The single biggest overlooked factor in AI

Why a lack of competence costs firms more than any AI tool ever will

1 | A Shiny Promise, then Reality Bites

Artificial intelligence has become a buzz-word. From chatbots to predictive analytics, boardrooms love the headlines, procurement teams love the demos—and budgets are waved through in record time. Yet many investment and real-estate firms neglect the decisive lever: internal AI expertise.

2 | The Competence Gap in Numbers

• Fewer than 3 % of European finance and property companies say they have a clear AI up-skilling plan.

• Over 60 % of purchased AI software licences are used only in a bare-bones fashion—mainly for basic reporting, not real modelling.

• Nine months is the average time (Gartner) before a new AI solution reaches day-to-day operations—if it ever does.

Sources: Gartner AI Adoption Survey 2025; Deloitte Tech Trends Report 2024

3 | Why Expensive Tools Alone Don’t Deliver

Data-literacy deficit: Without an understanding of data quality, ethics and modelling, the smartest dashboard becomes a black box.

Use-case gap: Staff know their own pain points better than any consultancy—yet they’re rarely involved in workshops.

Change-management blind spot: AI reshapes processes, roles and KPIs. Ignore that dimension and you’ll harvest resistance, not ROI.

4 | Especially Critical in Investment & Real Estate

Challenge	Typical oversight	Consequence
Portfolio valuation	Off-the-shelf valuation models bought in; analysts don’t grasp the parameters.	Poor buy-in, manual double-work
Risk scoring	External AI ratings adopted with no internal review.	Misclassification risk
Acquisition forecasts	Forecast tools remain an IT playground.	Sales teams stick to Excel

5 | Roadmap to AI Competence

• Skill audit before tool selection – map which roles need which knowledge and invest there first.

• Pilot workshops with business units – a small real use-case (e.g. vacancy forecasting for one property) builds proof of concept and trust.

• Establish AI buddies – tech-savvy employees coach colleagues in short lunch-and-learn sessions.

• Redefine ROI metrics – track not only savings, but also competence gains and process speed.

• Iterative up-skilling – micro-learning (10-minute videos, quiz apps) embeds knowledge far better than a two-day seminar.

6 | Cost vs Benefit: A Worked Example

Scenario	Annual software cost	Training cost	Efficiency gain	Break-even
Tool only	€120 000	€0	+ 5 %	> 5 yrs
Tool + training	€120 000	€40 000	+ 22 %	< 18 mths

7 | Conclusion

The real game-changer in AI adoption is not the next big model but your people’s ability to use it well. Buy a tool without building competence and you pay twice: first for the software, then for the disappointment. Invest instead in skills and culture and you create an organisation that not only uses AI, but understands it—unlocking competitive advantages no licence agreement can guarantee.