TCS and AWS Study Reveals AI Readiness Gap in Manufacturing

A study released by Tata Consultancy Services (TCS) in partnership with Amazon Web Services (AWS) reveals that global manufacturers are accelerating their transition towards intelligence-driven operations.

The research, titled the Future-Ready Manufacturing Study 2025, provides a data-driven view on how the industry is strengthening its digital and data foundations to enable greater autonomy and decision intelligence.

The findings, which included 216 senior leaders across North America and Europe, show a disparity between ambition and reality.

According to the study, while 75% of respondents anticipate AI becoming one of the top three contributors to their operating margins by 2026, only 21% report that they possess full AI readiness.

This could suggest foundational gaps in data integration and system preparedness across manufacturing plants and their associated supply chains.

The research included leaders from the automotive, industrial machinery, aerospace and defence, process industries, chemicals and heavy equipment sectors.

The rise of agentic AI in production

A key development highlighted in the study is the growing role of agentic AI, which facilitates the autonomous analysis of data.

The research found that 74% of leaders expect AI agents to manage between 11% and 50% of routine production decisions by 2028.

This move towards next-generation autonomy could see agentic AI assume a central role in how decisions are made across manufacturing environments, potentially leading to self-optimising workflows.

"Manufacturing is an industry defined by precision, reliability, and the relentless pursuit of performance.

"Today, that strength of foundation becomes multifold with AI in orchestrating decisions – delivering transformational business outcomes through greater predictability, stability and control," explains Anupam Singhal, President of Manufacturing at TCS.

"At TCS, we see this as a defining opportunity to help manufacturers build resilient, adaptive and future-ready enterprise ecosystems that can thrive in an era of intelligent autonomy."

Advancing factory-level intelligence

At the factory level, manufacturers are beginning to integrate AI-powered use cases for quality and planning, with the study showing nearly 40% are reporting early measurable gains.

These developments are taking place as manufacturers face a range of pressures.

The move from manual, reactive processes to intelligent, self-optimising systems could help address some of these challenges.

"Manufacturers today are facing intense pressure: from tight margins to volatile supply chains and workforce gaps," adds Ozgur Tohumcu, General Manager of Automotive and Manufacturing at AWS.

"At AWS, we are transforming manufacturing through AI-powered autonomous operations, shifting from manual, reactive processes to intelligent, self-optimising systems that operate at scale.

"By embedding artificial intelligence into every layer of the operation and leveraging cloud-native architecture, manufacturers can move beyond simple automation to true autonomous decision-making, where systems predict, adapt and act independently with minimal human intervention.

"This study makes it clear: the future of manufacturing is not just digital, it is autonomous – powered by AI that learns, evolves and operates continuously."

Enabling comprehensive manufacturing transformation

TCS supports manufacturers in this transformation by providing services across the value chain, from consulting and IT modernisation to digital manufacturing and cloud platforms.

Solutions such as TCS Manufacturing AI for Agentic Futures are designed to help manufacturers become more intelligent and adaptive.

Within the supply chain, agentic AI can be used for autonomous analysis of data, including market trends, inventory levels and supplier performance, resulting in more optimised purchasing and logistics.

According to the research, 67% of surveyed leaders report enhanced real-time visibility, strengthening resilience against disruptions.

In the factory itself, AI underpins predictive maintenance, quality control through real-time inspections and process optimisation.

These advancements require manufacturers to build stronger data foundations, invest in workforce upskilling and ensure effective cloud integration to support autonomy at scale.