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Geoff Webb The manufacturing industry is facing incredible pressure from every side: customers, suppliers, and competitors. The solution to dealing with all of these factors may well lie in the ability to harness the potential of emerging technologies, such as artificial intelligence (AI). Manufacturing businesses today operate in an increasingly complex landscape — whether it’s managing global supply and demand, the impact of rapidly changing customer expectations, changes in taxes, disruptive technology trends, or changes to regulations and standards. Not only must manufacturers adapt to changes in this complex landscape, but they must also do so quickly to remain competitive and avoid losing market share. Yet as the business landscape continues to evolve, driven by changes in all these factors, manufacturers must constantly consider and balance a huge range of variables to their business model. Ultimately their ability to juggle these variables can dramatically affect their profitability, their market share, and increasingly, their ability to survive. Simply understanding the interactions between competitors, suppliers, global markets, customers, and business models is a task that is already outstripping traditional management methods. There is simply too much complexity and too much data for your average human to process and understand. Therefore, machine learning-based technologies are emerging as one way that businesses can ensure they stay on top of changes quickly enough to protect and grow revenue. One of the most powerful capabilities of machine learning-based technologies such as AI, is that they can consume and evaluate very large quantities of data in a way that humans cannot. This allows good AI engines to seek out patterns in huge amounts of information, and having found those patterns, proactively offer advice and guidance. Simply put, AI can look at more data, and do so more quickly and more thoroughly than a human. AI tools […]