Leveraging AI in obsolescence management

In this article, IIOM explains how artificial intelligence can influence the semiconductor market and obsolescence management strategies.

In an era where technological advancements are reshaping industries, AI stands out as a transformative force with vast potential. According to PwC’s Global Artificial Intelligence report, AI could contribute up to $15.7 trillion to the global economy by 2030, signalling its impact across sectors. Moreover, Next Move Strategy Consulting forecasts a significant surge in AI chip market revenue, expected to reach $304 billion by 2030 from the current $100 billion.

At the forefront of this AI revolution lies the semiconductor industry, serving as the foundation for future technological innovations. With escalating demand for advanced chips capable of powering AI applications, companies like TSMC and NVIDIA are leading the charge. TSMC, the world’s largest semiconductor foundry, renowned for its state-of- the-art chip manufacturing capabilities, is producing the cutting-edge 5nm processor technology powering the latest AI chips. Meanwhile, NVIDIA dominates the market with over 80 per cent market share in AI chips, offering advanced GPU chips that stand out as the premier choice for AI applications.

However, the impact of AI extends beyond chip design, encompassing Generative Product Development and potentially addressing the impending gap of 3 to 4 million retiring engineers in Europe by 2030. AI could offer support across various engineering domains, including system and software development, plus testing and verification, ensuring workforce productivity and skill retention.

A pivotal area of AI application lies in data analysis and preparation, providing engineers with a robust foundation for decision-making. Despite
the transformative potential of AI, critics often raise concerns regarding data risks, emphasising privacy breaches and potential misuse of personal information. These concerns highlight the importance of implementing robust data governance frameworks and ethical AI practices to mitigate risks and ensure responsible deployment.

While AI plays a crucial role in shaping the future of the semiconductor industry, it also holds promise in revolutionising obsolescence management (OM) processes for businesses. IIOM recommends companies explore how AI technology can help their businesses; by leveraging AI algorithms and predictive analytics, organisations can anticipate component lifecycle trends, identify obsolescence risks, model product support plans and develop proactive mitigation strategies. AI-powered tools will enable accurate forecasting and decision-making, minimising disruption and optimising resource allocation. Integrating AI into OM processes enhances efficiency, reduces costs and ensures continuity and consistency in critical operations. Additionally, AI can streamline the OM process by automating routine tasks and workflows. This frees valuable time and resources for experts to focus on strategic initiatives and value-added activities.

As organisations navigate the complexities of AI integration and obsolescence management, embracing technological advancements and ethical considerations will be paramount in shaping a sustainable future for all industries and end users. By harnessing the power of AI, businesses can drive innovation, enhance resilience and remain at the forefront of the evolving technological landscape.

IIOM’s view is that obsolescence is not a new problem, but AI has the potential to offer a new way to manage the obsolescence challenges facing us all.