AI in Action Beyond Experimentation to Transform Industry 2025

Based on engagement with industry communities and as outlined in the industry-specific papers, the primary targets of AI investment vary: –Technology firms are spending heavily on data-centre infrastructure, such as AI chips and servers, and on R&D to develop AI applications that will support all other industries. –Financial services industry are leading in AI investment, primarily by focusing on fraud detection, risk management and customer- service enhancements through AI-driven chatbots and other personalized services. –Consumer industries are adopting AI to drive in silico innovation (using computer simulations and models for research and development), enhance tailored engagement through intelligent bots, and streamline integrated business planning across functions. –Media, entertainment and sport industry are adopting AI to augment the creative process, enhance audience engagement by providing hyper-personalized content and immersive experiences, and optimize content production activities. –Telecommunications industry are building on their experience with predictive AI, and are expanding genAI use cases to drive efficiencies, improve customer service and automate network management. –Energy industry are using AI to transform operations by optimizing energy production and use, enhancing grid management and advancing sustainability. –Healthcare industry are investing in AI for clinical decision support systems, diagnostics, patient management and operational efficiencies. –Advanced manufacturers are using AI to focus on predictive maintenance, quality control and automation of production processes. Future adoption rates would depend on how pervasive tasks are augmented or automated by AI. Figure 2 shows predictions by industries of the tasks that could potentially be augmented or automated. Projection of tasks potentially automated or augmented due to genAI, by industry FIGURE 2 Software & platforms0%10%20%30%40%50%60%70% Financial services0019%17% 17% 22%15%16% 15% 13% 12%11% 33% 23% 23% 22%17%24%22% 17% 18% 17%Work time exposure (automation and augmentation) to genAI, by industry Percentage of time dedicated to tasks exposed to automation and augmentation potential High potential for automation High potential for augmentation18% Media, entertainment & sportHigh tech Travel & tourismEnergy technologyHealthcare Automotive & mobility Aviation & aerospace Consumer industriesChemicalsUtilities Advanced manufacturingMining & metals13% 18%25%26%35% 32%36% Note: Analysis of over 19,000 individual tasks across 867 occupations and 22 countries, assessing the potential exposure of each task to LLM adoption, classifying them as tasks that have high potential for automation (shown), high potential for augmentation (also shown), low potential for either or are unaffected (non-language tasks). Source: Accenture. AI in Action: Beyond Experimentation to Transform Industry 11