AI in Action Beyond Experimentation to Transform Industry 2025

Adoption varies across functions, concentrating on functions that generate or digitalize large volumes of structured and unstructured data There is notable variation in adoption rates across functions (see Figure 3) – with marketing and sales, product and service development, service operations and risk management leading the way in 2023. Finance, human resources (HR), and marketing and sales are expected to experience the most disruption in tasks potentially automated or augmented, which is likely to further drive AI adoption in these functions (please refer to the World Economic Forum’s reports Jobs of Tomorrow: Large Language Models and Jobs and Leveraging Generative AI for Job Augmentation and Workforce Productivity: Scenarios, Case Studies and a Framework for Action). Functions with the highest rates of AI adoption are typically those that generate or digitalize large volumes of structured and unstructured data. The greater the data available, the more effectively AI models can be trained, refined and scaled. Adoption by function and industry, 2023 FIGURE 3 All industries Business, legal and professional services Customer goods/retail Financial services9% 7% 9%5% 9% 1%25% 28% 31% 22%9% 6% 26% 24% 15% 20% Manufacturing Human resourcesMarketing and salesProduct and/or service developmentRisk Service operationsStrategy and corporate financeSupply-chain managementHealthcare systems/pharma and medical products5% 7% 8% 26% 14% 6% 36% 44%10% 6% 28%19% 22% 31%8% 13% 2% 14%12% 24% 9% 6% 14% 4% 7% 15% 6% 11% ## 36% 6% 9%Tech, media and telecomms 7%Industry Percentage of respondents (function) Source: Maslej, N., L. Fattorini, R. Perrault, V. Parli, et al. (2024). Artificial Intelligence Index Report 2024. Stanford University. BMW introduced a platform with multiple genAI agents across its sales, supply chain and marketing functions to accelerate the conversion of data into real-time insights. The platform intelligently chooses a data source specific to the function and then pulls information corresponding to the user’s prompt. This faster transformation of enterprise data into actionable knowledge has improved productivity across both the firm’s corporate functions and on its showroom floors by 30-40%.25CASE STUDY 6 Cross-functional AI adoption AI in Action: Beyond Experimentation to Transform Industry 12