From factory floor to future core: How AI is powering the next industrial revolution

In today’s tech-driven world, the role of AI has moved beyond enhancing operations; it is redefining the core framework of industrial value creation from accelerating R&D cycles, reinventing supply chains, and streamlining every inch of the production floor. According to the recently released Manufacturing GenAI report by NTT DATA, 64% of manufacturers already view GenAI as a game-changer, with 96% attributing this to its ability to spur creativity and innovation. The factory floor is no longer just a hub of operations but has become the digital core of manufacturing strategy. 

However, a closer look reveals a striking contradiction. Despite rising optimism for AI, operational readiness is faltering due to outdated infrastructure, policy voids, and capability gaps. This makes it crucial for businesses to revisit their AI strategies and ensure a smooth operational integration with minimal bottlenecks.

The Promise of AI: A New Industrial Core

The deployment of AI in manufacturing, once driven by strict procedures and predictable systems, is bringing in a new era of flexibility and foresight. From real-time inventory forecasting to automated quality control, AI is increasing productivity across the value chain.
For instance, the integration of data from IoT devices and digital twins into AI models is improving decision-making, asset usage, and predictive maintenance. The Manufacturing GenAI report highlights that over 90% of industrial leaders believe that supply chain resilience and mechanical performance will be greatly enhanced by such convergence. 

This transformation is entering a more advanced phase with the emergence of Agentic AI, a new breed of AI solutions that bring autonomy, proactivity, and context-aware decision-making to industrial systems. These systems don’t just analyse but also act. They have the potential to orchestrate operations, adapting to unforeseen scenarios, and learning continuously, making tomorrow’s factories not just digitally aware but self-regulating, intelligent ecosystems. India’s manufacturing sector is increasingly adopting AI technologies for automation, especially in the automotive and electronics industries. A growing number of Indian manufacturers are exploring AI use cases in supply chain optimisation, R&D acceleration, and factory automation. Programs like the Production Linked Incentive (PLI) schemes offer an ideal atmosphere for AI-driven developments, positioning the country to build a solid blueprint for digitally transformed manufacturing. 
With India’s expanding AI talent pool and its strong push towards digital public infrastructure, there is a clear opportunity for manufacturers to advance through industrial maturity phases confidently and rapidly. However, that is only possible if the leadership concentrates on overcoming the gaps in strategy.

What's Holding Back the Revolution?

Despite strong commitments, manufacturers are still struggling to operationalize AI at scale. This is due to barriers across different stages:
•    Outdated Infrastructure: AI’s potential will remain constrained without modernized tech stacks. Manufacturers have often highlighted poor legacy systems as one of the major barriers.
•    Policy Vacuum: Several organizations still lack formal AI usage policies. As factories shift toward more autonomous systems, better frameworks must be developed in parallel to ensure safe and responsible deployment.
•    Workforce Readiness: There is a technical as well as a cultural divide. Without widespread AI literacy, operational adoption will continue to be fragmented. Employees may strive to keep pace with technological evolution, but their lack of proficiency in AI will continue to pose difficulties.

Turning Eagerness into Execution

Manufacturers and leaders must act swiftly to convert optimism into outcomes. This includes focusing on three key pillars:
•    Infrastructure Modernisation: To guarantee compatibility with AI models, IoT sensors, and digital twin frameworks, manufacturers need to review and update their legacy systems. This includes overhauling control systems, industrial networking infrastructure, and edge computing platforms, as well as evaluating data centres and connectivity—including submarine connectivity speeds—to support the capabilities of newer AI systems and identify potential points of failure.
•    Ethical and Operational Guardrails: Building trust across teams and stakeholders would require developing and applying usage policies, transparency norms, and AI safety frameworks. Governance must become a core ability, and not a compliance afterthought.
•    Employee Empowerment: Initiatives to upskill and skill employees need to move beyond data science roles. Field engineers, plant managers, and line supervisors must understand how AI tools work and how to use them effectively.

Real-World Impact: Automotive Leads the Charge

At present, the automotive industry is perhaps the most visible beneficiary of AI. Its several tangible outcomes, including shortened R&D cycles due to AI-led simulations, sustainable manufacturing enabled by generative designs, and digital optimisation of materials. These also include the management of inventory and supplier networks through predictive analytics, leading to a streamlined assembly process. This has led to smart factories reducing unplanned downtime, rework, and waste. 

Looking Ahead: A Time to Lead, Not Lag

Many organisations are playing catch-up, while a few manage to stay ahead of the curve. Fortunately, not all is lost—there is still time. AI itself is continuously evolving, maturing from traditional machine learning models to GenAI, and now to Agentic AI, which brings autonomous decision-making capabilities into the mix. However, this window of opportunity is not infinite.

To stay ahead, organisations need to view AI not merely as a tool but as a foundational component of their operations, strategy, and culture. Leadership must drive this transformation from the top down, setting the tone for ethical innovation, investing in infrastructure modernisation, and empowering employees. Much like the industrial revolution redefined human construction capabilities, today’s data-driven AI—especially with the rise of GenAI and Agentic AI—is poised to reshape how processes are designed, optimised, and executed.

Avinash Joshi

---

Avinash Joshii is CEO, India at NTT DATA.