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Time of India
09-07-2025
- Business
- Time of India
Gartner warns of 40% agentic AI failure by 2027 - Industry leaders push back
In a recent report, Gartner has predicted that more than 40% of Agentic AI projects would be cancelled by the end of 2027, due to escalating costs, unclear business value or inadequate risk controls. Though making significant predictions, the report does not outline the nature of the study, the parameters or the methodology involved in reaching such conclusions.'Most agentic AI projects right now are early stage experiments or proof of concepts that are mostly driven by hype and are often misapplied,' says Anushree Verma, Senior Director Analyst, Gartner. 'This can blind organizations to the real cost and complexity of deploying AI agents at scale, stalling projects from moving into production. They need to cut through the hype to make careful, strategic decisions about where and how they apply this emerging technology.' "If we don't invest in the invisible guardrails that Agentic AI warrants or if we design Agentic AI by overlooking overall system design, costs can escalate and repatriation can start. Left shift is a must as far as security, performance and costs are concerned. These should be the considerations at the architecture stage and not at the monitoring stage. Not everything needs to become agentic and not everything needs to go on cloud," says Anjali Satam, Head of Engineering and Technology Director at IKS Health. Assessing Gartner's initial claims Gartner's initial prediction about agentic AI adoption—prior to June 2025—was highly optimistic, especially regarding customer service and enterprise automation. They also stated that agentic AI would autonomously resolve common customer service issues without human intervention, leading to a reduction in operational costs. "I agree with the current Gartner point of view. Because, the ability to provide flawless access to data for agentic AI to truly function as intended is a major challenge, because most data is not ready and the majority of organizations have not invested in the computing infrastructure needed to deliver on the real promise of agentic AI," says Rajendra Deshpande, former CIO at Intelenet Global Services and a technology consultant. Implementations should be driven by business objectives A few technology experts are of the view that the current agentic AI models don't have the maturity and agency to autonomously achieve complex business goals or follow nuanced instructions over time and may not be able to autonomously achieve complex business goals or follow nuanced instructions over time and therefore could lack value or return on investment (ROI). Moreover, some use cases positioned as agentic AI may not require agentic implementations to be successful. 'Most agentic AI propositions lack significant value or return on investment (ROI), as current models don't have the maturity and agency to autonomously achieve complex business goals or follow nuanced instructions over time. Many use cases positioned as agentic today don't require agentic implementations,' adds Verma. Understanding Gartner's hype cycle Such overarching statements are not unusual. Most technologies follow the hype cycle. The hype cycle is a method to assess how technology evolves along an S-curve. Gartner categorizes current trends into five buckets, each representing a different stage of maturity. This process involves combining technologies and grouping them according to their maturity by a team of experts helps them evaluate the status of each technology on the S-curve. Such observations have usually held true for almost all emerging technologies. Almost 40% of projects fail in the first 1000 days, whether it is blockchain, drones or generative AI. The reasons could be diverse, including factors such as maturity of use cases, readiness of the specific industry, the cost of technology acquisition and implementation, challenges of integration with the existing legacy systems, etc. Gartner explains this phenomenon through its concept of the hype cycle, which is a graphical tool that plots the maturity, adoption, and social application of emergent technologies, providing insights into their potential risks and benefits. It includes five phases: the innovation trigger, peak of inflated expectations, trough of disillusionment, slope of enlightenment, and plateau of productivity. "I am not sure if they use any statistical models, but a team of experts definitely reviews and evaluates the status of each technology on the S-curve. This means there is a level of subjectivity embedded in the assessment for sure. Again, it would be interesting to see how many of their predictions have actually come true. I think the hype cycle is more of a framework to assess the level of maturity of technologies, rather than a precise prediction method. It would be even more interesting to know if Gartner has any audited data about the accuracy of their predictions," observes Deshpande. A major driver of the current hype around agentic AI is the widespread rebranding of existing products by many suppliers, often without delivering the true, full capabilities that define agentic AI. "In 2000, dot-coms rose fast and fell faster. In 2010, many IT services projects grew big but couldn't scale well. In 2020, SaaS exploded, but too much of it lacked clear value. Every hype wave leaves behind good ideas that failed because of weak execution or no real go-to-market!" points out Kingshuk Hazra, Founder, LeadStrategus.
Time of India
13-05-2025
- Business
- Time of India
Why is India lagging behind in deep tech?
Recently, India's Commerce Minister Piyush Goyal critiqued Indian startups for prioritizing convenience-driven ventures like food delivery over deep-tech innovation. He questioned whether the nation's entrepreneurial spirit was being channeled into "fancy ice cream and cookies" instead of groundbreaking technologies such as AI, robotics, and electric mobility. Goyal emphasized the need for India to emulate China's advancements in deep-tech sectors to avoid becoming a "technological colony." His remarks sparked debate within the startup community, with some defending the economic contributions of consumer-focused businesses and others acknowledging the necessity for increased investment and support in deep-tech initiatives. The National Technology Day is the most suitable occasion to raise important questions such as why is India lagging behind in terms of deep tech? Investment on research and development significantly smaller than many other countries India's expenditure on research and development (R&D) remains modest compared to global standards. According to reports, India's Gross Expenditure on R&D (GERD) stood at approximately 0.7% of its GDP. This is significantly lower than countries like China, the USA, and Israel. "One of the reasons we are lagging in research and development is the lack of a well-established ecosystem that fosters collaboration between colleges and industry. This connection is crucial for conducting truly industry-focused research that can create a significant impact," says Rajendra Deshpande, former CIO at Intelenet Global Services . "We can't blame people who are investing in grocery delivery apps. They are developing what we as a nation are demanding. Although as an individual I don't like grocery delivery apps. There are too many negatives of them. But we can discuss them separately. Since we are more focused on fighting to save our political alignments we are focusing less on growth requirements and systems. Once we start focusing on how we can grow our businesses we will start asking our governments for investments in the underlying infrastructure," says another technology expert. India's middle class does not have a risk appetite? "Let's not forget that domestic talent often prefers high-paying tech services jobs over uncertain R&D careers. There's a cultural tendency to avoid failure, which stifles bold experimentation. Middle-class families prioritize job security over innovation or entrepreneurship. This drives bright students toward stable careers (like IT services, government jobs, or medicine) rather than uncertain research roles or deep-tech startups. Pursuing a PhD or working in R&D is often seen as low-paying and risky compared to roles in multinational corporations. But indeed it requires PhD for roles involving fundamental research, algorithm development, or work in deep tech. How many parents do you know who push their children for PhD instead of UPSC? I know a lot of people who have spent years becoming a sarkari babu but I know very few who genuinely go for PhD. Infact, in our country it is seen as the last resort," says Siddharth Saxena, CTO, Vision Bank . New education system need of the hour "To bring about cultural change, Education 5.0 is the answer. If you read about it, it becomes evident that there has been a major shift from the evolution we saw from Education 1.0 to 4.0. Education 5.0 is student-centric and focuses on personalized learning, skill development, and technological integration," says Deshpande.
