Artificial Intelligence (AI), and particularly Generative AI (GenAI), have significant potential to drive efficiencies in businesses – however, it is often not being utilised to its fullest potential. Most companies have a long list of use cases for AI – some of which have been successfully installed – but this is not a comprehensive AI strategy. To see the full benefits of AI tools, businesses must adopt a structured, forward-thinking approach to implementation and long-term use.
Use cases for AI currently almost solely focus on enhancing efficiency. Our study of over 200 applications revealed that most improvements were incremental, offering measurable time and resource savings, with only 20% of use cases impacting business models.
Incremental efficiency gains, such as AI fact-based negotiations, identification of invoice errors or creating marketing content, offers measurable time and resource savings. Business growth driving use cases include online offers, customer targeting and product offer and own brand improvements as well as reduced product development cycles.
AI driven business transformation (especially if focused on efficiency gain or cost improvements only) must not target a single use case implementation. It requires a more holistic picture:
The potential for AI impact varies across departments, with some functions being more suited for automation than others. We found the highest potential for AI in Marketing, IT, Category Management & Procurement, and E-Commerce:
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