Many manufacturers are already experimenting with AI technologies in areas such as product design and development, supply chain management, plant operations, sales and marketing, distribution, and after-sales service. The TCS AI for Business Study has found that most senior executives in manufacturing are optimistic about the latest advancements in AI. This report provides unique insights into how manufacturing companies are moving forward to create effective AI strategies for their enterprise.
This report investigates:
Most manufacturing executives we surveyed have a positive sentiment toward AI.
Yet there’s no consensus on AI adoption strategies and not enough metrics to measure success.
When it comes to concerns about AI, especially with the hype around generative AI (GenAI), the five strategic challenges that are top of mind for manufacturing companies are:
As the integration of AI into business processes accelerates, the expected financial return on such an investment becomes increasingly significant. But only 15% of manufacturing companies said they have "good enough" metrics and KPIs for their current stage of AI deployments. Without adequate KPIs for AI-enabled operations, proving ROI and getting future buy-in is challenging.
Future of AI
Most manufacturing executives believe AI will augment and enhance human capabilities, enabling people to focus on high-value activities that require creativity, empathy, and strategic thinking.
66% of companies think human-centric decision-making and creativity will remain essential to their competitive advantage.
As AI becomes more advanced and part of “business as usual”, the role of humans in the workplace will evolve. Within the next three years, 44% of companies expect most of their employees will be using GenAI on a daily basis.
Innovation and revenue growth will be a focus for future AI implementations. 77% of Pacesetters in manufacturing—the more financially successful companies we surveyed—are primarily focused on using AI to spur innovation.
Embrace AI initiatives that support organizational priorities and use cases that can potentially enhance value chains and drive business outcomes like revenue growth, cost savings, and improved customer experience.
Create a multidimensional approach to AI adoption that encompasses strategic goals beyond productivity and revenue growth to include improving quality, reducing risk, and enhancing operational efficiencies and organizational decision-making.
Invest not only in the necessary technology and infrastructure, but also in a culture that embraces change, experimentation, and continuous learning.
Capitalize on AI’s capabilities to deliver more personalized, proactive, and valuable experiences across the customer journey, differentiating your business from the competition.
Be ready for AI to expand revenue, opportunities, and innovation while creating new ways for humans to do their current jobs or even create new roles.
TCS’ Thought Leadership Institute conducted an anonymous study of approximately 1,272 senior executives with P&L responsibilities in 12 industry sectors across Asia, Europe, Nordics, LATAM, North America, and the United Kingdom and Ireland, with respondents having an annual revenue of $5 billion to $100 billion.
The manufacturing industry findings are based on feedback received from 184 survey respondents. This global study examines how CEOs, directors, and business line managers prepare their businesses to be AI-ready, focusing on aspects such as their strategy around operations, talent, and future implementation plans. The study also provides best practice recommendations based on these insights.
