How AI will transform industrials

Advanced Manufacturing and Mobility Business Minute

In this episode, Alison Clark, EY UK Advanced Manufacturing and Mobility Leader, explores the roadmap to overcome challenges and leverage AI’s potential in industrials.

Driven by the rapid adoption of artificial intelligence (AI) and generative AI (GenAI) applications, the advanced manufacturing sector is experiencing a profound transformation. The emergence of these technologies is paving the way for a manufacturing renaissance, enabling new capabilities and enhancing traditional uses of AI.

Approximately 49% of advanced manufacturing and mobility firms have integrated AI into their capital allocation, and 96% of companies are projected to elevate their AI investment by 2030.1,2 This shift toward AI-centric operations is poised to reframe the competitive landscape, with companies leveraging AI technologies to unlock new opportunities for real growth.

This episode of the Advanced Manufacturing and Mobility Business Minute podcast series features Alison Clark, EY UK Advanced Manufacturing and Mobility Leader, who explores the strategic roadmap and challenges in the journey of AI adoption. Alison emphasizes the necessity of rich data, C-suite advocacy, skilled talent and a robust infrastructure and partner ecosystem to harness AI’s full potential.

For successful preparation for AI integration, Alison outlines five key initiatives: establishing a value-realization office, aligning AI with business strategy, conducting skills assessments, developing a cohesive data architecture and building an AI partner ecosystem. Join us to discover why embracing AI is more than a trend-driven journey and requires a distinct approach tailored to each organization’s objectives.

Key takeaways:

• Companies face several challenges in adopting AI, including supply chain complexities, strategic alignment, talent scarcity and the need for robust IT infrastructure. Addressing these challenges is critical for successful AI integration.
• Effective AI implementation thrives on robust data and efficient data distribution systems. It is vital to address data misalignment, elevate forecasting capabilities and manage inventory effectively for successful AI deployment.
• The adoption of AI should be a strategic decision, not a trend-driven response. Companies must approach AI with a strategy that aligns with their business objectives.

Sources:

1. "How CEOs juggle transformation priorities – the art of taking back control, EYGM Limited," EY website, https://www.ey.com/en_gl/ceo/ceo-outlook-global-report.
2. "Manufacturing in 2030 Project," Manufacturing Leadership Council website, https://manufacturingleadershipcouncil.com/manufacturing-in-2030-project/.