AI governance isn’t a brake on progress; it’s a strategic enabler of ethical, scaled innovation, requiring a shift to use-case focus and universal literacy.
Boards and executives must ask targeted questions to bridge their AI knowledge gap, ensuring responsible adoption and effective governance.
Creative AI is evolving beyond manual prompting to programmatic, high-throughput image generation with enhanced governance and analytics features.
AI-driven ‘vibe coding’ poses security risks, demanding a shift to DevSecOps where security is embedded throughout the automated software development lifecycle.
Despite the hype, GenAI is a multi-billion dollar bet on a technology vendors can’t own or control, requiring urgent regulation.
The limitations of current RAGs can be overcome by structuring information into hierarchical knowledge graphs for better reasoning and reliable AI.
Website interactions are shifting from static, keyword-based searches to personalised, conversational AI experiences, but human interfaces will remain crucial.
Invest in a modular, low-code AI fabric for immediate efficiency gains while avoiding costly, monolithic over-investment.
Firms face an AI talent trap; they must develop new skills and hire to stay competitive in the innovation economy.
