5 Pitfalls in Unstructured AI

25 June 2025

5 Pitfalls in Unstructured AI—and How WaiFinder Keeps You on Track

As AI adoption accelerates across UK businesses, many MSPs and consultants find projects veering off course. With an estimated 11,492 active MSPs in the UK—of which 1,500–1,700 fall under upcoming NIS compliance rules—there’s intense pressure to deliver reliable, governed AI services[^9^]. At the same time, a KPMG UK study shows most Brits lack formal AI training and harbour low trust in the technology[^4^]. Below are five common pitfalls in unstructured AI initiatives—and how WaiFinder’s structured framework helps you avoid them.

1. No Clear Business Objectives

Embarking on AI without well-defined goals is like sailing without a compass. Harvard Business Review finds projects with specific, measurable objectives are 3.5× more likely to succeed[^1^]. Yet too many MSPs chase the latest tool or license package instead of mapping AI to outcomes—reducing support tickets, automating backups, or predicting server failures.
How WaiFinder Helps: Our Stage 1 Business Profile forces alignment on your client’s top business objectives before any technical recommendations start, ensuring every AI step delivers measurable ROI.

2. Poor Data Strategy & Unstructured Data

AI thrives on clean, governed data. A Forbes survey of 700 C-suite executives revealed only 12% of organisations have an enterprise-wide data strategy[^8^]. In the UK, where data silos abound—from unstructured emails to disparate CRM systems—this chaos undermines model accuracy and stakeholder confidence.
How WaiFinder Helps: Our AI Readiness Assessment flags gaps in data quality, security, and accessibility.

3. Ignoring Change Management & Skills Gaps

Deploying AI isn’t just a tech project—it’s a cultural shift. With limited AI literacy among UK workforces, skipping user training and stakeholder alignment leads to resistance and low uptake[^4^]. Consultants repeatedly warn that neglecting the human side dooms projects before they begin.
How WaiFinder Helps: Our tailored Improvement Plans, encourage equipping teams with the skills and confidence they need for sustained adoption.

4. Misaligned Solution Selection & Integration Hurdles

Choosing the wrong AI stack or custom-coding everything from scratch creates costly delays. A recent Opollo report highlights that integration bottlenecks and bespoke development needs are common reasons UK MSPs see rollouts stall[^3^].
How WaiFinder Helps: Our Use Case prioritisation with the BXT Framework ensures your focus is on solutions that not online deliver real impact, but are feasible for you organisation to deliver with success.

5. Neglecting Governance & Compliance

Regulatory scrutiny is intensifying. Under the updated NIS regulations, around 90% of MSP revenue flows through providers now in scope, with strict duties on security and incident reporting[^9^]. Overlooking governance risks not only project delays but also fines and reputational harm.
How WaiFinder Helps: We already highlight risks with recommended mitigations, but we’re also working on a dedicated Compliance platform, coming soon.

Ready to swap unstructured pilots for predictable, governed AI rollouts?
WaiFinder’s end-to-end orchestration platform guides you through every stage—ensuring fast ROI, iron-clad compliance, and seamless integration.

👉 Book your demo today and discover how our framework AI aspirations into business aligned, high-value services.

[^1^]: “Avoiding Pitfalls: Common AI Implementation Mistakes,” The AI Hat (Oct 2024)
[^3^]: Steven Morey, “The Challenges MSPs Face in Implementing AI—and Why Delaying Adoption Is Costly,” Opollo Blog (Feb 2025)
[^4^]: “UK Attitudes to AI,” KPMG UK
[^8^]: Forbes, “Only 12% of Organisations Have an Enterprise-Wide Data Strategy”
[^9^]: “Research on UK Managed Service Providers,” GOV.UK (Feb 2024)