Factories on AI

By Staff Report June 6, 2025 7:20 pm IST

Once a world of grease, gears, and guesswork, today, manufacturing is run by algorithms, automation, and intelligent machines. Artificial Intelligence (AI) has become an integral part of the entire process, from design to delivery. This feature examines the AI tools that India is adopting and those that can significantly benefit the MSME sector.

As early as 1981, the Japanese government invested $850 million (equivalent to over $2 billion today) into the ambitious Fifth Generation Computer project, which aimed to develop machines capable of understanding language, reasoning like humans, and even engaging in conversations. Artificial Intelligence (AI) isn’t new; it has been part of our technological journey for decades. However, the roots of AI extend even further, intertwined with the very origins of modern computing. So, what’s changed in recent times?

In just the past few years, AI has transitioned from theory to everyday life. Today, even schoolchildren are familiar with tools like ChatGPT and image generators. Job interviews now often include questions about candidates’ familiarity with AI tools, including what they use and how effectively they use them. Across industries, proficiency with AI has become a fundamental expectation rather than a niche skill. This sudden shift has created a divide. While younger generations are adapting quickly, many mid-career professionals face increasing pressure to keep up or risk being left behind.

As the Fourth Industrial Revolution progresses, artificial intelligence (AI) is becoming a transformative force in the manufacturing sector. Once limited to research labs and tech companies, AI has now established a strong presence on factory floors. It powers predictive maintenance and quality control, enables intelligent automation, and fuels supply chains. By 2025, all manufacturers have deployed it at scale to promote resilience, efficiency, and innovation. Advanced technologies such as adaptive machines, digital twins, agentic robots, and AI-enhanced decision-making are revolutionising how products are designed, produced, and delivered. This article examines the latest breakthroughs in AI within manufacturing, highlighting the tools, trends, and investments that are the future of industrial production.

Practical AI agents

AI chatbots utilise generative AI to respond to individual interactions. When a person makes a query, the chatbot employs natural language processing to generate a reply. The next frontier in artificial intelligence is agentic AI, which utilises advanced reasoning and iterative planning to solve complex, multi-step problems autonomously. This technology is already in use by multiple manufacturers. For example, an AI agent designed for customer service could go beyond simple question-and-answer interactions. With agentic AI, it could check a user’s outstanding balance and recommend which accounts could be used to pay it off. It would wait for the user to make a decision and then complete the transaction when prompted. Agentic AI systems gather large amounts of data from multiple sources and third-party applications to analyse challenges, develop strategies, and execute tasks independently. Businesses are adopting agentic AI to personalise customer service, streamline software development, and facilitate patient interactions.  

One of the most notable impacts of AI in manufacturing is its capability to prevent equipment breakdowns before they happen. Machines are now equipped with sensors that continuously gather performance data. AI algorithms analyse this data to identify patterns and predict potential failures. This approach, known as predictive maintenance, helps reduce unplanned downtimes and prolongs the life of equipment, ultimately leading to significant savings in both time and money.

The use of digital twins—virtual replicas of physical assets and systems is another major tool. Manufacturers can simulate changes, test improvements, and optimise processes in a digital environment before applying them in the real world. This cuts down the risks and accelerates innovation.

AI-powered generative design tools are transforming the way engineers design and prototype products. These tools suggest design alternatives based on constraints like material usage, strength, and cost. This leads to faster development cycles, reduced material waste, and more creative, effective solutions. Autodesk Fusion 360, PTC Creo, nTopology, Siemens NX, and Dassault Systèmes – CATIA and SolidWorks are a few of the tools most commonly used by manufacturers.

Smart, flexible robots and humanoids significantly improve shop floors. Advanced integration platforms enable multiple robots to be programmed and coordinated quickly, allowing them to adapt to changes in tasks or production volumes without requiring extensive reprogramming. This accessibility makes automation feasible for large-scale manufacturers and small and mid-sized enterprises that aim to scale efficiently. Sameer Gandhi, Managing Director of OMRON Automation in India, shares that they deploy AI-powered robotics for precision assembly and predictive maintenance, while smart factory solutions enable real-time monitoring and analytics. These innovations have improved their quality and operations, regardless of geographical location. They also evolved their automation supply chain strategy by increasing production capacity, redesigning products to avoid hard-to-find components, and renegotiating with suppliers to increase allocated production volumes, among other measures.

AI-driven applications

Sudhanshu Mittal, Head and Director of Technical Solutions at Nasscom CoE, states that the ratio of doctors to patients in India is extremely low compared to the WHO recommendations, especially in rural areas, and this gap can’t be bridged organically. AI has begun playing a significant role in the healthcare sector and is poised to play a much larger role in the future. From using AI to analyse X-ray and MRI reports to identify cancer and abnormalities to utilising an AI-based NLP interface to address patients’ first-level queries, AI has begun playing a significant role in the healthcare system. Pharmaceutical companies have begun using AI to shorten the cycle of drug discovery and reduce costs. AI is being used to create personalised treatment plans after analysing large amounts of data to address critical illnesses. AI is also being used to identify how existing drugs can be used to treat different problems (drug repurposing). Such an approach would cut down the costly clinical trials that are a necessary part of any drug launch.

Digitalisation is becoming the norm across all industries. Prashant Sinha, Head of Marketing at WIKA India, shares, “It is also enhancing supply chain resilience and operational efficiency. Complemented by predictive maintenance in its calibration and instrumentation offerings, Industrial Internet of Things (IIoT) technologies enable the real-time monitoring of equipment parameters, such as pressure, temperature, and vibration. AI and machine learning algorithms can identify failures, allowing proactive maintenance and reducing unplanned downtime.” 

AI is transforming quality control by using computer vision systems that inspect products around the clock with high precision and consistency. These systems can detect defects that human inspectors might miss, ensuring that every item leaving the production line meets the necessary standards. This leads to improved quality, reduced rework, and minimised waste.

The advantages of AI extend beyond the production floor and into the supply chain. By analysing large amounts of data, AI can forecast demand more accurately, manage inventory levels effectively, and optimise delivery routes. This makes supply chains more resilient, decreases the likelihood of stockouts or overstocking, and enhances the overall flow of goods.

MSMEs and AI

Nasscom says AI could be a transformative opportunity for Indian Micro, Small, and Medium Enterprises (MSMEs), the one that they have been looking for for decades. AI will be able to address their resource constraints and enhance their competitiveness. MSMEs can automate processes, improve decision-making, and explore new avenues for growth by utilising AI tools and technologies. However, Indian MSMEs face numerous challenges that hinder their adoption of AI to boost productivity and growth. Key obstacles include limited resources, restricted marketing reach, and a lack of technical expertise.

45% of tech-enabled MSMEs highlighted the necessity of accessing industry-specific use cases to comprehend the practical benefits of AI. Without these, they struggle to see the tangible advantages of AI for their businesses. The scarcity of toolkits and training materials restricts marketers’ ability to utilise AI, hindering its adoption effectively.

There is low interest in adopting solutions from tech-enabled MSMEs by larger enterprises, necessitating trust-building and demonstrating value propositions. Scalability remains a significant challenge for MSMEs in managing growing data needs, largely due to limited resources and technical capabilities.

Moreover, a lack of understanding of India’s data protection laws complicates data management, with 56.4% of MSMEs expressing concerns about data privacy and security. Financial constraints impact 59% of these enterprises, while 91% believe AI should be democratically accessible. Limited training resources hinder the development of expertise, as noted by 72% of MSMEs.

The analysis of AI awareness among tech-enabled MSMEs revealed significant knowledge gaps regarding tools, technologies, and integration methods, which impede optimal AI adoption. Increasing productivity through AI requires streamlined processes and enhanced resource utilisation, yet challenges in technical integration and data quality persist for these firms.

To bridge the gap between potential and actual implementation, MSMEs require comprehensive support and education that addresses their specific needs. By launching targeted skill development programs and fostering peer learning networks, MSMEs can acquire the knowledge and confidence necessary to leverage AI technologies effectively.

Collaboration with prestigious institutions for certification programs, alongside an understanding of data protection laws, will enhance the credibility and compliance of AI initiatives within the MSME sector. Furthermore, establishing hyper-local accelerator programs and financial support mechanisms will help them navigate resource constraints while innovating with AI solutions.

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Sudhanshu Mittal, Head & Director Technical Solutions, Nasscom CoE

India has strong AI capabilities, with startups collaborating with healthcare providers and pharmaceutical companies to integrate AI in various sectors. The primary barrier to advancing indigenous technologies is the reluctance of these players to move beyond traditional methods and adopt innovative technologies.

Prashant Sinha, Head of Marketing, WIKA India.

Digitalisation is now standard across industries, enhancing supply chain resilience and operational efficiency. Combined with predictive maintenance in calibration and instrumentation, IIoT technologies enable real-time monitoring of equipment parameters, such as pressure, temperature, and vibration. AI and machine learning can identify failures, enabling proactive maintenance and minimising unplanned downtime.

G Balaji, SVP, Energy Industries, ABB India

By integrating AI-driven forecasting and predictive diagnostics, manufacturers can empower OEMs to unlock smarter energy management, anticipate issues, optimise consumption, and drive sustainable performance across global operations.

A. Shanmugasundaram, Director Amsak Cranes Pvt. Ltd.

Amsak Cranes sees AI as a catalyst for smarter lifting, enabling predictive maintenance, real-time diagnostics, and intelligent safety systems that reduce downtime and enhance operational reliability. We are focusing on areas such as AI-driven condition monitoring, energy-efficient crane systems, and the development of hybrid or battery-powered overhead cranes to support the growth of green factories.