CASE STUDY 3 The electric vehicle ecosystem The compounding effects in electric vehicle (EV) adoption illustrate these dynamics. Initial adoption faced challenges of high vehicle costs, limited range and inadequate charging infrastructure. As adoption has scaled, battery costs declined by 90% over the past 15 years,10 charging networks expanded from isolated corridors to comprehensive coverage, and regulatory frameworks evolved to support electrification through incentives and standards. Organizations that recognized these compounding dynamics early secured advantageous positions in establishing battery manufacturing scale, securing critical mineral supply chains and developing proprietary charging technologies that created lasting competitive advantages as the market matured. For executive decision-makers, the compounding phase requires strategic patience combined with aggressive execution. They must maintain investment through early adoption challenges while constantly optimizing for scale as markets develop. Organizations that master this balance achieve what appear to be “overnight successes” that actually result from years of strategic positioning for inevitable compounding effects.Compounding should not be viewed as a final stage of a process but as a catalyst for the next wave of technological combinations that creates a self-reinforcing cycle. The cycle activates when compounding standardizations inspire firms to seek new technological combinations, otherwise known as “The Innovator’s Dilemma”. Early adopters of converged technologies who captured premium margins find their competitive advantages gradually reduced as technologies become widely available at decreasing costs. Standardization is beneficial for the ecosystem but presents a strategic challenge for individual companies seeking continued differentiation. NVIDIA exemplifies this cycle. As general-purpose GPUs became standard for AI training, NVIDIA recognized the need for new combinations to maintain its market advantage. The company invested heavily in combining its hardware expertise with specialized AI software frameworks (CUDA, cuDNN) and application-specific integrated circuits. This strategic pivot towards new combinations allowed NVIDIA to capture extraordinary value as AI compounding accelerated – increasing its market capitalization from approximately $300 billion to over $3 trillion in just three years. Similarly, as LLMs reach compounding scale and standardize through application programming interface (API) access, companies like Anthropic and OpenAI are already pursuing new combinations – integrating LLMs with agent architectures, specialized reasoning capabilities and domain-specific training techniques – to create the next wave of differentiated AI applications. Technology Convergence Report 12

Technology Convergence Report 2025