seen the Pope wear a cool puffy jacket)
So how did we get here:
The rush to implement AI solutions was largely driven by market pressure and FOMO (Fear of Missing Out). Companies, desperate to stay competitive, rushed to deploy AI solutions without proper governance frameworks or security controls. Board rooms worldwide echoed with demands for “AI strategy,” often without understanding what that actually meant for their business.
This perfect storm was further fueled by the accessibility of AI tools and platforms. What used to require deep technical expertise became available through simple APIs and low-code interfaces. While this democratisation of AI is generally positive, it led to a “wild west” scenario where implementations often outpaced proper security and compliance considerations.
The result? Poor deployment, Terrible user experience and many half-baked AI solutions, security vulnerabilities, and trust issues.
Before You Start: The Boring (But Essential) Bits
Look, I get it – you want to jump straight into the exciting world of AI. But here’s the thing: you need to sort out your data house first. Think of it like baby-proofing your home. Your CISO and security team need to know exactly what data you’ve got, where it lives, and who’s allowed to play with it.
Get your Microsoft Purview DLP policies sorted, tag your sensitive stuff using Purview Information Protection, and make sure you’ve got the right security controls in place. Trust me, this boring bit will save you from some proper headaches later.
The Fix: Four Simple Actionable Steps
- Sort Out Your Governance
- Get an AI committee going
- Write clear policies on AI usage, Data Protection, etc
- Set proper standards
- Actually check if things work (please audit!)
- Lock Down Security
- Content verification is your friend
- Proper access controls (seriously)
- Encrypt everything (not just email but the underlying data must be encrypted too)
- Have a plan when things go wrong
- Quality Control
- Keep humans in the loop
- Test, test, test
- Watch those outputs (again please run audit checks)
- Clean data = better results
- Azure has a good framework for this: Test and evaluate AI workloads on Azure
- Smart Implementation
- Start small, scale later (even on a controlled Copilot for Microsoft 365, pilot it first with a handful of trusted people)
- Train your people properly, (end-user education is a must)
- Listen to user feedback
- Don’t rush it
2024 showed us that rushing in without proper planning is a recipe for disaster. Take your time, do it right, and maybe we won’t see your company in next year’s “AI Fails” list.
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