Ten Years of CSR

Read Time:4 Minute

In the wake of the implementation of the CSR Amendment Rules 2021 on January 22, 2021, which mandated compulsory CSR spending, a notable surge in CSR initiatives has taken place.

It is indeed heartening to observe that a majority of corporations are actively engaging in the execution of CSR projects, demonstrating a preference for tangible actions over mere contributions to funds outlined in Schedule VII. With the fundamental aim of fostering awareness among all stakeholders in the CSR landscape about the core objectives and intricacies of the government-enacted CSR Legislation, the MMA-KAS in collaboration with CSR Spark conducted a conclave recently.

The CSR Conclave delved into the multiple opportunities that lie ahead for social entrepreneurs to harness CSR as a catalyst for propelling their enterprises, thus facilitating compliance with legal mandates while motivating corporations to undertake initiatives congruent with their Environmental, Social, and Governance (ESG) aspirations. Furthermore, the event offered valuable insights into optimal accounting practices tailored for nonprofit organizations, punctuated by pertinent case studies spotlighting successful CSR implementations.

The welcome address was delivered by Mr R S Krishnaswamy, the Founder of CSR Spark. Mr Nikhil Pant, an esteemed CSR Coach, provided a comprehensive overview of his authored CSR Manual, which was formally unveiled during the conclave by distinguished dignitaries. In his address, Mr URC Devarajan, the Managing Director of URC Constructions Pvt Ltd, proposed the notion of a rating system for NGOs, a mechanism that could streamline their engagement with corporations seeking to extend support.

Mr. K Pandiarajan, Executive Director of CIEL and a former Tamil Nadu State Minister, articulated during the occasion that CSR is intrinsically linked to the ethos and operational conduct of an organization. “What is important is: What I do and how I do? This is the fundamental question that every organisation must ask themselves, as their first step towards CSR,” he said. He emphasized the significance of channeling the core competencies of an organization, consciously built in its DNA, towards fostering societal welfare and serving the larger good of the community.

Justice N. Seshasayee, Honourable Judge of the Madras High Court, stressed the need for the corporates and NGOs to go beyond the academic requirements of CSR legislations. “Corporate Social Responsibility is a journey from one ‘S’ to another—from Self to Society,” he said and added that this transformation necessitates a blend of compassion and empowerment. He further said, “As we chart our path, it’s crucial to be aware of where we stand and diligently work our way forward. The crux of this journey lies in individual responsibility. Thus, before we extend our focus to society at large, it’s important to begin by addressing the individual. The responsibility to nurture one’s family and organizational team members is a significant one because only when we keep our family and team happy, we can go out peacefully to serve the larger needs of the society.”

He also cautioned that the scope of CSR is not to be confined to ticking off the boxes of 80G or Section 135. “Often, CSR is directed primarily towards established entities, leaving out numerous unorganized individuals in need of support. Consider, for instance, those who dropped out of engineering colleges due to financial constraints or individuals who cannot afford medical treatment. To bridge this gap, I advocate for a collaborative network among all NGOs. Think of a platform where anyone in need could seek assistance. Such a mechanism must extend its benefits to all individuals, many of whom often remain hidden from our sight,” he said.

He pointed out that India’s strength lies in its numbers. “Even if 20 crore people each contribute a modest amount, collectively, it can yield a significant sum. It’s true that we might not be able to solve every problem for everyone, all the time. However, taking on one project per month is within our reach. We can begin with a group of hundred participants, each contributing a thousand rupees monthly. It’s a hard fact that people are willing to spend a similar amount on liquor but hesitate to contribute to charitable causes. When someone seeks help, a discreet inquiry can help verify their genuineness without demeaning or belittling them.”

Justice Seshasayee said that the question we must ask ourselves is: What’s the best I can do for my society? “Rather than merely quoting the wisdom of leaders like Gandhi or Nehru, it’s a call to action that is more important. In this crucial juncture in our nation’s history and civilisation, it’s our duty to bring about a positive change. Nation-building is not just an outsourcing of a construction project; it needs to be built in our hearts. We must carry the intent to shoulder the responsibility for our society, he said passionately. As I step out of my chambers each day, that thought that echoes in my mind is: What’s the best I can do today? Let’s infuse this thought into the fabric of our nation as we celebrate its 75th year of independence,” he said.  

The conclave hosted an assortment of sessions that encapsulated the spectrum of CSR dynamics. Mr R S Krishnaswamy delved deep into the intricacies of the CSR Act, encompassing recent amendments and penalties for non-compliance. Notably, while the top 20 companies contribute 27% of the total CSR expenditure, the other companies can focus on the balance 73%, he suggested. Mr Nikhil Pant’s session revolved around the theme “10 Years of CSR Evolution & Way Forward: Strategy & Policy Frameworks.”

Mr K.Ravi, the CFO of the Roots Group of Companies, deep-dived into the accounting practices tailored for nonprofit entities. These informative sessions were followed by a thought-provoking panel discussion on CSR Best Practices, featuring Mr. Rajaram from Srinivasan Services Trust (SST), Dr. Vasudevan representing MMA, and Mr. Prem Kumar from BumbleB Trust, moderated by Dr. K S Ravichandran, Managing Partner, KSR & Co Company Secretaries LLP.

Understanding the Generative AI Landscape

Read Time:14 Minute

The making of the ‘thought engine’ and how far have we come, was a session theme at the recently concluded convention on AI. A team of eminent panelists discussed the challenges and opportunities brought in by AI.

Mr Sachin Premnath

Director-Business Consulting, EY

ChatGPT has generated a lot of interest both in the investment and technology communities. Business users are now asking us if we can apply any AI component to their work. This is the opposite of a year ago when we used to pursue customers to try Gen AI in their work. ChatGPT is the fastest to reach 1 million customers, and a lot of venture capitalist funding goes into it.

There are social, economic, and legal constraints in using ChatGPT, and laws have been passed in the US and EU regions regarding its use. Stanford has conducted a study on how various models are performing and how reliable they are. There are places where people have applied AI in their day-to-day work, such as preparing a speech, generating templates, wordsmithing, and writing emails to clients, which are perfect ways to use it. You could also use it to improve revenue opportunities and identify new revenue streams that did not exist in the past. However, one has to be judicious in using the various components of Gen AI.

AI: A Holistic Field

Over the last decade, people have been using the words AI and ML interchangeably. AI is a holistic field of study that encompasses machine learning algorithms. The more layers you train AI, the more it becomes deep learning. It has evolved from natural language processing and has been trained specifically from a tech standpoint. Today, unless you want to experience it, you don’t need to go to Paris and stand near the Eiffel Tower for a picture. You can use Gen AI to create a more realistic image of you by the Eiffel Tower. From a source code generation standpoint, many of my clients are leveraging this, especially for re-platforming from one language to another. It’s not limited to text anymore. You can create content, images, music, videos, and pretty much anything; it is possible now.

Any enterprise can be broken down into three layers: analysts, function heads, and CXOs. All three of them can leverage Gen AI, and there are various use cases for it. You can use it for searching knowledge databases. When you are on a call with a customer and need to refer to an SOP document before responding, Gen AI can search those documents and provide a relevant response. The function head can use the search functionality to gain insights from the document. Thus, it can be applied to every role.

Mr Vijay Karunakaran

Founder & CEO, Ingage Technologies Pvt Ltd

Even a year before ChatGPT hit the market, we had been using Gen AI for a lot of content generation. I also advise the Tamil Government for AI projects. We help the forest department monitor and track the movement of elephants so they don’t get killed on the railway track.

I am going to discuss the role of semiconductors and Metaverse. Semiconductors drive the Gen AI explosion. On average, close to 10 million people log in and send queries to ChatGPT. They get 8 billion searches every single day. That’s going to cost them heavily, and it is not going to be free for too long. They already charge for ChatGPT Plus. Even if you pay $20 a month, you’re restricted to a certain number of queries per day or per week. Why is that?

Mobile Computing & Apps

The real cost comes from computing. There are many semiconductors. We moved from the PC world in the 1990s to a smartphone mobile world in 2000. It is the CPU, the central processing unit, that is delivered by the Intels and AMDs of the world that drove the PC computing. Then came the mobile smartphone computing, also a CPU, but we had a new entrant called ARM processor driven by a bunch of semiconductor companies. Now, we are entering the new role of AI computing, which can also be called immersive computing or spatial computing.

Across the PC computing market, the economic share of the technology stack for semiconductor companies was close to 20-30%. That dropped to 10% in the smartphone era because the smartphone market exploded due to applications. It is the software that took a major market share of the entire economic value of mobile computing. Now, for the next five decades, as we are entering generative AI, it is a great opportunity for semiconductors to recapture 40 to 50% share of the entire technology stack. The semiconductor is the most important component of generative AI.

There are four layers in the AI stack:

  • Layer 0 is the hardware and the cloud which will drive the AI explosion, and that is where the semiconductor comes into play.
  • Layer 1 is Model Foundation which comes from the Open AI companies.
  • Layer 2 is Integration, Orchestration, and Deployment Tooling, which includes all the frameworks and is provided by companies like Google and Microsoft.
  • Layer 3 is AI applications like ChatGPT, image creation, and so on.

From CPUs to GPUs

There are various types of semiconductors. We have terms like FPGA, GPU, and CPU. GPU means a graphical processing unit, while CPU stands for central processing unit. The GPU was born from the requirements of the gaming industry. It is highly parallel processing. The company that makes that is Nvidia. There are only four companies that are beyond $1 trillion. The first is Apple at $2.6 trillion. India’s GDP is only $3 trillion. Then comes Microsoft, Google, and Saudi Aramco. This is followed by Amazon and Nvidia. Its market cap doubled in the last one year because it is the GPU of Nvidia that drives the AI industry. A CPU in a computer costs only $80 or $90, but an Nvidia chip costs $10,000.

On the other hand, while it costs one billion dollars to build a data center built using CPUs, it costs just 100 million dollars (just one tenth of a CPU) for a GPU-based parallel processing data center. Hence, there’s a huge demand for GPUs of Nvidia. Intel is trying to catch up. In the last five decades, oil and gas was the currency for international diplomacy in geopolitics. For the next five decades, it is going to be semiconductor chips. Why does America defend and spend billions to save Taiwan? Is it because they like Taiwanese people or their noodles? No. It is because they have the world’s best top-notch cutting-edge fabrication company called TSMC, which controls 90% of all the advanced chips manufacturing.

Facebook changed its name to Meta because they think that the Metaverse is the next computing and it’s going to be the future. Over the years from the 1940s, we have come a long way in computing. We had workstations and floppy cards. Then we moved to PCs and laptops, and now we are in the smartphone era. The touch and feel interaction with the device is going to be immersive as we go forward. We’re going to use gestures and eye movements to do the computing. That is where we’re heading. Then we have the AI edge driven by augmented reality and Blockchain.

Web 1.0 to Web 3.0

We have also moved from Web 1.0 to Web 2.0 and Web 3.0. In Web 1.0, when we enter the URL, we get the data from the server—which is Read Only. That was the start of the internet revolution, and it was there for 10 to 15 years. Then came web 2.0. Currently, most of our applications are on web 2.0. It can read; it can write. When you order food on Swiggy, you give a lot of information about yourself, your location, and your credit card; it means that you are writing data from the device to the server. That’s what helped the entire mobility ecosystem.

But there are two drawbacks to web 2.0. Number one, it is centralized. That means anything you send hits the server and goes back. At the server, there are people like Facebook, who give the products WhatsApp and Instagram for free. They give it free because for them, you are the product. They store the data to analyze your behavior and offer products that you may not need. The second drawback is it is two-dimensional.

Web 3.0 is meant to solve that by doing decentralization using blockchain technology. That’s number one. The second is delivering immersive 3D content. Engagement delivered by augmented reality and virtual reality put together is called the Metaverse. That’s where the world is moving, whether we like it or not. Right now, the devices are on our head. At some point, it can become smaller and smaller. It’s more an enterprise game show now. But soon when Apple launches its app—Vision Pro, the market price may come down. 80% of the content of the Metaverse could be generated using generative AI.

Prof U Dinesh Kumar

Dean, Data Centre & Analytics Lab, IIM Bangalore

What are the problems with Large Language Models (LLMs)? How much can we trust large language models? LLMs use Internet data. The question is, can you trust the data on the internet, and is there bias in the data? Let me give you an example.

A Sensation, for the Wrong Reason

In an internet poll conducted in the year 2000, Jamie Pollock was voted the most influential man of the past 2000 years. Not many can recognize him. In that poll, Jesus Christ came second, followed by Karl Marx. You may wonder how he got the largest number of votes.

In 1999-2000, he was playing for ManCity, which had just won the Champions League and Premier League. It was a division one team. It was the last match of that season, and they were playing against another team called Queens Park Rangers (QPR). Both these teams were in a critical situation because if they lost the match, they would be relegated. In that match, Jamie Pollock scored a self-goal, and Man City was relegated to division two while QPR stayed in division one. This internet poll was done immediately after that match. All the fans of QPR voted for Jamie Pollock as the most influential man of the past 2000 years. That’s how he got a large number of votes.

The point I’m trying to make is that you must know where you are getting your data from for your large language models. What is the source of the data? I asked this question, “Who are the most influential men of the past 3000 years?” ChatGPT said, “Confucius, Julius Caesar, Leonardo da Vinci, Karl Marx…” and Jesus Christ was missing from the list because I said the last 3000 years. When I asked, “Did Jesus agree with Buddha’s idea?” it gave me some answer. It said, “Yes, there are similarities, but they never met at all.”

Look out for the Source

On YouTube, there is a BBC documentary titled, “Is Jesus possibly a Buddhist monk?” If you include YouTube data, the answer might have been different. The problem when we use large language models is that we have to be careful where the data is coming from. The second is, there could be bias in the data. For example, if you take any other form of medicine other than allopathy, Wikipedia will say they are all pseudo-scientific, whether it is homeopathy, naturopathy, or anything else. Wikipedia also says that 80% of the population of India and Nepal actually use something other than allopathy. Basically, it says that one-sixth of the population has used pseudo-scientific methods. Can you trust Wikipedia data which is heavily used in large language models (LLMs)? LLMs have a large number of limitations. They cannot predict.

But having said that, LLMs can contribute in multiple ways—in text generation, code generation, image generation, speech, video, 3D, and other forms of data. We can create data that would otherwise be difficult. When AI came into discussion about 100 years back, people wanted to create something that would imitate humans, but all that has changed. What we see today is that humans actually imitate Gen AI systems. In the last 10 or 15 days, the entire media world was focusing on Oceangate, the submarine that imploded in the Atlantic. The problem with these innovations is that we have very limited data about the materials that were used and to what extent they can survive the deep-sea environment.

People try to see how Gen AI can help in treating neonatal sepsis, in which newborn babies can die because of sepsis. Sepsis is a bacterial infection, and there is a very high chance of death. In India, the mortality rate is 35. We are looking at non-invasive procedures to solve this problem. Can we look at the baby’s parameters and mother’s parameters and predict the chance that the baby may get into sepsis? Asha workers in India carry a lot of data. Can we pull that data together and come up with a model that can help reduce neonatal sepsis deaths?

Thanks to Gen AI, we can create solutions where data-driven decision becomes very easy and accessible to everybody. For example, if somebody asked me a question, “Should I invest in Infosys stock or TCS stock?” At the back end, I can run AI models and generate data, but GenAI can’t predict things. So I have to integrate other machine learning algorithms to do enhancers kind of things.

There’ll be a lot of jobs that will be created through AI technology. ChatGPT is an information synthesizer. Unless you integrate many other technologies, it is not going to be a thought engine. We are far away from that, but there are efforts to make it a thought engine.

India has been trying to get into the chip manufacturing space. When is it expected to see the light of the day? How much investment is required for India to become a leading chip manufacturer?

Vijay: In semiconductor manufacturing, there are three distinct phases. The first phase is the design, which is done using PCs and software. Once the design is completed, it is sent for manufacturing where the fab comes into play. After the first few prototypes become available, they undergo the post-silicon validation process. India already has a large presence in the first phase, i.e., the design phase. All the major players in the semiconductor industry, such as Intel, Qualcomm, and others, have a presence in Bangalore and other parts of India. Semiconductor manufacturing requires close to $10 to $15 billion in investment. The money is not that difficult for a country the size of India. What is crucial is the technology transfer. India has reopened the PLI window, and Vedanta and Foxconn came up with a deal for some manufacturing, but it got stalled because they couldn’t find a technology partner.

The technology we are considering is very outdated, probably 28 nanometer thickness, whereas the current chips come in 4 nanometers size. India must get close to America and try to influence TSMC to invest in India and bring the technology transfer. It is no longer just a money problem.

How do we see the manufacturing industry five years down the line, using AI?

Sachin: AI has already been implemented in manufacturing, at least for the last five or six years. I have worked extensively with AI in manufacturing, especially for pharma clients, to manufacture high-quality soft gels. Specific computer vision and AI use cases have been implemented. We can detect, from a safety standpoint, if people are wearing helmets and other safety gear. AI will make further inroads and grow much more to improve efficiencies and reduce costs.

Prof Dinesh Kumar: There are a large number of applications of AI in manufacturing. We have worked on projects in manufacturing systems to predict whether there will be a fire in the next 10 minutes using IoT sensors. We have also worked with many automobile companies to predict failures, warranty claims, and detect any fraudulent claims. AI is being used in almost every sector.

Is it possible to translate more than one language at the same time?

Sachin: Yes, the Government of India has a specific initiative called Bashini (Basha Interface) using which a lot of chatbots are being developed, and the language accuracy is extremely good.

Prof Dinesh Kumar: In the UN Council, members from more than 150 countries speak different languages. Whenever a speaker speaks in any language, it automatically gets translated.

Dinesh: Another good application is a 3D avatar of a person delivering a speech.

With respect to Web 3.0, the data will be more personalized. What happens to the data science professions, which are more dependent on data?

Vijay: Obviously, upskilling is required. There won’t be any job loss. There will be realignment or reassignment of various job roles, and people will upskill themselves.

Prof Dinesh Kumar: Data Science will not go away because ChatGPT cannot predict. It’s a language model. Data scientists predict. People use LLM because it’s a fun application today, but soon they will realize the limitations and need to bring in AI/ML and other models to integrate them with large language models to solve problems.

Generative AI: The Future is Here

Read Time:18 Minute

With its ability to create new and unique content ranging from text, imagery, videos, music content and more, generative AI is revolutionizing businesses across industries ranging from manufacturing, healthcare, IT, arts and design, advertising, and marketing. Recently, some of the top experts in the field had come together to facilitate our understanding of business applications, limitations, regulatory considerations and use cases of AI tools.

“Unleashing a wave of innovation…”

Mr Gopi Kallayil, Google, USA

Every one of you has used AI today in a direct or indirect way, without realizing it. If you use Gmail, you’ve already used AI, because AI is being used to keep your Gmail saved from spam. If you shopped on a site like Amazon, you probably got some recommendations from the service, powered by AI. AI has already been embedded across many of the products and services you use. Like electricity, you may not realize it. 

However, the field of generative AI has ignited the imagination of the world, primarily because there are some AI-based services that are now available to consumers. Bard or ChatGPT has allowed us to ask questions and it seems to converse with us like a human being does, with fully formed sentences and excellent answers. You can write code. There are other tools where you just give a text prompt and you can get a complete picture generated.

Three Major Platform Shifts

We have been privileged to witness three big technology platform shifts that have fundamentally altered human civilization. They have changed the way we interact with each other, the way we consume information and the way we conduct commerce. First was in the 90s when computers that were sitting on desktop suddenly could get connected to each other through the amazing thing called the internet. The browser that was created in 2004 allowed us to access all the information very easily. The second shift happened starting 2006 when mobile phones, especially smartphones started appearing in our hands and the world shifted towards mobile computing. Now the third one is taking place, which is AI, work on which has been going on for the last several years. Since last year, we could see it, feel it and touch it. This will create thousands of companies, entrepreneurs and new ideas. Problems will get solved. 

Artificial Intelligence is any computer system that mimics or amplifies our incredible human ability called natural intelligence. AI can play board games and translate languages (like Google Translate). We can have very, very complex systems like ChatGPT or Bard that engage in conversation.  Even more sophisticated systems are now coming up in diagnosing health conditions.

Will AI replace us? No, it will amplify our efforts. It’ll make us smarter and be able to move more quickly and solve problems on a scale that we could not. The analogy I want you to keep in mind is how humans did movement and motion. When we were young infants, we crawled around the living room of our parents. When we got a little older, we learned to walk. Then we learned to run. Then our parents put us on a bicycle and using our own muscle power, we could go farther and faster. The bicycle amplified our movement in motion. Similarly, AI tools we’re building, will amplify our cognitive ability.

Four Buckets of AI

What can these systems do? What are they capable of doing now? The future falls into four buckets. 

  1. They can synthesize vast amounts of data.
  2. They can make predictions. They can look at patterns, come up with logic and tell us lots of things that will happen in the future, like the movement of a stock index or weather or copper production.
  3. They can create new content like how humans create using our right brain capabilities.
  4. They show capabilities of human conversation.  When we converse, we listen to the words, look at the gestures and the facial expressions and then respond to them. The systems are beginning to replicate some of the conversation capability. However, they only do it with words. They can’t read emotions, they can’t see and understand our gestures. But in future, those capabilities may develop, looking at the way generative AI is going. 

Let me put those into two categories. In the brain, we have the right side that does creative thinking and the left side does analytical, logical thinking. Similarly in AI, there’s an entire category of systems that seem to mirror the right side and that is generative AI. One of them is conversational AI, a system like Bard. It’s built on large language models. There are other systems that mirror the left side of the brain and they are analytical and predictive AI.  For example, there is a feature in Google Maps called eco-friendly routing. It can suggest the most fuel efficient route, for different types of vehicles. We tested this in Canada and now it has been rolled out in US and eight countries in Europe.  

Images, Music and Movies

Using Google Imagen, we can get images from text. If I want the picture of a chrome plated duck arguing with an angry turtle with a golden beak, I can get it in 20 seconds. Using Music ML, text to music creation is possible. Experiments are also going on to create movies from text, using a combination of Imagen and Phenaki. Now the quality is not so great. These are early days but those are solvable problems. In the future, this will get scaled up, so we can create lots of audio and video contents.  

Google has been at AI for a very long time. In fact, Sundar Pichai, CEO of Google declared as early as 2016 that we are an AI-first company. Every few years, roughly a decade or so, Google shifts its focus to a new platform. When we started in 1998, we were a ‘search first’ company. Around 2006-2007, when mobile phones became widely adopted, we shifted our focus as a mobile-first company and built our products around mobile. From 2016, we saw where the world would be headed in AI and became an AI-first company.

Three Audiences

At Google, we want AI to help three audiences: consumers; communities and companies. We want all our consumer products that you use work better. There are 15 products with at least half a billion people using them—Search, Gmail, YouTube, Google Lens, Google Translate, etc.  Second, we are looking at big social problems and trying to solve them. With Alphafold, we are trying to solve the protein problem in the world. Protein is essential for animals, plants and humans. There are 200 million proteins in the world and only 4% of them are well understood. We used AI and over a four year period, documented every single protein and it’s available in our open database called alphafold. A million biologists, scientists and pharmaceutical technicians are using it to conduct the research. Third, we’re helping companies grow by improving the marketing significantly by AI. We help companies to become more efficient by using AI and manage contact centres 24 X 7. 

Working on AI, there is so much of promise. But there are also a lot of risks and we understand this. We want to take a bold approach with AI, but also a very responsible approach. We work under seven core principles to guide all our work in AI. We’re very open and transparent about it.  

Unleashing a wave of innovation, we will solve many problems that exist in the human condition. We will increase quality of life and also lift a lot of people in their economic level. This will be to the benefit of all, if we manage it all very, very carefully. So, as Google founder Larry Page would ask us, “Are you uncomfortably excited?”  

“Generative AI will not replace you, however, a person using it will.”

Mr. Jaspreet Bindra, Tech Whisperer Ltd, UK.

The whole field of generative AI, in some sense, can be reduced to five fundamental facts, which I believe are the most significant today.  AI as a technology has been there for a very long time, while generative AI is something which we know of today. The word AI was actually coined by John McCarthy, around the time India got independence. It’s more than 70 years old.  AI in many ways is a philosophy rather than a technology. The technologies are the ones that sit under this AI umbrella—machine learning deep learning, neural networks, algorithms and so on. 

The 5 AI Facts

AI has come out from the background and probably for the first time into the hands of ordinary people like us. That is why we say that this is something which is amazingly powerful. That’s the reason why 100 million users have ChatGPT in two months. The next fastest app was TikTok, which took about nine months. Facebook took four and a half years. There’s a wonderful tweet by someone which says that in technology, there are decades where nothing happens. And then there are weeks where decades happen.   

1. This is Generative AI. Use it to generate, don’t use it to search.

Someone said that Google is a search engine and ChatGPT is a thought engine. Think of it as something which is creative. Generative AI is built on large language models. These models are trained on massive amounts of language, text conversations, paragraphs, etc. ChatGPT3 is two generations behind. We’ve had ChatGPT 3.5. After that, we have ChatGPT 4. When ChatGPT 3 was trained, all of Wikipedia was just 0.6% of its training data. So you can imagine the sheer amount of words and language that has been fed into it to train it.  

A chat GPT or Bard pretty much makes up stuff as it goes along. It sometimes hallucinates. It’s not optimized for facts or truth. It’s actually more optimized for believability or plausibility. It’s actually what we humans do. That’s why we feel a little bit of kinship with these new, human like technologies.  

2. Generative AI will not replace you, however, a person using it will.

Kent Beck is a legendary Software Engineer. He wrote that he was reluctant to try ChatGPT. In his tweet, he says, “Today I thought about that relevance.

The value of 90% of my skills just dropped to $0. The leverage for the remaining 10% went up 1000x. I need to recalibrate.” Most of the white collar jobs can be replaced by AI.  A report by Goldman Sachs says that AI will affect about 300 million jobs across major economies. About 7% of jobs will disappear. If you’re a low end coder, a journalist summarising your stuff and calling it news, then your jobs will go.

30% of jobs are safe and these are menial jobs. If you’re a farmer or a construction worker or a nurse who’s working on compassion, then nothing is going to happen to your jobs. A bunch of new jobs will be created. We still don’t know which ones they will be. Every technology has created more jobs than jobs lost. Net-net, there are always more jobs created. It’s up to us whether we use generative AI to enhance our jobs or become lazy and let someone else who uses it to take that job away from us. Generative AI hits the cognitive jobs or the higher end jobs first. That’s why, in India, we may have a minimum effect on jobs, while the developed economies will have the maximum impact from generative AI. It will vary across industry, it will vary across function. But the key thing is that it will not replace you. Someone using it could replace you. So don’t fear AI. You have to fear a human being using AI. 

3. The horizontals are interesting but the verticals are useful

We see many horizontals in Generative AI like ChatGPT, Bard, and LLaMA. These are interesting and they do a lot of things.  But the really useful stuff will be the verticals which are industry and domain specific. 

4. Generative AI will be as transformative as were search, internet, email or phone

Every 10 years or so, a fundamental platform shift happens. We are at the time of a platform shift. It’s going to reshape technology, industries and big tech. There’s a new tech company called Nvidia. It’s a trillion dollar company, which emerged out of nowhere on the back of generative AI. We’re going to see some of these newer things reshaping the world. 

5.General Artificial Intelligence is not equal to Artificial General Intelligence

We talk about super intelligence where technology becomes as intelligent as or more intelligent than human beings. There’s a lot of conversation happening in this. Elon Musk, Sam Altman, Geoffrey Hinton and others are talking about it. What we have today is not artificial general intelligence, at least for now. In AI, we have something called the alignment problem which is about how you can embed in AI values that are aligned with human beings.

My view is that within human beings themselves, the values are not aligned. We don’t agree on democracy. We don’t agree on what truth means. We don’t even agree on what facts mean. So the danger is not with a super intelligent AI, but with us not agreeing with each other. There are lots of ethical issues around AI. We’re talking about regulation, plagiarism, bias and fake news which are environmentally very destructive. For the first time ever, the creators of this Generative AI industry are the ones who stand up and say, “Regulate us.” We will see a lot of action in this space.  

“This technology works on probabilities.”

Mr Sankaranarayan ‘Shanky’ Viswanathan, TCS

At TCS, I lead the generative AI initiative alongside a lot of emergent tech initiatives. One of the biggest questions our customers ask is: What do we do with AI? It’s a phenomenally good tool to give me a route from Delhi to Chennai, to tell me all the restaurants where I can eat and the temples I can go to.  A lawyer was bold enough in the US to create an entire legal submission based on ChatCPT, but only to be thrown out, because the judge realized that some of the case references which ChatGPT had given did not exist at all. It cooked up an airline that did not exist. 

This is a fascinatingly good technology and it is ripe. But the biggest question our customers in industries are asking is: What do I do with it? The natural inference is that it is good to converse. So the first immediate thing that customers think is it will replace contact centers. Generative AI is a good tool in areas where you can verify the answers and you are comfortable with the response. How can you control the response when you expose it into a wider ecosystem? These are the challenges that enterprises have.  

Need for Training

This technology works on probabilities. You ask technology a question from what it has been trained to answer. If it is unable to find an answer, it keeps trying to build a language as a response, which is closest to the answer that you have. The probability might just be 17%. It doesn’t care, because that is the best response it could give. So, let us not worry that this machine will lie at any point in time, if you are able to train this model with sufficient data.

The second big challenge customers have is bias. We were operationalizing a mortgage with an insurance provider in the US. Ironically, we realised that a lot of insurance recommendations were more attuned to working class white men. Immediately there might be a regulatory body pointing out the inherent bias. The fact is that it is not an inherent bias. We need to understand and appreciate that the general corpus, the Wikipedias of the world, will have a lot more articles on white male than a tall, dark, handsome Tamilian sitting in Chennai.  We must feed information and data to ensure that this bias is suitably managed and controlled. 

Third, you have to be extremely prescriptive. You must ensure legitimacy when you prescribe. Again, it is all about probabilities. There are methods to ensure that the large language model starts to zero in on the right answer, rather than give any of the vague answers. There are a lot of training methods for that. These technology concerns which exist, can be mediated through processes, procedures and adjacent technology. So making it viable within your organizations is a viable prospect. We must understand, appreciate and embrace the beauty of the technology rather than anything else. 

Need for Guardrails

Generative AI’s response has a bearing on the way you interrogate or interact with it. It is not feasible for you to go and educate everybody in your organization to do things in the right way. So sufficient guardrails must be put within your enterprise or organization to ensure that such deviations do not cause serious harm. 

We must use it for creative purpose. Most of our customers right now are using it for its conversational capability because it converses very well. The second big usage that we see is anything which entails knowledge search. For example, in your HR department, a lot of people ask you about the PF or LTA conditions. If you give all the information to AI, you don’t need a person answering these questions. There is a phenomenal opportunity to leverage anything related to document extraction and summarization. It does it in a phenomenally good, secure and predictable way. No challenges at all. But that is just the tip of the iceberg.

Tacit Knowledge

The biggest opportunity generative AI is going to unravel is in data analytics. An investment advisor looks at a huge amount of charts and then gives his recommendations. A shop floor mechanic who looks at a huge turbine problem comes and looks at all the preconditions and parameters and says what you have to do to fix that. What we have done so far is, we have automated the intelligence being presented to people, so that the right action can be taken in a phenomenally good way. The most important thing is to understand that the space between our ears is what defines how actions are being taken. That is what I call tacit knowledge.

While plumbing is the same, you still want the best plumber to come to your house. Because you know that experience and tacit knowledge exist. To fix your turbine, you want the person who’s seen this problem multiple times to come and solve the problem. The reason is, this inherent knowledge is never captured in a company. We must be able to formalize, define, capture and document knowledge. More often than not, our industries are still knowledge driven. They are run by experienced people who know what calculated action is to be taken.  

Knowledge as a Capability

What if we are able to disrupt this knowledge value chain? Generative AI or large language models are not about predicting the next best word like a WhatsApp message. Language is the best form of documenting knowledge. Language is the form of communicating knowledge. Generative AI, when you feed data, insights, intelligence and more importantly, the actions which have been taken in the past, has a unique ability to discern and distill knowledge and save it. It will be able to cross the knowledge gap and then discern and determine the right action to be taken.

Just visualize this. You capture knowledge across your workforce, create a knowledge corpus as a capability and make it available for anybody in the world in your type of organization. That to us is the biggest difference Generative AI will make. For example, a shop floor person goes and stands in front of the turbine and tries to figure out the problem. It is not about just his knowledge. It is about the collective knowledge of every shop floor mechanic, from what happened in the past and it is available to them in a digital fashion.

So the biggest shift that generative AI will create is that knowledge as a capability will be made available to every industry in a similar category. Don’t just focus on collaborative automation or knowledge extraction. Generative AI provides a unique opportunity for you to reimagine your enterprise. It is not about automation or productivity improvement. You can completely reimagine the way your shop floor will work using multiple technologies together.

The Convergence of Three

There are three very important technologies which converge to make this a reality.  The first is compute. The compute capability of chips will become so pervasive that they will be existing in a watch, in a cell phone, and in an IoT device. Each of these chips can potentially run one large language model on its own and deliver specific outcomes.  

The second big technology is 5G. 5G is not about downloading YouTube videos fast. It’s about having have pervasive systems of connectivity, to bring intelligence to life and collaborate with any of the systems of knowledge. 

The third big disruption which is happening already is the convergence of cyber and physical systems. What we mean by cyber physical systems is that most of the robots are built for robots to exist on their own. Humans will collaborate with technology and systems and robots.  

Last but not the least, digital twins will give real time avatars of everything that is happening around you. That gives the context; Generative AI gives the knowledge. Cyber physical systems ensure people and machine work together in a completely different way against the ubiquitous connectivity enabled by 5G. We must thus look at multiple, concurrent technologies together to reimagine our industries. Generative AI is the biggest piece of the jigsaw puzzle, primarily because it is not about automation. It is about a knowledge driven enterprise. Knowledge is going to be enabled as a capability within your respective industries. These are, therefore, absolutely exciting times.  

Reimagining Business in New India

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As the world emerges from the pandemic, it has opened up numerous opportunities. However, these opportunities come with challenges that India and the rest of the world must contend with. In this conclave, successful entrepreneurs, leaders and experts share their thoughts, opinions, insights and experiences with a focus on inspiring and guiding businesses, young entrepreneurs, and investors about the opportunities available and how to grow their business potentials.

Mr Sunil Mathur, Director General of Income Tax Investigation (TN & Puducherry)

We have just come out of a very difficult period. We are really lucky that India—our people, economy and businesses—has been very resilient. Although we had a bad FY20-21—the economy was literally in recession and growth was negative at around 6%, we did well in the subsequent FY21-22. The growth rate has been around 8.5%, and in the coming financial year, it is expected to be 7.5%. This shows that the country is recovering and the economy gaining the momentum lost two years ago. This fact is also borne out by the robustness in revenue collection. Last year, the government had targeted revenue collection of about Rs.22 lakh crore but the revenue departments could achieve about Rs.27 lakh crore. This shows that revenue collections are rising and there is momentum in the economy. This year also, after the first instalment of direct tax collection, we find that there is a growth of about 45% in net collection. These figures indicate that businesses have done well and are ready to take India into the next level. We have a new India which is looking to leap into a league of advanced nations. In this new India, our current government wants us to be Atmanirbhar Bharat—a self-sufficient and self-dependent India where businesses have a big role to play.

Efforts in Digitisation

Businesses among themselves are doing well in adopting technology. The government is also trying to keep pace with them and it is not lagging behind. The tax departments have taken a number of initiatives in digitising processes and compliance requirements, thereby making an effort to ease the compliance burden of taxpayers. You must have seen what has happened during the past 10 years in the IT department—right from payment of taxes, getting PAN number allotted, filing of income tax return, filing of TDS return and processing of returns, etc. Now you can do everything online, sitting at home!

About two or three years ago, the scrutiny of assessments by the IT department was an area where the taxpayers were required to come to the IT office. If their case got selected for scrutiny, they will have to come to the IT department to attend to proceedings of assessment and also subsequent proceedings. In August 2020, a transformative decision was taken by the government. The Prime Minister announced a scheme that honours the honest, in which it was decided that the major part of income tax department would become faceless. After two years, we have almost implemented that scheme.

The features of this scheme are very unique, and they may not be there in many of the advanced countries. Under this scheme, if your case is selected for scrutiny, you will not be required to go to the IT department. Whatever notices are issued, the communication will be online. The information will come in your registered account. Once the notices come, you will also have to file all your responses and submissions to the questions asked, online.

Territorial-less Assessment

Another feature is the scrapping of territorial jurisdiction. If you are in Chennai and say, you live in Nungambakkam area, there used to be an assessing officer in charge of Nungambakkam area and you had to appear before that officer for your scrutiny assessment. Now, your assessment will not be done by him. It may be done by anyone else in the country. Your assessment case may be assigned to somebody in Gujarat, Assam or Rajasthan.  You will not have any contact with your assessing officer. He may be far-off and will communicate with you only online.

Group Assessment

The third feature is group assessment. An officer who has been assigned from any part of the country will question you, but he will not do it alone.  He will prepare a draft order which will then be shared with another unit called review unit. This unit will review the draft order and only when it approves the order, a final order will be passed. This scheme is called group assessment. The idea is to make it comfortable for the taxpayer to comply with the requirements.  During the initial implementation of this scheme, there were some teething problems. There may be some problems even now and we are improving them. Some of the taxpayers want to have personal hearing as they want to explain their case personally.  So the government has allowed to have personal hearings too, but again, these will not be face-to-face or in person. It will be through video conference and the assessing officer will be at a remote place. The link for the video conference will be shared with the taxpayer.

The faceless and territorial-less assessment has now been extended to faceless penalty scheme and faceless appeals. The appeals were being done by the Commissioner of Appeals. Now if you appeal from Chennai, it will be heard by somebody sitting somewhere else. This is a transformative change which has been brought by the government with the intention to minimize the compliance burden of the taxpayer.

Goodbye to Parking Woes

On a lighter note, while this has brought a lot of comfort to the taxpayer, our officers have become lonely. Nowadays, there are hardly any visitors to the IT department. Earlier we used to have parking problem in our offices. It is no more there because whatever the taxpayers want to say, they have to say it online. It is also compulsory for the officers to communicate with taxpayer only through online.

Of course, there is an exception to this: the investigation wing, which is in charge of conducting IT raids. From this wing, sometimes we go to the taxpayer and at other times, the tax payer is called to our office for scrutiny.

Re-engineering of Conventional Business Using Technology

Mr Santosh Parekh, Partner, Tulsi Silks, Chennai

  • Thirty years ago, we did not have a differentiator in selling our silk sarees. I stayed in a weaver’s place for three months to understand the weaving process. Then we did backward integration, added looms and designed our sarees, after which our business started picking up gradually.
  • Family owned businesses must embrace technology and for which, a top-down approach is needed. It is very easy for people with business experience to adopt technology.
  • To insulate from competition, businesses must focus on R&D, investing in technology and recruiting the best talent.
  • We have embraced technology and we are now using apps in our entire business, providing customers and other value chain partners with great experience.

Trade from India – The Story for Next Decade

Mr Navin Ranka, Director, SPR India, Chennai

  • Historically, India is very strong in trade. Trading comes to India quite naturally but we don’t focus on trade tourism as China does.
  • China makes 49% of US toys, 70% of world umbrellas, 60% of world buttons and 72% of US shoes. All these are not high tech.
  • India’s falling behind in trade is because of its losing steam in manufacturing, while focussing heavily on services.
  • Parking, safety and sanitation, restricted movement, risk of fire, rainy days and legal challenges are the key impediments to doing trade in India and showcasing it to the world.
  • The solution lies in building world-class Trade Parks. Each Tier 1 city must have at least one or two trade parks.

Brand Building for Success

Mr Vijay Parthasarathy, Brand Specialist, Mind Coach and Speaker

  • Businesses must develop a strong brand narrative that resonates with customers.
  • Emotions are the key to build a powerful brand. It is never about what we are. It is always about who we are.
  • The secret to building a powerful brand is picking the right emotions, mapping it with the target customers and then building the narrative carefully.

Tax Technology—Current and Future Trends

CA Divyesh Lapsiwala, Partner, Ernst & Young, Mumbai

  • Tax technology is all about tax professionals and very less about the software itself. Therefore, tax professionals must drive the technology.
  • Earlier, it used to take a long time to summarise the transactions and tax used to be the last point. Now with ERPs being used by most companies, we see frequent use of the tax module and thus, tax planning. Tax has thus determined the way of running businesses.
  • The penetration of tax technology that we see in India is not seen even in many advanced countries. They are now trying to introduce the tech with many similarities to the India model (like E-invoicing and GST filing). It is a proud moment and an opportunity for us, as we go along.
  • Looking at GSTIN data for the last 4 years, we can see that 80.2% tax payers are proprietary concerns paying 13.3% of GST.
  • E-Invoicing is one of the most successful and transformational thing that India has done.
  • The guiding principle of new approach is based on: Re-use of IP; leveraging new technology and Re-use of data.
  • Efficiency, Risk & Governance and Value optimisation are critical aspects in tax transformation.
  • Tax professionals must aim to offer platforms that can be operated on mobile phones and which can be easily used by the customers. This presents huge opportunities.

Stock Market and Opportunities in Alternative Investment

Mr Sudarshan Lodha, Founder & CEO, Strata Property, Bangalore

  • Investments must give a return that can beat inflation.
  • There are multiple products available in the market that can give you good returns and help you grow your business. Some of the alternate investment opportunities which are different from traditional investments are:
    • Invoice discounting
    • P2P lending / Liquid loans
    • Fractional commercial real estate
    • Working capital financing
    • Bonds (E-rated bonds that give a very good return)
    • Revenue based financing
    • Asset financing (like funding charging stations for Electric Vehicles.)
  • Platforms are there for all these options. They take care of the CIBIL score and other requirements that a lender / investor must be concerned with.
  • KredX, Wint, Grip, Klub and Smallcase are some of these platforms. Using these platforms, one can also raise money for their own businesses.
  • Though there are risks associated with these like defaulting of bill payment by a company, these can be managed by carefully selecting the companies. Investors can experiment with a minimum of 3 to 5% of their portfolio in these alternate investments and explore.

Stock Market and Opportunities in Alternative Investment

Mr R Pallava Rajan, Founder -Director, PMS Bazaar, Chennai

  • There are two major categories of alternative investment.
  • Category 1: Angel funds, Venture capital funds, SME funds and Infrastructure funds
  • Category 2: Private equity funds, debt funds, Fund of funds, Real estate funds.
  • There is enough of asset class available in our country that is well regulated and which can be picked by us, with minimum investment. All asset classes will not perform well at the same time. Investors must understand this fact and have a well-diversified and balanced portfolio.

Emerging Technology – Driver for Business Growth

Mr Vijay Hebbar, Sr. Vice President & Global Head, Sales and Marketing, KrypC, Bangalore

The Top Trends that can impact your business are:

  • Smarter devices (like intelligent home robots)
  • Robotics, AI and Machine Learning
  • Computing Power (Use of Cloud, 5G and 6G)
  • 3D Printing (including printed food, metal and composite materials)
  • Genomics (modified crops, disease eradication, new vaccines and medical breakthroughs)
  • New Energy Solutions (Green Energy and Cost Effective)
  • Quantum Computing
  • Digital Trust / Blockchain (Distributed ledgers and non-fungible tokens –NFTs that transform the world)
  • Extended Reality (ER) / Metaverse whose advances pave the way for incredible experiences.

Transition of Family Business to Next Generation – The Nitty-gritty and Nuances

Mr Krish Srikanth, Business Family Mentor, Life & Executive Coach Organisational Consultant, Chennai

  • Business owners must know the difference between business and employment. If the day-to-day operation of a business cannot run if the owner is not there, then it is not a business. It is, in other words, self-employment for the owner.
  • Have a vision for the business.
  • Treat business income as separate from personal income. The owners must aim to become to financially free as individuals. Even if the business fails, the individuals must be able to run their life with the same lifestyle. Therefore, diversify your investments in different buckets.
  • Different business models are followed by family run businesses. They are meritocratic model (the best person manages), democratic model (all are treated equal), multi-trust model and cash-it-out model (where the business owners fight and kill the business. It is better to sell such businesses and distribute the money to the family members)
  • Writing a personal will is very important and more so, for family business owners. Believing that nothing will happen to us is akin to having a no business model.
  • Business owners must have plans to overcome some of the common problems faced by the family business owners and which are:
    • Ensuring other family members work properly. The talent level of the members is an important factor.
    • How to get good non-family members to join the business and they remain loyal to the business.
    • How to prepare and groom the family members.

The Making of a Successful Entrepreneur

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MMA in association with Madurai Management Association and Konrad-Adenauer-Stiftung (KAS) along with the support of like-minded organisations organised an offline conclave on the theme, ‘The Making of a Successful Entrepreneur,’ at Hotel Taj, Madurai on 19 March 2022.

Mr Shanmugasundaram, President of Madurai Management Association delivered the welcome address. Mr Pankaj Madan, Deputy Head-India Office and Head Programmes, KAS delivered the opening remarks in which he highlighted various activities and programmes organised by KAS worldwide including the political dialogue programmes and programmes organised in India. He requested the entrepreneurs to add a ‘Green Tag’ when looking at business plans and made a strong case for sustainable business practices, including practising of ‘circular approach to production.’

Circular economy will help India to the tune of 40 Lakh crores by 2030, he said. India is estimated to reach a net zero economy by 2070 by which time 50 million jobs are going to be created. By 2030, there will be economic opportunities worth 1 Tn $, he explained, quoting from published reports.

Dr S Aneesh Sekhar IAS, District Collector & District Magistrate, Madurai, delivered a special address on the theme, ‘Startup Opportunities in Madurai and the Support of Tamilnadu Government.’ Startups were there even during earlier decades but now it has gained much importance. There are many startup owners now, because venture capitalists, PE fund owners and others are ready to fund them now, but during the previous era, funding was very restricted in view of the risks involved in a starting an enterprise, he noted.

He spoke about various measures announced in the Tamilnadu government budget to promote startup ecosystem, especially in Tier 2 cities. Three startup hubs are planned in Erode, Madurai and Tirunelveli, he said. He noted that the startup incubator cell in Thiagarajar Engineering College is doing a good job and hoped that investors will support startups coming up in Madurai.

Dr Asit K Barma, Director, Bharathidasan Institute of Management spoke on the convention theme. He spoke about the massive shift from individual company-focussed business models to platform based models and about how Amazons, Olas and Ubers and Tech companies like Google share the major pie of market capitalization and how they have created values for themselves. According to him, for India, to reach 1Tn$ economy by 2030 is a tall order and to achieve this, we have to grow in a non-linear way. Traditional companies always were creating value using their internal resources whereas the Amazons create value by orchestrating their external resources, he said. Companies today must aim for Scale, Scope and Speed (3S) to achieve exponential growth, he argued.

He predicted that today’s cold war will be centered on data. For getting higher productivity from existing factories, especially in Tamilnadu, he suggested the below:

a) Marrying economic engine to ecological engine and making ESG a part of the organisation’s culture.

b) Converting existing IT parks into digital parks

c) Leveraging existing natural resources in the State and doing value addition in Tamilnadu itself.

d) Focussing on developing the ecosystem and skilling, upskilling, reskilling the State’s youth.

Mr Peter Rimmele, Resident Representative to India, KAS spoke on ‘Entrepreneurial Ecosystem in Germany.’ He pointed out that German entrepreneurial ecosystem has a huge impact on the European entrepreneurial ecosystem.

Mr Peter Rimmele stated that there are six pillars that hold this entrepreneurial ecosystem, namely: the policies of the government /companies; financial system; culture; the support system; the human capital and the market situation. These pillars are unique to each country and therefore, they cannot be copied, he remarked. He touched on the social projects undertaken by the companies in Germany, which is slightly different from the CSR concept in India. He opined that in India, the system is overregulated and under-governed. He pleaded that companies should not just look at how much profits they can make but also on how much they can contribute to the common good of the society.

The trade-off between values and valuation is an important factor. More than mere valuation, the values that companies provide will ultimately matter. ~ Mr K Hari Thigarajan

Mr K Hari Thigarajan, ED, Thiagarajar Mills Pvt Ltd, the Chief Guest stated in his address that as the bank interest rates have come down throughout the world post-Covid, many investors try to put their funds in startups but this situation may soon change and the startup ecosystem may not be as hot as it was during the recent times. The trade-off between values and valuation is an important factor, he said. More than mere valuation, the values that companies provide will ultimately matter, he argued. Constant innovation, use of e-commerce and digital technology, conducting SWOT analysis and constant re-strategising are very important in this VUCA world, he said.

He explained many of the best practices followed by the founder of Thiagarajar Mills. He talked about how he brought down the cash-to-cash cycle time, even without knowing about such concepts or studying MBA.

Robust Public Policy for Business Transformation

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Business transformation of the innovation ecosystem is not only inevitable but also a highly complex and uncertain process. The way to facilitate transformation with policies has become a topic of common concern for academia and policymakers.

We need public policy to ensure stability. We need public policy if we want to change or transform. We need public policy to adapt or react to change. In all these three situations, public policy becomes very critical; its absence or a wrong public policy can lead to disaster as we have seen in many instances. It is an understatement to say that we are in a world that is transforming exponentially on all fronts. A simple illustration of ‘exponential’ is the story of the chessboard that may you recall.

The man who designed the chessboard presented it to the king. The king saw it and was so impressed that he said, “Ask what you want.”

The man said, “I only require one grain of rice on the first square of the chessboard; twice that on the second square, twice that on the third and so on.” The king said, “Oh, is that all what you want?” He ordered that to be fulfilled, not realizing that when you double 64 times, you will reach a fancy figure of one quintillion. The entire granary in the kingdom was not sufficient to meet the man’s needs or desire. That’s the power of exponential and that’s what we see now. This is apart from the Covid effect, which businesses and commerce are facing. We will continue to be in a world that is volatile, uncertain, ambiguous and fast-changing exponentially. Forget about differences in generations. That’s the pace of change and development happening. In his book, ‘The Law of Accelerating Returns,’ Ray Kurzweil did the math and found that we are going to experience 20,000 years of technological change over the next 100 years.

Built for stability, not disruption
Our biggest companies and government agencies were designed for another century for purposes of safety and stability—built to last as the saying goes. They were built to withstand rapid radical change but not the exponential change, which we are seeing today. That is why, according to Yale’s Richard Foster, 40% of today’s Fortune 500 companies will be gone in 10 years, replaced by the most part by big upstarts who are not heard of before. This is true of regulations and public policy too. Their shelf life is significantly limited and will soon become outdated. These need to be contemporary. A leading author predicted that in 10 years from now, you may perhaps need a license to possess a human operated car. During my younger days, we needed a license for a radio and a transistor; for a bicycle and a bullock cart. That was the policy in those days. As things changed, today you don’t need a license for a mobile or any other wireless gadget.

If you look at the graveyards of companies, there you will find all those businesses which did not recognize and adapt to change; those businesses that did not read the tea leaves or smell the coffee brewing and which did not adjust their sails to the wind. This is true of professions too.

Introspect and evaluate
My first message to businesses is to introspect, which they often don’t do. When things are going well, one doesn’t introspect. One must identify the trends and patterns and all that is happening around. What is gradual today can become exponential tomorrow but the most important thing is determining the elements which contribute to the success today. Why am I successful? Why is my business successful? Why is my profession successful? Why am I wanted? Why are we in existence? What are those elements which contribute to your success today? That is the analysis which often people fail to do.

The next step is to evaluate if those elements will continue in future. We need to apply the same test for all the regulations and public policies. Will this continue in future? If not, what does it mean for your businesses? The corporate strategy work is not just about improving profits. It’s about understanding the tea leaves; looking at what elements contributed to the success. Particularly, those businesses which are exposed to or impacted, whether favourably or unfavourably by regulations need to focus even more on public policy and ask: Will this be forever? What are those changes which are likely to happen? What are the changes which should happen? Businesses need to identify who their competitor is. For Toyota, it is not General Motors. It may be Tesla or Google.

End of exclusivity era
If you are in a space where you are exclusive—whether as a profession or a business—like a chartered accountant who is the only person authorized to audit or somebody else who is the only person authorized to represent before tax authorities or a particular business which is the only business licensed to do a certain thing, remember that those businesses and professions are under threat. You have to realize that exclusivity cannot continue forever.
It is equally important that regulated businesses which are protected are also highly vulnerable. I remember the time—before the Narasimha Rao government came in the 90s—when you had to import goods and services using an import license. The business that thrived in those days were canalising agencies. When regulations got dismantled, those businesses disappeared completely.

Not cast in stone
This is what I mean by evaluating the current systems and looking at everything, including regulations and public policy around us. Let us look at some of the areas where public policy plays a key role and will continue to play a key role. Take the first one, which is about trade agreements—the economic boundaries. You would recall that when Donald Trump came in, overnight he started dismantling trade agreements, reneging on all the trade agreements. That means that all those who were relying on those agreements as being cast in stone were suddenly disrupted. It required a revisiting and reshaping of public policy. This can happen to anything. Don’t proceed on the basis that a particular law has come in and that it is a law which is cast in stone. We have seen what has happened in the farmers’ agitation recently.

Not a mere buzz word
The second important thing is the fourth industrial revolution. It is a congruence of the physical world, the digital world and the biological world and it is revolutionizing businesses. It’s revolutionizing the world. Everybody will be impacted by it. No profession is exempt from it. But what is happening is that the change is so rapid that the society’s systems and laws are not keeping pace with it.
That is where public policy plays a key role. We suddenly saw the Ubers and Olas coming in. The yellow and black taxi drivers started waking up. Everybody started waking up and pressed for regulations around the drivers and pricing mechanisms. This is a classic example of a business model which arose first and then the society started waking up to say that they need public policy and regulatory changes. The question is—shouldn’t we be looking at all of these, including the impact of the 4th Industrial Revolution, climate change, ESG and diversity? These will not only transform our businesses but we will also have public policy that will impact the businesses.
We need to have public policies in the areas of autonomous vehicles, labour laws, non-tariff barriers which are coming up and alternate dispute resolution (ADR). Our courts are clogged and increasingly, there is a talk of alternative dispute resolution. We need public policy mandating ADR so that we can de-clog the judicial system. Businesses have started looking at their contracts to see if alternate dispute resolution with a conciliation or arbitration clause can be built into their contracts rather than pursuing a protracted litigation. New business models are coming up like the emergence of Ola, Uber and AirBnB. With the growth of the technology companies like Google or Facebook, the world is now waking up and realizing the power which they have over all of us, especially with the data they possess. There is talk of antitrust rules and if they should they be allowed to continue in the same way.
With increasing cybersecurity threats, what are the policy initiatives that are required? Look at education. The other day Byju’s announced that they would raise 4 billion. What does it mean? What happens to the brick-and-mortar schools? What happens to the education policy? What changes are required in the way online education is to be conducted? Do we need regulations and public policy initiatives? Cryptocurrency is being widely discussed today. These are just some illustrations.
The three who can shape it
Public policy can be shaped by three sets of people—the Government; the businesses; and the users or those who are impacted. Advocacy and shaping of public policy has become a key agenda item for businesses.
Let’s look at some of the businesses which have been impacted very recently by a lot of these changes. NBFCs were suddenly impacted by RBI’s new regulations in terms of how provisioning should be done, particularly in the case of restructured loans. For RTPs (Related party transactions), SEBI has come up with a document and a new set of rules. Corporates are grappling with it. The question in all of these is, will you be reactive? Will you be proactive? Do you need focus on public policy? What are the areas that you need to focus? How do you shape public policy? How do you shape regulations? For more than a decade, telecom companies were battling the interpretation of a regulation on spectrum charges. Finally, all of them had to cough up thousands of crores of rupees. Had they worked on public policy initiatives in terms of getting the definitions upright or right upfront, perhaps the pain would have been considerably lesser. The same situation will be faced by automobile companies in terms of pollution or the electric vehicle policy. Credit card companies were suddenly disrupted when RBI came down heavily and barred them from issuing new credit cards because they had not complied with certain requirements. Overnight, their businesses were disrupted.
Drive the agenda
So to conclude, businesses should drive this agenda. And how should they drive this? First, they should have a responsible person or a department which continuously monitors the developments and prepares the roadmap for action. In your business, if you do not have a person in charge of public policy or regulation, you will be history soon because you’ll only be reactive and not proactive. The second is, businesses and professions should actively work with industry and professional bodies as a collective voice.
The third and most important aspect is that an industry body, business body and professional body must try and have a seat at the table where policy and regulations are shaped. The fourth, identify and connect with influencers. There are many experts in the field who the government and others go to for advice in terms of shaping regulations. Businesses and professions should connect with such influencers.
Listen to and also use social media and other channels to ensure that your voice is heard. Most importantly, be proactive and not reactive. Whilst we talk of public policy and regulations, I am passionate that there needs to be a balance. You can’t have over-regulation. At the same time, you must ensure there is a free market. Today, we are seeing a trend where regulations are more knee jerk in nature. Regulations are introduced without doing enough work. Maybe, it is because of a lack of early inputs in shaping the regulations. In the case of Companies Act 2013, there were multiple parliamentary committees, finally ending with the 2013 bill, which became an act. At least, there was a lot of debate and there have been numerous amendments thereafter.
Nail the root cause
The point is, if you have to shape public policy and are able to shape regulations appropriately, you need to first identify what the problem is. See what change is required and why it is required. The second most important thing to do is a root cause analysis. Often, we think of a particular remedy which is, more often than not, wrong because we haven’t done a root cause analysis of the problem. Third, identify potential solutions and determine the right solution. The fourth is to have a very clear view of the outcome of the regulation or public policy. It may be fashionable sometimes to say we need a certain type of voting pattern for independent directors or for related party transactions. But what is the outcome you’re seeking to achieve and how? Outcome determination before a public policy or regulation is finalised is, in my view, very critical.
Have futuristic boards
Lastly, let me come to the role of the boards. The boards play a very critical role. I believe the role and the board agenda has to change. It has to change from focussing on the past and performance, to focussing on the future. Boards have to be forward looking. They must see what the future is going to be. How do we prepare or adapt for the future? What enabling legislation is required? What transformation is required? What public policy changes are required?
As Henry Ford said, “If you continue to do what you are doing, you will continue to get what you are getting.” n

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