Top 10 AI Risks

Understand your risks before you go all in for AI.

Successful AI implementation needs a clear business case, supported by strong data foundations, and a change management strategy that puts people at the heart.

However, you need to understand your key risks first:

⚠️ Technology-first thinking, instead of problem-solving

⚠️ Poor data quality undermining every output

⚠️ Zero user adoption plans 

⚠️ Missing ROI metrics from day one

Before you invest another £ in AI, ask yourself:

👉 Do we know exactly what problem we are solving?

👉 Is our data actually fit for purpose?

👉 Have we planned for adoption from the start?

Swipe through the carousel to see the top 10 key risks that need to be mitigated for AI projects.