Ranjit Kohli highlights how synthetic data—artificially generated to mimic real data—is revolutionizing AI by enhancing privacy, reducing bias, and enabling rare scenario testing, though challenges like realism and validation remain.

Installing Copilot without training leads to confusion, wasted potential, and poor ROI. AI needs proper onboarding, integration, and power users to deliver value—otherwise, it's just an expensive tool gathering dust behind a Word ribbon icon.

The AI Index 2025 highlights explosive growth in AI capabilities, investment, and adoption. From outperforming humans in tasks to surging global regulation and educational expansion, AI is reshaping science, business, policy, and public opinion—while ethical and environmental concerns escalate.

Synthetic data is increasingly utilized to train AI models amid real data scarcity and privacy concerns. While it offers cost-effective and scalable solutions, challenges like model collapse, bias propagation, and ethical issues persist. A hybrid approach combining synthetic and real data, along with robust validation and ethical frameworks, is recommended to harness its benefits responsibly.