Protiviti, in collaboration with the Confederation of Indian Industry (CII), recently unveiled a report titled “AI Trends and Future Impact: Industry Adoption and Insights”. The report highlights transformative AI trends across industries and explores its future impact on business strategies and operations. On the sidelines of the summit, Sachin Tayal, Managing Director of Protiviti Member Firm in India, spoke with Tech Achieve Media to share his perspective on the rapidly evolving AI landscape. In this engaging discussion, he addressed the significance of an “AI-first” approach, the role of leadership in driving AI adoption, and how emerging technologies like generative AI and data protection frameworks are shaping the future of business.
Also read: India Stands at the Cusp of AI-driven Transformation – Protiviti and CII Report
Read on to explore Sachin Tayal’s insights on how AI is transforming industries, strategies for successful AI adoption, and the immense potential of this game-changing technology.
TAM: Like many have cloud first approach while deciding Infra now, what is the probability leaders will have AI first approach to solve problems? Or will companies hold back due to the ROI aspect?
Sachin Tayal: AI is going to take us beyond a cloud-first approach. Think of it like the time when the internet was emerging wherein many doubted its widespread adoption. People questioned how many would actually use the internet. Similarly, during the early days of automobiles or mobile phones, no one could have predicted their ubiquity. For instance, when mobile phones first appeared, who would have imagined they’d eventually come with cameras? Now, it’s hard to find a phone without one. AI, in my view, is that kind of revolutionary shift.
Also read: Budget Announcements to have Cascading and Net Positive Effect on Industry – Sachin Tayal
What’s unique about AI is its impact on individuals, not just organizations. For example, my daughter, who’s in class 10, uses ChatGPT daily. This generation is growing up with generative AI as a natural part of their lives. The transformation we’re witnessing will lead to a generational shift. My father, for instance, struggles to use a mobile phone the way I do. But the next generation will be incredibly AI-savvy. This revolution goes beyond what we saw with cloud-first strategies.
Regarding ROI, the perspective has significantly changed. As per the survey conducted, over 300 companies in India were analyzed, and only 3% reported that they have not yet implemented or are not planning to implement AI in the near future. That means 97% are either in the process or already on board. This indicates how widespread AI adoption is becoming. So, ROI is no longer the primary question, and it’s evident that AI is the future, and organizations are actively embracing it.
Gone are the days when ROI was primarily about investing in networks or implementing ERP systems. Organizations now realize that digitization significantly boosts efficiency and enhances customer service. Take restaurants, for instance. A chef might think their culinary skills are enough, but by connecting with e-commerce platforms, they can reach far more customers and scale their business exponentially. India has moved on from traditional approaches, and that’s why we’re seeing a rapid adoption of AI. In my view, the question of ROI when it comes to AI will soon be irrelevant.
India’s transformation isn’t surprising when you consider its digital journey. Affordable high-speed internet, the rollout of 5G enabling Industry 4.0 and even Industry 5.0, and the government’s push for a robust digital economy through initiatives like UPI and Aadhaar have laid a solid foundation. These advancements have created an ecosystem where innovation thrives.
We once said, “Data is the new oil.” Today, that data is fueling an entire digital revolution. It’s not just numbers but data is now pictures, videos, and so much more. Videos, in particular, are becoming a significant part of data. In this context, ROI should no longer be a concern. The focus has shifted to leveraging these advancements to drive growth and innovation.
TAM: As AI evolves, what strategies can organisations adopt to future-proof AI investments?
Sachin Tayal: In my view, progress will keep getting better and better over time. Think of it like buying a new laptop or phone. You’ll always find newer and better versions coming out. But that doesn’t mean you should hold off indefinitely, wondering whether to buy the original iPhone or wait for the iPhone 8 or iPhone X because they’re better. The same principle applies here. Technology will continue to evolve, but that doesn’t mean you should wait for the “best” version and miss out on the “better” options available today.
TAM: What lessons can organizations learn from early adopters of AI?
Sachin Tayal: The applicability of AI depends heavily on the sector. Let’s start with one of the largest sectors in the economy—financial services. In banking and finance, AI is widely used for algorithmic trading and investment strategies to maximize returns. However, the sector’s biggest challenges revolve around fraud, risk management, and money laundering. Anti-money laundering efforts, identifying investment opportunities, and deciding where to grant loans are areas where AI plays a critical role.
Additionally, compliance is a significant aspect of banking and NBFCs today, and AI can streamline the implementation of compliance frameworks within these organizations.
Now, turning to healthcare, there’s growing discussion about legislation that may mandate AI involvement in diagnostic procedures. For instance, no PET scan or MRI results may be confirmed without an AI-reviewed second opinion. The accuracy and reliability AI can provide often surpass what a radiologist alone can achieve, offering greater diagnostic confidence.
Moving on to the automotive sector, as Sandeep mentioned, driverless cars are a prime example of AI in action. These vehicles rely on AI to make critical decisions, such as when to stop to avoid collisions or when to turn. Generative AI powers features like voice commands—e.g., “Hey BMW, play my favorite song”—while edge AI ensures real-time functionality and responsiveness. All these AI applications work together to create an advanced autonomous driving experience. Looking ahead, the next frontier could be flying cars, which would bring even more transformative use cases to the table.
This report highlights a wide range of AI applications across industries like healthcare, automotive, manufacturing, and financial services. The potential for further innovation is enormous, and we can expect many more use cases to emerge in the future.
TAM: Do you think leaders can ignore adoption of AI or GenAI? How will it affect their business according to you?
Sachin Tayal: Generative AI, for example, is still in its infancy within organizations. Approximately 25% of businesses have reported starting to use generative AI. However, many more use cases are either in development or yet to be explored. Companies like SAP, Microsoft, and others are already integrating generative AI into their offerings, such as co-pilots. That said, I don’t believe generative AI has reached a level of hype where it risks a downturn. On the contrary, as more use cases are developed, its utility and impact will only grow.
Currently, generative AI is being leveraged to enhance customer experiences, particularly by improving interactions with clients. Looking ahead, we can expect broader adoption in areas like business planning, demand forecasting, and supply chain management. As large language models and generative AI solutions evolve, these emerging use cases will begin to take shape, further solidifying their role in business operations.
TAM: The DPDP Draft Rules are out, and the law is soon going to be implemented. Do you see this having an impact on GenAI and its potential?
Sachin Tayal: You need brakes in a car so that it can run faster, right? Similarly, the DPDP (Digital Personal Data Protection Act) will instill a sense of caution in organizations or entities handling data. It sends a clear message: if you misuse data, there will be penalties. Just like brakes enable cars to operate safely and efficiently, the DPDP acts as an enabler, addressing critical gaps in data protection.
Think of it like a toll gate. Raw data passes through a process where a “cleansing agent” ensures compliance with DPDP. It cleanses, anonymizes, or tokenizes data according to privacy standards, making it suitable for AI consumption while safeguarding sensitive information. This ensures that data streams no longer contain privacy-related information that could be exposed. In essence, the protective wall created by DPDP will be beneficial overall, enhancing trust and security in data usage.
TAM: What advice would you give to businesses navigating the complexities of AI adoption?
Sachin Tayal: In my view, the adoption of AI has to start from the top. Sadeep made a great point when he spoke about the cloud. Historically, it was the CIOs and CTOs who were primarily concerned with cloud adoption and driving those conversations. However, this approach won’t work for AI. AI must be driven by the business leadership like the CEO, chairman, or managing director. It requires a top-down approach, with leadership at the highest level championing an “AI-first” mindset.
Whenever organizations engage in vision exercises or strategy planning, AI needs to be integrated into every aspect of their operations. This includes processes and touchpoints involving customers, suppliers, and stakeholders.
In summary, my recommendations are twofold:
- Leadership must drive AI adoption from the top.
- Organizations should embrace an “AI-first” approach, ensuring AI is a fundamental consideration in all strategic decisions.
