Artificial intelligence appears in every proposal now. Real value shows up in specific cases — not everywhere. Practical uses today: ticket classification, suggested replies for staff, summarizing long reports, and anomaly detection in transactions. Watch out for: promises of “full automation” without clean data. Models learn from input quality — garbage in, garbage out. Privacy and compliance: customer data in the GCC needs clear governance. Where is it stored? Who accesses it? Is consent documented? Start with a small pilot: measure time saved or accuracy gained before scaling. Do not build an “AI platform” from scratch if you only need a focused use case. AI is a tool in the toolbox — not a strategy by itself. Thoughtful adoption wins; trend-chasing pays with no return.
AI in business software: real opportunity or hype?
Where AI adds value today — and how to avoid “AI projects” with no measurable return.
