Deep dive: AI for scientific discovery — the hidden trade-offs and how to manage them
What's working, what isn't, and what's next — with the trade-offs made explicit. Focus on data quality, standards alignment, and how to avoid measurement theater.
Discover 7 articles exploring discovery, from foundational concepts to advanced strategies and real-world applications.
What's working, what isn't, and what's next — with the trade-offs made explicit. Focus on data quality, standards alignment, and how to avoid measurement theater.
A step-by-step rollout plan with milestones, owners, and metrics. Focus on KPIs that matter, benchmark ranges, and what 'good' looks like in practice.
A concrete implementation with numbers, lessons learned, and what to copy/avoid. Focus on implementation trade-offs, stakeholder incentives, and the hidden bottlenecks.
A practical primer: key concepts, the decision checklist, and the core economics. Focus on data quality, standards alignment, and how to avoid measurement theater.
Signals to watch, value pools, and how the landscape may shift over the next 12–24 months. Focus on data quality, standards alignment, and how to avoid measurement theater.
Myths vs. realities, backed by recent evidence and practitioner experience. Focus on KPIs that matter, benchmark ranges, and what 'good' looks like in practice.
A practitioner conversation: what surprised them, what failed, and what they'd do differently. Focus on implementation trade-offs, stakeholder incentives, and the hidden bottlenecks.