A study by Deloitte titled 'The Fourth Industrial Revolution' discovered that businesses with comprehensive Industry 4.0 strategies are far more successful across the board. They’re innovating and growing faster, successfully integrating Industry 4.0 technologies, and doing a better job of attracting and training the people they’ll need in the future.
It is, therefore, almost inevitable that success in the coming decade in the manufacturing domain will revolve around a business’s ability to adapt and leverage emerging technologies like AI / ML.
The same report also found that only 10% of leaders said they have longer-range strategies to leverage new technologies that reach across their organizations. This should be seen as concerning, as AI/ML technologies provide incredible leverage to companies that incorporate it into their workflow and processes.
The role that AI can play in Industry 4.0 is by enabling manufacturers to automate complex tasks, improve decision-making, and optimize production processes. Some of the most common AI models used in manufacturing include machine learning, deep learning, computer vision, natural language processing, and robotics.
Generative Design, for instance, an area of AI that has been showing a lot of promise of late, allows designers to get AI’s help in designing products. It’s similar to the popular Text-to-Image models like Stable Diffusion or Dall-E, except for product design generation. This can have profound implications for future product designers, and how products are created.
AI has also shown potential in streamlining factory operations, helping with finding defects, reducing wastage, or improving supply-chain. These capabilities haven’t gone unnoticed. A Capgemini research found that more than half of European manufacturers (51%) are already implementing AI solutions, with Japan (30%) and the US (28%) following at second and third positions. Some of the most prominent figures in the AI world are also diving into this. As a case in point, Andrew Ng, who has authored or co-authored over 100 published papers in machine learning, and was the co-founder and head of Google Brain and the former Chief Scientist at Baidu, also co-founded Landing.ai in 2018 to do exactly this - to bring AI to the factory floor.
It is not surprising, therefore, that Industry 4.0 has been a focal point for Global Capability Centres (GCCs), which are looking to bring AI-related innovation to manufacturing industries.
India is currently home to 1,580 GCCs, a number that’s anticipated to surpass 1,900 by 2025 and 2,400 by 2030. Our country is deemed as the 'global GCC capital' with over 50% stakes in the global GCC market.
The core driver of GCCs in India comes from engineering and R&D services, contributing to 56% of the total revenue. Increasingly, they have morphed into hubs of innovation, impacting even their parent companies from where they originated. With access to a vast pool of highly skilled IT professionals, Indian GCCs have the advantage of easily locating the right talent with the necessary skills to align with the company's goals.
Their innovation-centric approach has positioned GCCs in India as key players in pushing innovation and digital transformation within the manufacturing sector. They are the ones increasingly looking to capitalize on the growing opportunities of AI in manufacturing.
India is already a notable player in the global AI arena, contributing 16% of the worldwide AI talent, which puts it in the top three global contributors. The technological workforce in the country leapfrogged to an era dominated by the internet and cloud technologies, building solutions by integrating legacy systems with cloud and SaaS components. With a skilled AI-ready workforce, GCCs have the capability now to unlock phenomenal new opportunities in the manufacturing sector.
Additionally, the India-born Cloud Service Providers (CSPs) and Hyperscalers have swiftly established the necessary Cloud GPU infrastructure and Machine Learning platforms conducive to AI innovation. This infrastructure is pivotal as AI and ML technologies are heavily dependent on advanced Cloud GPUs and Cloud GPU Clusters for training AI algorithms. GCCs are capitalizing on both this robust infrastructure and the rich talent reservoir to fuel swift innovation and advance the realization of Industry 4.0 objectives.
In the coming decade, as Deep Learning AI and Machine Learning advance further, we expect that this synergy will grow further. GCCs will push the research and innovation in AI technologies, deploying solutions at scale, and leveraging the talent pool that they have access to. Advanced GPU Cluster supply will be offered by India’s highly capable GPU Cloud Infrastructure companies. These solutions will be deployed by manufacturing companies at scale, to thrive in an increasingly AI-centric world.
Furthermore, the landscape of AI in India's manufacturing sector is set to be significantly shaped by the Indian government's active interest in becoming a major player in the global discourse surrounding AI adoption and regulation.
In the 2023-24 Union Budget, the finance minister emphasized the mantra of 'Making AI in India and Making AI Work for India'. This budget also unveiled the establishment of three 'Centres of Excellence' dedicated to AI research within top-tier educational institutions. In 2022, the revenue accrued from AI in India reached USD 12 billion, a figure anticipated to see a swift uptick in the coming decade.
This synergy involving GCCs, government policies, and forward-thinking Hyperscalers and Cloud Computing firms will be key to the next evolution of manufacturing, Industry 4.0.
