Ololade Shonubi
Future organisational success will increasingly depend on harnessing generative artificial intelligence (GenAI) for innovation differentiation. This conceptual paper examines how GenAI transforms product and service innovation strategies and introduces the GenAI Recombination-Targeting-Improvement (RTI) paradigm, showing how organisations can leverage generative intelligence to create distinctive offerings and achieve sustainable competitive advantage. The paradigm comprises three components: scalable recombination (generating novel solutions through AI-powered creative synthesis), precision targeting (delivering personalised innovations to specific market segments), and iterative improvement (continuously enhancing offerings via AI-driven learning loops). Together, these components mark a shift from linear innovation processes to dynamic, adaptive systems. Drawing on strategic management, innovation theory, digital transformation literature, and qualitative case studies from NVIDIA (AI semiconductor firm), DiDi (mobility services provider), JPMorgan Chase (financial services), and IBM Watson Health (health technology provider), the paper illustrates how organisations are moving from static product attributes to fluid, AI-enabled innovation ecosystems. The RTI paradigm addresses theoretical gaps in AI strategy integration and provides a framework for understanding how generative intelligence reshapes competitive dynamics. It reconceptualises differentiation as an emergent property of human-AI collaboration rather than a fixed capability. Importantly, generative artificial intelligence does not replace human strategic agency but reshapes its locus and leverage, repositioning managerial influence towards the orchestration of human-AI innovation ecosystems. The paper concludes with an RTI Framework Readiness Assessment and Component Mapping, offering propositions for empirical validation and guidance for practitioners preparing for a GenAI-driven competitive landscape.