Manufacturers race to close AI readiness gap amid optimistic forecasts for autonomous operations

A new report reveals manufacturers are rapidly investing in AI and data infrastructure, yet foundational gaps threaten to slow progress towards autonomous, intelligence-driven factories by 2026.

Global manufacturers are moving rapidly towards intelligence‑driven operations and higher levels of autonomy, but substantial foundational gaps threaten to slow the shift, according to the TCS–AWS Future‑Ready Manufacturing Study 2025. The report finds that 75% of manufact...

urers expect artificial intelligence to be among the top three contributors to operating margins by 2026, yet only 21% say they are fully AI‑ready , a shortfall the study attributes to weaknesses in data, systems integration and plant maturity.

According to the original report, manufacturers are prioritising investments in data and cloud foundations to support decision intelligence and autonomous workflows. Agentic AI , systems that can act and decide with limited human direction , is emerging as a central capability: 74% of respondents anticipate AI agents will manage 11–50% of routine production decisions by 2028. The study adds that nearly 40% of firms embedding AI into quality and planning use cases are already reporting early, measurable gains at the factory level.

Industry data shows improved real‑time supply‑chain visibility is already being realised: 67% of participants reported enhanced visibility that strengthens resilience and responsiveness. More than 30% of manufacturers forecast meaningful productivity gains from AI‑led modernisation, signalling expectations that intelligent automation will translate into tangible operational improvements and margin expansion.

Speaking to the potential role of AI, Anupam Singhal, president – manufacturing, TCS, said, “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.” The company framed these comments within the context of firms accelerating foundational investments to reach real‑time decision intelligence.

The report stresses, however, that optimism on margins outpaces preparedness. Legacy systems, fragmented data and uneven integration across plants and supply networks remain material risks to realising the projected benefits. In that light, the study adopts a cautious editorial stance: while vendors and partners highlight AI’s potential, manufacturers must prioritise data quality, interoperability and governance to avoid costly implementations that underdeliver.

Ozgur Tohumcu, general manager – automotive and manufacturing, AWS, framed the shift as architectural as well as technological, saying “Manufacturers today are facing unprecedented pressure , from tight margins to volatile supply chains and workforce gaps. 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 enables not just faster response times, but fundamentally transforms operations with AI‑driven predictability, resilience, and agility. 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.”

For manufacturers, the practical implication is clear: to convert expectations into margin gains by 2026 they must accelerate foundational work now , upgrading data pipelines, modernising legacy control systems, and embedding governance , while pursuing targeted AI pilots that demonstrate measurable returns and scale.

Source: Noah Wire Services