AI is already used to measure and maintain quality — for example, major manufacturers now use As the sophis�ca�on of AI’s capabili�es AI-powered systems to monitor increases, it will be applied more widely produc�on equipment, predict across enterprises in every industry to raise poten�al issues, and detect anomalies the overall level of excellence an in the output. And the industries organiza�on can produce and innovate upon. where “quality” is more likely to be cited as a primary mo�vator for AI deployment are those industries where there is less room for error — where significant declines in quality can have serious nega�ve effects: Consumer Packaged Goods, U�li�es, and Healthcare. For example, AI is enabling doctors to make major strides in the use of AI-assisted cancer diagnoses and robo�cs-assisted endovascular neurosurgery, among other recent developments. Increasingly, however, as AI makes employees more efficient, more produc�ve and more innova�ve, its consistent decision-making capabili�es will also help raise the bar across companies, improving the overall quality of not just products and services, but eleva�ng en�re opera�ons, func�ons, customer rela�onships, and brand values to con�nuously higher levels of performance. Technology enables the business—period Did we have any goals around this ini�a�ve? No. It was the other way around. We always have goals around business. Technologies and digitaliza�on enable the business. It's not an outcome in itself. Ul�mately, you must make or save money for the company, period. —From a masked interview with Head of AI and Automation for a large mining machines manufacturer TCS AI for Business Study Key Findings Report 33