Abstract
Artificial intelligence (AI) has emerged as a game-changer across industries in the rapidly evolving digital landscape. Industry experts have started AI implementation and believe AI is the transformative force that can revolutionise Industry 4.0. However, the results and impacts are questionable as data fragmentation, inefficient decision-making, and operational bottlenecks persist even with AI implementation. It leaves the stakeholders hesitating if AI is the key to unlocking the potential or improving Industry 4.0. Digitisation, which systematically transforms traditional processes, data, and systems into digital formats, lays the groundwork for broader technological transformation. Digitalisation, in turn, takes a more integrated approach by utilising digital data and technologies to reshape business operations and streamline workflows. Both digitisation and, more significantly, digitalisation have been recognised as essential enablers for successful AI implementation. However, the significance of digitalisation remains a question, as some stakeholders consider it to be an optional step instead of a prerequisite for AI. Without a mature digital ecosystem, AI-driven solutions often face inefficiencies, including delayed and inaccurate data processing, as well as redundant workflows that result in misleading insights. This work employs the Six Sigma methodology, often known as DMAIC (Define, Measure, Analyse, Improve, Control) methodology, to systematically assess the necessity of digitalisation prior to AI adoption. A case study in the manufacturing industry is presented to illustrate the gaps or limitations of implementing AI without a mature digital ecosystem. The application of the Six Sigma methodology defines key challenges in non-digitalised manufacturing environments, measures performance disparities, analyses root causes of AI failures, improves AI integration through structured digital transformation, and finally establishes control mechanisms for sustainable AI-driven operations. The findings reflect that a well-established digital ecosystem is critical for AI success. This work provides a strategic framework for policymakers, businesses, and industries as a guide for improving the digitalisation process and maximising AI's potential in the future.
