Supply Chains Are Getting Smarter—But Only the Prepared Will Survive

The rise of artificial intelligence and synthetic biology marks a defining moment in human history. Together forming “The Wave,” these technologies are rapidly transforming economies, societies and civilisation itself. The potential is vast – from medical breakthroughs to smarter systems and solutions to global challenges – but the risks are equally profound, including autonomous systems operating beyond human control and the manipulation of biology at its core.

AI isn’t just about what machines know—it’s about how they talk. The future of AI depends on two things working in harmony: how AI thinks and how it speaks.

A stark MIT report has jolted enterprise boardrooms by revealing that 95% of AI applications fail to yield meaningful revenue growth, with Wharton research echoing that most large firms are still “too early” in realising measurable returns. The problem isn’t the models—it’s the integration. Organisations are misfiring by applying generative AI in sales and marketing while ignoring high-impact back-office use cases like automation and data management.

A landmark investigation by consumer group Which? has revealed alarming flaws in major AI platforms like ChatGPT, Gemini, and Microsoft Copilot. Across 40 essential consumer questions—ranging from financial and legal issues to health and travel—AI responses were frequently inaccurate, unclear, or potentially harmful. ChatGPT scored just 64%, with Meta AI faring even worse at 55%. Only Perplexity exceeded 70%, leading the pack in utility and accuracy.

AI’s rapid advance in healthcare promises transformative benefits—from sharper diagnostics to streamlined admin—but the path forward demands rigorous legal and ethical frameworks. In the US, the FDA has greenlit over 1,200 AI-enabled medical devices and recently issued new draft guidance aimed at tightening oversight throughout their lifecycle. This complements broader efforts such as the White House’s AI Bill of Rights and NIST’s AI Risk Management Framework, both promoting transparency, fairness, and human oversight.

Anthropic has stepped decisively into the centre of the AI ethics debate with the release of a new open-source framework aimed at measuring political bias in AI chatbots. The tool—built around a novel “Paired Prompts” methodology—evaluates how fairly AI systems handle politically sensitive queries posed from opposing ideological standpoints. It assesses models based on engagement balance, counterargument recognition, and tendencies to decline political commentary.