A recent study by MIT and McKinsey has found that artificial intelligence (AI) is providing faster returns for manufacturers and operations than in previous years. However, the report also highlights a growing divide between companies effectively using AI and those struggling to keep pace.
The launch of OpenAI’s ChatGPT in late 2022 brought widespread attention to generative AI. Since then, businesses have sought to tap into what analysts estimate as $2.6 to $4.4 trillion in potential value from AI applications.
AI use cases in manufacturing go beyond customer-facing chatbots. Companies are leveraging the technology to improve back-office functions and streamline operations. For example, a global pharmaceutical company implemented a generative AI tool to review supplier invoices. This system read invoice details from PDFs with 95% accuracy, identified over $10 million in lost value within four weeks, and flagged recurring costs not covered by contracts, allowing for better negotiations.
Despite these successes, many companies face challenges integrating AI into their processes or scaling its use across departments. The study examined more than 100 companies and included interviews with 15 organizations. It identified four main factors that distinguish leading AI adopters: executive support, strong partnerships with vendors and experts, cross-team collaboration, and investment in reliable data systems.
Common obstacles include difficulty measuring return on investment (ROI), limited resources, and uncertain outcomes from new technologies like AI. Nevertheless, some leaders are reporting project returns up to five times higher than their costs within five years.
One case cited involves a multinational manufacturer attempting to enhance its advanced process control systems with AI. After an initial failed partnership due to a lack of understanding of the company’s unique needs, the manufacturer developed its own system that was both faster and less expensive to operate.
Partnerships remain important for success; 67% of leading companies work with external partners compared to only half of lower-performing firms. The nature of these collaborations is shifting away from universities and start-ups toward consulting firms, vendors, and industry partners as the market matures.
The study also notes that payback periods for AI investments are shrinking. While earlier research showed leading companies saw returns within 12–18 months—and others took even longer—current findings indicate payback can now occur in just six to twelve months as technology advances.
Researchers conclude that companies prioritizing executive involvement, robust partnerships, connected data teams, and reliable data infrastructure are positioned for improved performance gains through AI adoption.
“AI is transforming manufacturing and operations—but success isn’t guaranteed. Companies that invest in leadership support, partnerships, collaboration, and data are pulling ahead quickly. For everyone else, the message is clear: adapt now, or risk being left behind.”
