MMA Annual Convention 2025

In this session on Technology Resilience, experts demystified AI’s hype, emphasizing resilience, skill-building, and the enduring importance of human purpose.

Who will emerge as the winner in this era?

Anurag Sharma
Associate Partner, McKinsey & Company

Will AI take over the world and all of our jobs? While we may not have a definitive answer, this question certainly grabs attention. We’ve pondered this ourselves and realised that AI is part of a repeating pattern of technological transformations we’ve seen over the years. Looking back, we’ve witnessed multiple revolutions and transformations, each with its own set of winners, who capitalised on clear advantages.

For example, during the late 18th and early 19th centuries, the Industrial Revolution saw the UK as the undisputed leader, followed closely by Germany and the United States. Then came the era of electricity and mass production—assembly lines, automobiles, and telecommunication, where the US took the lead with companies like Ford and General Electric and with Germany and Japan also becoming industrial powerhouses.

Moving into the 20th century, the digital era saw the rise of Silicon Valley, where the US stood out with companies like Microsoft, Apple, and Intel, while Japan and South Korea excelled in hardware manufacturing. Following this was the internet and connectivity era, with giants like Amazon, Facebook, and Google emerging in the US, and China stepping up with players like Alibaba, Tencent, and Baidu.

Next came the cloud and big data era, led by the US and China. Now, we’re in what I like to call the AI and automation era, characterised by rapid advancements in automation technologies. The pressing question now is: who will emerge as the winner in this era? What does it take to succeed, not just at the country level, but also at the institutional and individual levels?

Across all these eras, we’ve identified a few common themes: adaptability, investment in education and R&D, infrastructure development, inclusive progress, and public-private collaboration. Given the recent hype around AI, we need to distinguish between what’s true and what’s not. Rather than focussing on one specific example, let’s address the broader question: How do we capture the opportunities presented by the AI and automation era? How can we ensure we don’t become obsolete? How can we upskill ourselves and move forward?

We can enhance human abilities through technological augmentation.

Prof Pankaj Setia
Founding Chairperson, Centre for Digital Transformation, IIM, Ahmedabad

Every technology has driven some people forward. Who advances and who doesn’t? I’ve pondered this question and concluded that technological revolutions are actually revolutions in human purpose. Understanding this purpose is complex for individuals, organisations, and societies.

Three Key Aspects

To move forward, we must clearly identify our purpose. Consider three key aspects: technology itself, the logic of human organisation, and the individual. Digital technology is often discussed as the way forward, but we must focus on its purpose. Technologies are advancing, as seen with innovations like ChatGPT and DeepSeek. India is also developing advanced technologies. These technologies can evoke human experiences, like AI-generated poetry. Automation is transforming processes, and intelligent technologies are becoming prevalent.

Rold of Technology

In India, complex technologies like Aadhar and UPI have made great impact, but we must also consider advancements like humanoid robots. Technology transformations are not the phenomena to observe from a distance; they are integral to our progress. As a society, as individuals, as professionals, and as managers, we don’t have the luxury to wait and watch. Advanced technology is being built right here in India.

The critical question is: What happens in the next 10 to 15 years? The real excitement lies in projecting where technology will be. Reflect on the past 20 to 30 years—your mobile phone now has more computing power than a supercomputer from the 60s and 70s. Imagine what will happen 20 years from now, with computing power doubling every two years—it could be a million times more powerful than today. Consider the immense computational capabilities we’ll possess, far exceeding our current understanding of intelligence. While this brings great potential for good, we must use these advancements wisely.

Tech-Enabled Organisation

The second element to consider is organisation. Organisation distinguishes living beings from non-living beings. It is fundamental to all life forms—birds build nests, and we gather to discuss digital transformation and technology resilience. Right in our homes, we organise our lives. We organise our desks, our work. Everything we do involves organization. Technology plays a significant role in helping us organise, which is essential for our well-being. Advanced computational capabilities can help us organise better.

For instance, Google Flu Trends predicts flu outbreaks by analysing search trends for symptoms, often before public health agencies detect them. People searching for symptoms provide real-time data, enabling early prediction of flu spread. In education, AI detects student deficiencies by mining data across different courses. This is just one example of how technology can solve public health and educational problems, demonstrating its potential to enhance our organisation.

If a student struggles in physics and math, it’s challenging for teachers to identify the underlying reason. AI can detect specific issues, like a student’s difficulty with quadratic equations, which may not be apparent to individual teachers. AI analyses student performance across courses, revealing hidden deficiencies and helping us educate more effectively. At Columbia University, robots assist in setting up experiments, demonstrating AI’s role in scientific discovery and organisation.

We’re also looking at future technologies like autonomous cars. Consider the incident in India where miners were trapped—why send humans into dangerous tasks when AI and robotics can take over? While job displacement is a concern, certain jobs are too hazardous for humans. We must rethink our approach to organisation in society. Technology helps us organise better, whether it’s through AI predicting flu outbreaks or improving education. We face real challenges, but advanced computational capabilities can address many of them.

Prof. Erik Brynjolfsson, a professor at MIT, analyzed a large amount of data and found a decoupling between jobs and productivity. The idea is that we can now create a variety of things by employing fewer people, so organisations don’t need as many employees. This is a significant technological factor. For instance, companies like Ford, which once had the largest market share, employed many more people compared to today’s dominant companies. In Silicon Valley, small teams of about 10 people are creating million-dollar companies with high valuations, thanks to their productivity with fewer workers. This raises a concern: How do we organise ourselves if this is a challenge for our organizations? When we think about organisation, we must also consider issues like cybercrime.

Garry Kasparov, after losing to Deep Blue, started a freestyle chess tournament where both humans and robots could participate. He found that the best teams were a combination of humans and robots. This highlights the importance of augmenting human capabilities with technology. We can achieve more with technology, and technology performs better with human input. This synergy is the current paradigm, though its duration remains uncertain. The key idea is that we can enhance human abilities through technological augmentation.

Technology and Individual

The third aspect to consider is the individual. The fear of AI is widely discussed. Many believe that there will be hardly any tasks that robots won’t perform better than humans. This raises the question: What will humans do?

There are concerns about the negative effects of technology. For example, Verizon highlights issues like mental health problems, poor sleep, declining grades, loneliness, and family issues. The stress from AI replacing humans is significant, impacting individual health and well-being. We must consider these downsides while also acknowledging the positives.

India’s fintech revolution, with UPI adoption by 300 million people, is a prime example of positive technology impact. While there are challenges, technology has the potential to drive significant progress. The UPI system has provided access to credit and respect to many who previously lacked it. This financial inclusion has positively impacted 300 million people, more than the population of most countries. Some bankers initially missed this opportunity, but the transformation it has brought is undeniable.

Successful digital transformation is driven by a purpose that intertwines technology, individuals, and organisations. This latent human force propels societies forward by understanding these interactions better. The key is not to view technology, individuals, or organisations in isolation, but to see how they collectively drive progress. How do we unravel this? I propose a scientific approach, focusing on three questions: what, how, and why. What do we need to do for digital transformation? How should organisations organize themselves differently? To address this, I outline the Davao Gomu model, which explains how organisations can harness this purpose to achieve better outcomes. Finally, the eternal question societies must ponder is: Why do we digitally transform? While some restrict children’s exposure to technology to avoid negative impacts, we need to consider why digital transformation is beneficial. There is an answer to when it is good and when it is not.  

The IT services industry faces potential impacts from AI.

Somnath Chatterjee
Founder & CEO, Prismforce

We are entering an era of ubiquitous AI. Just as Google democratised access to information, AI has the potential to make intelligence far more accessible. The impact of AI is unprecedented, with advancements occurring at a rate of 10 times year after year. The cost of AI tokens has decreased significantly, and the efficacy of AI models has improved drastically.

This compounding effect means AI will be everywhere, narrowing the gap between science fiction and reality. AI interactions will become more humane, acting as extensions of ourselves. This can break down barriers like information access and language, aiding innovation and productivity. As entrepreneurs, we must be optimists and explore the possibilities AI offers. For a country like ours, AI presents opportunities for leapfrogging. However, this also brings risks of disruption. Businesses relying on complex AI systems must prioritise resilience to protect revenues, reputation, and market share.

In my own experience, resilience was crucial when building my startup. We won a mandate from a top global IT services player, which emphasised the importance of business continuity planning and disaster recovery. This experience taught us that resilience should be integral to our architecture and strategy. The IT services industry, which has played a significant role in India’s emergence, faces potential impacts from AI. The cost and labour arbitrage that fuelled outsourcing is now challenged by AI-driven efficiency. Chennai, as a major exporter of software services, must adapt to the AI-led services model. The sector has shown resilience through past disruptions, such as the dotcom bust and the global financial crisis.

India’s tech services industry has the potential to create new jobs by leveraging its young, AI-trained population. The value is shifting from hardware to foundational models and applications, where India has an inherent advantage. Though disruptions are inevitable, I am very sure that entrepreneurs and leaders in India will seize these opportunities and create new jobs, driving the country’s progress.

Manikandan Thangarathnam

Senior Director, Mobility and Platforms, Uber

The tech landscape has undergone massive shifts. I remember building large-scale distributed systems at Amazon, a complex undertaking requiring top-tier engineers. Then cloud computing emerged, offering APIs that commoditised these capabilities. Tasks that once demanded huge teams—like storing petabytes of data—became easily achievable with services like Elastic, or cloud compute.

The Rise of Data and AI

This ease of development led to an explosion of data, driving the focus towards data analytics and intelligence. Now, AI is the buzz, but I believe it too will become a commodity. Building AI-powered solutions is already faster and easier, requiring fewer specialised engineers because algorithms are readily available.

Key Priorities for Organisations

So, what should organisations prioritise?

• Speed: With readily available tools, how quickly can you build? The answer should be: very fast.
• Efficiency: You don’t need massive engineering teams anymore. Focus on building end-to-end systems with smaller, highly skilled teams.
• Reliability & Scalability: How well does your system perform in production? Reliability and scalability are crucial.
• Cost: What are you spending on these commoditized APIs? Cost optimization is key.

Customer expectations evolve rapidly. Consider Uber: Users once patiently waited minutes for a ride, now they expect instant service. Reliability is extremely important. At Uber, we handle millions of trips daily across thousands of cities. Imagine a small config change breaking functionality in a single city. Identifying and addressing such anomalies quickly is vital.

Problem-First Approach

Focus on solving real problems, not just chasing the latest technology. Don’t ask, “How can I use AI?” Instead, ask, “What problem am I trying to solve, and what technology – including AI – is best suited for it?” Choose problem statements that will remain relevant. For example, the need for affordable, reliable, and safe transportation will always exist. This led us to explore high-capacity vehicles, which presented complex challenges in routing, stop placement, and driver optimisation. We then leveraged AI to optimise routing and maximise bus utilization. It took years of experimentation to build a profitable business.

Academia and Skill Sets

What about academia? While curricula evolve, the focus should remain on foundational knowledge. Vertical expertise comes from practical application. The real issue isn’t a lack of jobs; it’s a lack of qualified candidates. Companies like Uber are actively hiring, but we need individuals who can write the best code, not just any code. The same applies to AI. It’s not enough to say you ‘know’ AI; you must be able to build, tune, and measure the accuracy of models. Don’t wait for curricula to change. Take responsibility for building your own expertise. The resources are available; it’s up to you to leverage them.