Tag: Progress Data Platform

Syngenta is showing why the future of agricultural innovation depends not just on more data, but on making scientific knowledge searchable, connected and usable at speed. By building an AI-powered semantic search platform, the company helped scientists find critical research faster, reduce knowledge silos and accelerate R&D decision-making.

This blog explains the difference between AI ethics and AI governance, showing how responsible AI principles such as fairness, transparency, privacy, safety, accountability, and human oversight can be translated into practical policies, controls, workflows, and evidence. It outlines why governance matters as AI adoption grows, how organizations can manage risks, and how a structured approach helps teams build AI systems that are trusted, explainable, auditable and aligned with both enterprise goals and broader public-good outcomes.

With CHAPS 2027 ahead, the real opportunity for payment providers is not just meeting ISO 20022 requirements, but building the data foundation needed to use richer payment information with confidence.

AI pricing is increasing, but the real problem is token waste. Enterprises are overspending because poor data architecture forces models to process too much irrelevant context. Better retrieval, semantic enrichment, rules, and governance reduce cost, improve accuracy, and make AI more scalable.

Trust is now the differentiator: AI capability is rising fast, but enterprise adoption depends on governance, explainability and control. User-first beats tool-first: The winning model is bringing AI into the flow of work, not forcing people to learn complex tooling. Boring is what scales: Predictable, policy-aligned and auditable AI is what turns pilots into production outcomes.