Valuation of corporate strategy for adopting generative artificial intelligence in B2B operations

This paper explores the valuation of corporate strategies for integrating generative artificial intelligence (AI) within business-to-business (B2B) business models, focusing on its impact on operational efficiency, customer engagement, and competitive advantage. The research problem centres on the strategic challenges and opportunities associated with the adoption of generative this. The purpose of the study is to provide actionable insights into AI that enhance strategies for improved business performance. The methodology employs a mixed-methods approach, incorporating both quantitative data (e.g., surveys) and qualitative insights (e.g., expert interviews). Key findings reveal that operational efficiency is the primary driver for AI adoption, with companies reporting significant productivity improvements in manufacturing and logistics. However, barriers such as high initial costs and resistance to change are prevalent. The study concludes that aligning AI initiatives with strategic goals is crucial for long-term success and competitive positioning. These findings highlight the transformative potential of generative AI in B2B industries and underline the need for strategic alignment, ongoing training, and investment in AI technologies.