Transforming Consumer Industries in the Age of AI 2025

A dynamic and interactive control tower for end-to-end automated contract life cycle management, supplier review, order management and vendor risk assessment – ensuring consistent sourcing, improving efficiencies and mitigating disruptionIntelligent sourcing and supplier management Al-powered integration of structured and unstructured data and real-time insights for demand sensing, predictive and prescriptive analytics, suggesting next-best actions and enabling higher agility to prevent stockout or over-production scenarios Hyper-automation incorporated into manufacturing and distribution via real-time data, which seamlessly links Al/ML-based algorithms with scalable robotics for self-monitoring, self-learning and self-correcting supply chain systemsInsights-driven demand sensing and forecastingSupply assurance and profit-to-serve focus with proactive optimization Agile segmented service with multi-speed delivery and ever-changing flow paths based on unstructured data Self-monitoring/self-correcting systems that require less manual intervention while improving yield, quality and overall throughput Self-adaptive manufacturingStrategic bet Reinvented processesTop areas where AI technologies can drive value in operations and supply practices FIGURE 18 The adoption of such comprehensive thinking is at an early stage overall. More than a third (35%) of consumer industries executives, however, are adopting AI and genAI initiatives in the area of customer and consumer engagement, followed by 23% in operations and supply and 21% in innovation and growth, with strong results. Strategy and planning is an emerging area where adoption hasn’t yet taken hold, though this may change in the coming years.35 3.6 Intensifying cross-domain collaboration Each mega process implies and anticipates amplified and deepened connections across domains within the consumer industries. In fact, these connections may present early opportunities for significant differentiation. The ability to work faster and better within an enterprise goes hand-in- hand with the ability to extend those collaborative properties up and down the value chain. With that in mind, executives should also be exploring and evaluating future cross-domain scenarios, asking questions such as: “What pain points might be addressed through more expansive data sharing?” and, “In what ways could companies across domains increase their transparency in other areas to support customer and consumer engagement?”. If a company wants to drive strategic differentiation, its leaders first need to get their own house in order, harnessing AI to break down internal segregation and advance and accelerate workflows. The next frontier is more focused on reaching out to others in the value chain, working at the leadership level to establish rules that enable breakthrough levels of collaboration, innovation and growth. Source: Accenture. Transforming Consumer Industries in the Age of AI 23