Organizational Transformation in the Age of AI How Organizations Maximize AI%27s Potential 2026

Four operating model shifts in R&D and innovation FIGURE 3 4From linear execution... Insights flow continuously across research, development, testing and launch. New activities: model training/validation, data curation, AI oversight; the trained model becomes an asset.to short, evidence-driven learning cycles1From narrow exploration... AI-augmented discovery increases the number and diversity of hypotheses explored early. to expanded option space 2From late failure... Decision gates move earlier, using partial but richer evidence. Activities shifted upstream: manufacturability, regulatory and quality considerations become inputs earlier, guided by AI sims.to early risk calibration 3From physical-first... Virtual simulations replace most forms of early physical testing in the value chain. Activities eliminated or automated include manual screening, routine data aggregation and repetitive experiment documentation.to virtual-first validation Organizational Transformation in the Age of AI: How Organizations Maximize AI’s Potential 20