Designing a Value-Based Business Modelfor AI-Integrated Industrial Products : A single case study of business model transformation in B2B markets

Sammanfattning

As industrial firms increasingly embed Artificial Intelligence (AI) into their physical products, they are unlocking new types of customer value such as predictive maintenance, adaptive performance, energy efficiency, and real-time operational insights. However, these benefits are often intangible, continuous, and outcome-based, making it difficult for traditional product focused business models and pricing strategies to capture their full value. This thesis investigates how firms can develop value-based strategies to better commercialize AI-integrated offerings in business-to-business (B2B) markets. Using a single-case study approach, the research centers on a company developing an AI-integrated climate control system. A mixed-methods design was adopted, combining qualitative interviews with internal stakeholders and a customer survey to explore value perceptions and pricing expectations. The analysis contrasts the company’s existing product-centric approach with a proposed value based business model tailored for AI-driven solutions. From this, two practical frameworks are introduced: A Four-Step Value-Based Strategy Framework, which helps firms move from identifying customer value to redesigning their business model, and A Customer Value-Pricing Quadrant, which links different types of customer-perceived value to pricing strategies based on their measurability and nature. The findings reveal shifts across key elements of the Business Model Canvas, including the value proposition, revenue logic, customer relationships, and cost structure, highlighting the broader transformation required to align AI-enabled value with effective monetization. Ultimately, the research offers a structured pathway for firms to transition from selling products to delivering outcomes, and from pricing based on features to pricing based on customer-perceived value.