There’s a big difference between how something should work in theory vs. how it works in the real world; This is when tools meet human behaviour.
If you were born before 90s, you may remember the long queues in banks to update the passbooks. One had to plead to the person behind the desk to give some time to this task and copy down the entries from ledger to the passbook. More often than not, one was asked to leave the passbook behind and collect it after a few days. There were delays in cheque clearances, with money sometimes taking weeks to get credited to the account. The need for computerization was stark but some of you may remember the furor when computerization in the banking industry was initiated. This was opposed tooth and nail by the trade unions and various political parties over possible job loss. Computerization, though slow to start, developed momentum over the years. There has been stark change. There were around 61,000 bank branches employing ~1 million personnel in 1993. The number of branches now is 122,000 with employees being at around 1.5 million. During the same period, the saving deposits have gone up by close to 100 times. Clearly, the banking industry during the last three decades has undergone a remarkable transformation in volume, agility and technology adoption.
In 80s, India faced a horrific industrial disaster when there was a gas leakage in Union Carbide’s pesticide plant in Bhopal leading to death and injuries to thousands of people. The Indian Government filed a lawsuit against the company in the district court of Bhopal. I remember reading at that time in press that the some of the American lawyers representing Union Carbide were carrying laptop to the court room and it was strenuously objected to by the Indian lawyers on the other side as being an unknown technology and offering undue advantage to the other side. More than three decades have passed since then and while technology adoption in Indian courts has gradually increased, it has a long way to go in terms of improving efficiency and ease of access to the judiciary and litigants. Furthermore, the implementation remains patchy across various courts. The common reasons offered for slow adoption of technology have been legal traditions, the need to balance innovation with security and due process, investment required etc. Last year India had the dubious distinction of its pending court cases hitting 50 million mark. This was less than 30 million around fifteen years back.
So, we have two different professions in Indian society which faced productivity challenges but reacted very differently to technology adoption. The same holds true for companies within the same industry as well. One just needs to see the user experience or ease in online purchase of insurance policy from any of the private general insurance companies versus that from any public sector one. It is not that the technology backend is not available to the public sector companies or that the private sector firm’s risk exposure is suffering adversely by making large online sales; On the other contrary, the private sector general insurers are not only able to increase their market share but also reduce policy acquisition cost and have better financial metrics. It would have been logical to expect that seeing the results, the public sector companies in the industry would follow suit. It has not been the case, and this is where human behaviour comes in.
The human factor has also played a large role in driving success of applications like ERP that are ubiquitous across large organisations. While there are global firms like Oracle, SAP, Microsoft, SAGE etc. offering their standard suite of products, the implementation success has been varied. There are examples like Nike which bungled their ERP implementation resulting in supply chain disruptions expected to have cost them $100 mn in missed sales. There have been several examples of successful complex multi-geography ERP rollouts by companies like Nestle, Amazon etc. as well. The difference between success and failure has been whether the implementation was thought through, if there were significant customizations making system complex and difficult to maintain, whether existing business processes were reengineered or it was just automation of inefficient processes, or if the system was tested adequately before going live etc. None of these factors would be challenged if flagged as essential to successful implementation, but still several companies have suffered as they couldn’t manage the behavioral dynamics.
As we look at the chatter around AI and it being either lauded as a boon for mankind or attacked as bane for employment, one needs to consider how humans adapt to it. I remember reading that a multi-year study done in USA could identify only one role, that of a lift operator, which had been completely obsoleted by technology. Clearly, that is not the case in India where one still finds lift operators sitting on stool in various office buildings! So, while Goldman Sachs estimates that globally 300 million jobs would be lost or affected by AI, history tells us otherwise.
The pace of technology advancement and integration of AI in various tasks and roles would be varied across countries and industries. While most would agree that AI will reshape the job market and some jobs shall be automated or would undergo significant changes, the net impact on employment will depend on how society adapts to and utilizes AI. Efforts by Governments and Industries to prepare the workforce with the skills needed in an AI-driven world will be critical to improve productivity, better decision-making and have new opportunities in years to come. Early this year, Sam Altman said that it would be hopeless for Indian companies to try building ChatGPT like tool. There was a lot of indignation, and several leading industrialists accepted the challenge. I would rather that we repurpose that energy and resources to adapting our ecosystem and workforce to AI. This technological leap would make winners out of not only the technology providers but also the economies that make the most out of it.
There’s a big difference between how something should work in theory vs. how it works in the real world; This is when tools meet human behaviour.
Himanshu Chaturvedi,
Chief Strategy and Growth Officer,
Tata Projects Limited
Simplify. Create.
