Based on: “15 AI Predictions For Small Businesses In 2026” (Forbes, 2026)
It’s January, the season of AI predictions. Everywhere you look, experts are forecasting what the next year will bring. Among the many lists out there, one recent Forbes article stood out to us. Not because it was sensational, but because its predictions feel practical, realistic, and highly relevant for organizations in Curaçao and the wider Caribbean.
After years of working with local businesses and government entities, we recognize the same challenges, ambitions, and hurdles described in the article. One prediction in particular deserves special attention: The Data Quality Crisis.
Why Most AI Projects Will Struggle
Forbes predicts that in 2026, 60% of AI projects in small and medium-sized businesses will fail, not due to lack of technology, but because of poor data quality.
AI systems rely completely on the information they are given. When that data is incomplete, outdated, or inconsistent, even the smartest tools produce unreliable results. The old rule still applies: Garbage In, Garbage Out.
As a result, many companies will discover that the real challenge is not adopting AI, but preparing their data to be AI-ready.
The Dutch Caribbean Reality
This prediction strongly reflects what we see locally.
Instead of well-structured data platforms, many organizations operate with:
- Critical information stored in Excel sheets and CSV files
- Multiple versions of the same data across departments
- Extracts without clear business rules or validations
- Systems that don’t properly integrate
These setups often work for day-to-day operations. But the moment data is analyzed or fed into an AI solution, data quality problems immediately surface.
The underlying issue is simple:
Most organizations lack a solid, centralized data foundation.
Without a place where data is consistently stored, managed, and governed, AI initiatives quickly become complex, costly, and unreliable.
The Smart Pivot for 2026
The key takeaway from Forbes is a shift in priorities. Instead of rushing into AI tools, SMEs should focus first on what the article calls “janitorial work.”
For our market, that means:
- Building a central data repository
- Implementing proper ELT processes
- Establishing data governance and privacy controls
- Actively cleaning and monitoring data quality
This foundation dramatically reduces risk and ensures that future AI investments actually deliver value.
Conclusion
AI is powerful, but only when built on trustworthy data.
For organizations in Curaçao and the Caribbean, the roadmap is clear:
Data hygiene first, innovation second.
Those who invest in strong data fundamentals today will be the ones able to successfully leverage AI tomorrow.
For a detailed legal breakdown, you can access the full article via Forbes
