The market for robotic products is growing steadily and the demand for humanoid robots is strong and well-articulated.
NEW DELHI: Newer versions of AI, smarter automation and stronger compute power will be the defining technologies of 2025. Let’s take a look at three deep shifts that will impact global industry.
AUTOMATION AND ROBOTICS
Mainstreaming of humanoid robots will impact societies and economies. Highly populous countries with young populations will have to rethink their policies for employment, labour.
When Tesla founder Elon Musk showed off Optimus in October 2024, an autonomous assistant that can “do anything”, it triggered fresh interest about the impact and utility of humanoid robots. At an event in Los Angeles, he showcased fully self-driven cabs and vans that will operate without pedals and a steering wheel. The three products will be made for mass consumption globally.
The market for robotic products is growing steadily and the demand for humanoid robots is strong and well-articulated. A report by Goldman Sachs Research estimates that the global market for humanoid robots will in 10-15 years be worth $38 billion from a previous forecast of $6 billion. The market could even be much bigger. “Should the hurdles of product design, use case, technology, affordability, and wide public acceptance be completely overcome, our analysts envision a market of up to $154 billion by 2035 in a blue-sky scenario,” according to the report named “Humanoid Robot: The AI Accelerant” released earlier last year.
Humanoid robots have become smarter, cheaper and more human owing to a collection of factors. Firstly, the cost of components and parts has reduced as other machines get robotic features. Artificial intelligence (AI) has allowed such robots to improve their latency in response and become more lifelike. According to the Goldman Sachs report the manufacturing cost of humanoid robots has dropped: From an estimated $50,000 (for a lower-end model) and $250,000 (top version) to a range of $30,000-$150,000 now. While analysts had expected costs to reduce 15-20 per cent per annum, they declined more than 40 per cent.
Not surprising then that Musk announced that Optimus could be available for as low as $20,000. The robot will be a household help, watering plants, serving food and managing other sundry chores. “It will basically do anything you want. It can be a teacher. It can babysit your kids, walk your dog, mow your lawn, get the groceries, just be your friend, and serve drinks. Whatever you can think of, it will do and it’s going to be awesome,” he said at an event called “We, Robot”.
A report by Morgan Stanley predicted that by 2040 the United States (US) may have 8 million working humanoid robots, with a $357 billion impact on wages. By 2050 the number of humanoid robots will rise to 63 million, potentially shaping 75 per cent of occupations, 40 per cent of employees and roughly $3 trillion in payroll. The investment bank’s analysts said that as many as 70 per cent of construction jobs and 67 per cent in farming, fishing and forestry could be impacted in the US alone.
Boston Dynamics has a range of humanoid and dog-like robots that can perform various industrial tasks and are deployed in construction sites, factories and warehouses.
SELF ACTIVATED AI
The AI era has just begun. In the next few months, evolved versions of AI will emerge and find mainstream applications. From prompt-based AI, the world of business will face autonomous, automated, agentic AI.
The impact of evolving versions of AI will be deep and disruptive. Governments will struggle with the regulatory aspect while private enterprises will have to be in a constant change mode. Starts-ups will be agile enough to adopt while consumers will be sharp enough to adopt it for their personal use.
Even so, every dimension of business and governance will face fresh waves of change. Intelligent agents in AI will make AI more useful, says Gartner. “Today’s AI models perform tasks such as generating text, but these are “prompted”—the AI isn’t acting by itself. That is about to change with agentic AI, or AI with agency.” According to Gartner, about one third of enterprise software applications will include agentic AI by 2028. This inclusion of agentic AI will enable 15% of day-to-day work decisions to be made autonomously. Today humans work with AI tools to complete various functions. The direction and objectives are set by humans. Agentic AI would change that.
Nvidia is among the top technology companies betting on agentic AI. The next frontier of artificial intelligence is agentic AI, which uses sophisticated reasoning and iterative planning to autonomously solve complex, multi-step problems, it says. Agentic AI systems ingest vast amounts of data from multiple sources to independently analyze challenges, develop strategies and execute tasks like supply chain optimization, cybersecurity vulnerability analysis and helping doctors with time-consuming tasks, according to an assessment by Nvidia.
For example, an agentic AI system may be able to process a payment claim on its own. Another such system will have the ability to generate images on its own for a social media post without being prompted to do so. It would understand the context of the post and generate the image to go along with the content.
The engine for this remains the LLM or large language model which current chatbots use. However agentic AI will not depend on a human instruction but move autonomously based on certain embedded triggers in the software.
According to Gartner, Agentic AI will be incorporated into AI assistants and built into software, SaaS platforms, Internet-of-Things devices and robotics. Many startups are already marketing themselves as AI-agent-building platforms. Hyperscalers are adding agentic AI to their AI assistants.
A fully mature intelligent agent will have agency to learn from its environment, create complex plans and perform tasks autonomously, Gartner says.
For enterprises, there will be yet another wave of organizational and workflow change. Process automation company UiPath predicts that businesses will begin reimagining roles, workflows, and operational models. This will lead to a dynamic redistribution of tasks between human and virtual workers. The shift will require significant investments in upskilling, retraining, and reassigning employees. Business leaders and policy makers will have to keep a sharp eye on the evolving versions of AI
GREENING AI
However, the solution itself is becoming a problem for climate action. Even as AI based solutions are being increasingly used for climate action, they are posing a new problem for the world.
AI is being recognized as an energy guzzler and consequently a contributor to climate crisis. The energy consumption associated with AI technologies, particularly deep learning models, is substantial. Training large-scale AI models like GPT-3 and AlphaGo requires immense computational power, resulting in significant energy use. For instance, training GPT-3 required 1,287 MWh of electricity, equivalent to the annual energy consumption of over 120 US homes, according to research published by Springer. Another study quoted by Springer highlighted that training a single AI model can emit as much carbon as five cars over their lifetimes. Moreover, datacentres housing AI infrastructure are major consumers of electricity.
This could lead to energy shortages caused by increasing use of AI. “The explosive growth of new hyperscale data centers to implement GenAI is creating an insatiable demand for power that will exceed the ability of utility providers to expand their capacity fast enough,” says Bob Johnson, VP Analyst at Gartner. “In turn, this threatens to disrupt energy availability and lead to shortages, which will limit the growth of new data centers for GenAI and other uses from 2026.”
Continuous innovation in AI and its applications is crucial for addressing global challenges like climate change. However, the computational power needed to sustain AI’s growth is doubling roughly every 100 days, leading to a significant rise in energy consumption, UN body International Telecommunication Union (ITU) says. The energy required to run AI tasks is also escalating, with annual growth rates between 26 percent and 36 percent. “We can and must reduce the environmental footprint of digital technologies while leveraging their undeniable potential to tackle the climate crisis,” says ITU Secretary-General Doreen Bogdan-Martin.
Experts believe that AI and GenAI can be made greener by a slew of steps. Tech companies will have to design algorithms in a way that they consumer lesser energy. Experts say that selecting more computationally efficient hardware can also contribute to energy savings. AI is helping reduce energy wastage and improves business process efficiencies. However, its energy use may be neutralizing the overall benefits from digitization.
Technology companies and policymakers have to come together for greening of AI now. Hopefully, the efforts to reduce the carbon footprint of AI will allow the net impact of digitization to be climate positive.
STRONGER COMPUTER POWER
Digital solutions driven by AI are adopted across the demand for powerful computing power has grown too. Computing power is as crucial to a nation’s economic sovereignty as digital and telecom infrastructure. In the era of connected devices and digital platforms, strong connectivity and computing power are as important as highways and factories are for an economy.
According to a Mordor Intelligence report, the High Performance Computing (HPC) market is valued at USD 54.32 billion and is expected to grow to become USD 96.79 billion by the next five years. “Factors such as the increasing investments in the Industrial Internet of Things (IIoT), Artificial Intelligence (AI), and engineering, which demand Electronic Design Automation (EDA), are likely to drive the market,” says the report. “High-performance Computing (HPC) systems with Computer-aided Engineering (CAE) software for high-fidelity modeling simulation are becoming more widely used in various sectors, including discrete manufacturing, robotics in healthcare, and the automotive industry, fueling the market growth.”
From Param 8000 to Param Rudra Super Computers, even India is on a journey to deepen its compute power. Ministry of Electronics and Information Technology stated that India will deploy 10,000 GPUs in the next few months in public private partnership model. This will allow government and private entities to have access to high level computing prowess for their digital applications. Though experts estimate that at a national level, several thousand more GPUs will be needed for India.
Additionally, India is deepening its investment in super computers. The three PARAM Rudra Supercomputers worth around Rs 130 crore, developed indigenously under NSM were launched recently. These supercomputers have been deployed in Pune, Delhi and Kolkata to facilitate scientific and industrial research.
A supercomputer can conduct trillions of calculations simultaneously. Each supercomputer includes many separate computers (known as nodes) that combine their power by working parallelly.
NSM envisages empowering academic and R&D institutions spread over the country by installing a vast supercomputing grid comprising of more than 70 High-Performance Computing (HPC) facilities.
The increasing use of data centres, cloud centres, IoT and use of AI has made the world computer power hungry. Affordable and accessible compute power will be as important as electricity for start-ups and SMEs in growing economies.
* Pranjal Sharma is the author of The Next New: Navigating the Fifth Industrial Revolution.