Organizations seeking to excel at identifying and capturing convergence opportunities must maintain disciplined focus on economic fundamentals while continuously evaluating how technological evolution creates new value chain positioning options. They need to recognize that successful convergence strategies begin with a clear understanding of customer economics and value creation potential, rather than over- focusing on technological combinations alone. By systematically analysing how technology combinations reshape value chains, leaders can identify emerging revenue streams before competitors recognize the same opportunities, positioning their organizations to capture disproportionate value.This is exemplified today in the healthcare industry, where organizations are combining genomic sequencing technology (custom), AI diagnostic models (product) and electronic health record systems (commodity) to create personalized treatment protocols (Figure 4). Solutions such as UPMC’s Enhanced Detection System for Healthcare-Associated Transmission (EDS- HAT), which combines ML with whole genome sequencing and EHR data, are saving hospitals as much as $700,000 over a two-year period through improved infection control.9 1.3 Compounding Exponential ecosystem impacts through scaled adoption Once convergence takes hold, compounding effects drive exponential adoption and cost reductions. The compounding stage transforms promising convergence plays into market-defining forces through scale economics, network effects and ecosystem dynamics. Two reinforcing mechanisms drive compounding effects: 1 Firm-level scale economics: As combined tech solutions gain market adoption, organizations benefit from traditional scale economics, including: –Production efficiencies: Unit costs decline as fixed development costs are spread across larger volumes. For example, a logistics company deploying AI-enhanced robotics might slash delivery costs by 25% as adoption scales. –Learning effects: Performance improves as organizations accumulate implementation experience. In the same example as above, the logistical company using robotics uses the data it collects to refine its AI, further boosting efficiency. –Business model innovation: The above changes impact the scaling capabilities of the early adopter, enabling new pricing and delivery models, not possible at lower volumes or for other ecosystem actors to match – unless they adopt the same tactics. 2 Ecosystem network effects: Beyond firm- level benefits, compounding creates powerful ecosystem dynamics that further accelerate adoption and value creation: –Standards emergence: As solutions scale, de facto standards emerge that reduce integration costs. –Complementary innovation: Third parties develop complementary products and services that enhance core solution value. –Supply chain maturation: Specialized suppliers emerge to deliver components at lower costs and higher quality. –Regulatory adaptation: Governance frameworks evolve to accommodate new technologies, reducing compliance uncertainty. Strategy leaders who recognize these ecosystem dynamics can position their organizations to capture disproportionate value by establishing positions that benefit from complementary innovations or by creating dependencies that lead to long-term competitive advantage. Technology Convergence Report 11

Technology Convergence Report 2025