Businesses are struggling to implement "responsible AI" - but it could make all the difference (www.techradar.com)

Experian’s new report finds widespread recognition that “responsible AI” is both a competitive advantage and a major implementation challenge: 89% of UK business leaders say AI already improves performance, 87% expect responsible AI to set winners apart in 2–3 years, yet 76% call putting it into practice one of their biggest hurdles. Fewer than half of organisations (45%) have integrated responsible-AI practices and only 48% feel their teams are prepared. Key barriers are gaps in technical expertise (32%), translating models into real-world use cases (31%), and balancing rapid innovation with governance (30%). Experian frames responsible AI around four principles—reliability, privacy protection, bias minimization and risk management—and highlights data quality as the critical enabler: 90% agree it’s essential but only 43% trust their data. The report urges concrete steps for AI/ML teams: continuous model-performance assessment, privacy-by-design, explainability tooling, bias monitoring, security hardening, simulated testing before deployment, and diverse cross-functional teams. The implication for the AI community is clear: organisations must invest in data, governance, tooling and talent to operationalize responsible AI—both to reduce operational/legal/ethical risk and to preserve the productivity gains models deliver.