Tata Consultancy Services (TCS) on Thursday launched an artificial intelligence (AI) platform for industrial enterprises that could improve manufacturing productivity by 20-25% and cut new product development timelines by 25%, as companies look to scale AI adoption beyond conventional business applications.

Its AI platform, Industrial Intelligence Foundry, combines configurable AI agents, workflows and governance capabilities to support engineering and manufacturing operations across sectors such as aerospace, mobility, semiconductors, medical devices, industrial electronics, utilities and energy.

Unlike general-purpose AI platforms, the offering is designed to integrate with existing enterprise workflows, eliminating the need to build AI agents from scratch. Productivity gains could exceed 40% as data foundations and operating ecosystems mature, TCS said.

The platform supports applications across product development, manufacturing operations, asset performance, quality management and compliance. Its Human+AI Service Autonomy Model seeks to augment decision-making across engineering, manufacturing and field operations.

“The next wave of industrial AI will be shaped by how effectively AI agents are orchestrated to transform engineering, plant systems, and asset-centric operations,” said Sreenivasa Chakravarti, global head and vice-president of Industrial Autonomy and Engineering at TCS.

“While enterprises are scaling their use of AI agents, our firm belief is that the AI era will be won by context-aware agentic deployment across enterprises,” he said.

Ramachandran S, practice leader at HFS Research, said industrial and physical AI offered opportunities beyond conventional enterprise applications.

“Most enterprise AI still lives on desktops, while there is untapped value on shop floors in industrial and physical AI,” he said.

Industrial organisations plan to double physical AI spending over the next two years, according to HFS Research findings.

“Industrial Intelligence Foundry is TCS’ bet to fill this gap with domain-specific AI, with the potential for significant business impact, scaling AI implementations and not just another agentic AI project,” he said.