12
According to the MIT State of AI in Business 2025 Report, only 5% of deployed AI pilots successfully scale and deliver measurable returns. The primary challenge lies not in ambition, but in the foundational capabilities required to deploy AI responsibly and at scale.
As per Sharad Agarwal, CEO of Cyber Gear, “We have launched an AI Readiness Tool designed to help enterprises and government entities assess their preparedness for artificial intelligence and identify practical actions to accelerate adoption and impact. By combining benchmarking, diagnostics, and actionable guidance, the AI Readiness Tool enables leaders to prioritise investments, strengthen governance, and make informed decisions with confidence.”
Based on Cyber Gear’s experience, most organisations are not ready. Here’s why:
The Problem
- Data fragmented across ERP, CRM, finance, and operations.
- No single agreed version of the truth across the business.
- No clear data ownership, quality standards, or governance.
- Reports that contradict each other depending on the source.
The Impact
- Decisions made on incomplete or untrustworthy information.
- Compliance risk with no data lineage or audit trail.
- AI initiatives that stall before they deliver value.
- Operational inefficiency that compounds over time.
Inference
Data management is now a strategic and regulatory priority across the UAE.
Across UAE, governments are formalising data management requirements through regulation, digital strategy mandates, and sector-specific standards.
Cyber Gear is proud to be a Dubai AI Seal verified enterprise.
For more information, visit https://www.cyber-gear.ai