Inc42, in collaboration with Confluent, recently hosted a panel discussion on how startups and enterprises are leveraging AI-powered insights to drive business growth, bringing together 12 technology leaders from various industries.
The roundtable focused on key trends in data analytics that could impact business dynamics, functions and monetization of data.
Speakers discussed the shift from a human-centric approach to AI-driven insights and the importance of a strategic data roadmap.
Many Indian businesses are now using artificial intelligence (AI) and machine learning (ML) to manage and analyze their data assets, thereby gaining valuable insights for their business success. In fact, big data analytics has become a revolution in industry segments and organizations of all sizes as data-driven decisions lead to timely innovations, greater efficiency, and better customer experiences. When supported by cutting-edge AI/ML tools, these data analytics enable startups and enterprises to develop robust operational frameworks and forward-thinking strategies.
Consider this. According to Confluent’s Data Streaming in APAC: Powering the Future of Business report, almost half of organizations in the Asia-Pacific region (48%) are actively democratizing the use of AI/ML across their operations, with an additional 43% considering doing so. Even more interesting, 77% of startups invest in AI/ML and other advanced technologies to realize their full potential, according to an SAP India-Dun & Bradstreet study. Essentially, harnessing Big Data and the power of AI will result in improved business models and a rapidly evolving industry landscape, optimizing value creation and sustainable growth.
To explore the transformative power of real-time data insights, Inc42, in collaboration with data streaming platform Confluent, recently hosted a panel discussion in Bangalore as part of its ongoing knowledge series titled Executive Boardroom: Harnessing Data for Growth. The first roundtable brought together 12 technology leaders from various industries such as insurance, e-commerce, automotive, software development, artificial intelligence and much more. Their discussions focused on the theme: How startups and enterprises are leveraging AI-powered insights to drive business growth.
Sameer Dhanrajani, Founding Partner of MIRAI Ventures and CEO of 3AI, moderated the session. Among the participants were:
- Subhash Choudhary, Co-founder and CTO, Dukaan
- Harish Rama Rao, Senior Vice President (Product Engineering), Acko
- Vivek Pandey, CTO, Simpl
- Ankur Sharma, Co-Founder and Product Manager, Instamojo
- Chandra Sekhar Reddivari, Technical Architect and Head of AI, Vymo
- Anoop Kumar Mishra, Senior Director (Data & AI), Ace Turtle
- Naveen Budda, co-founder, KarmaLifeAI
- Ananthakrishnan Gopal, Co-Founder and CTO, DaveAI
- Ramakrishna R, Co-Founder and CTO, CureSkin
- Alok Dubey, Chief Architect, Embitel
- Kishore Gopalakrishna, Co-Founder and CEO, StarTree
- Sheshanth Bhambore, Regional Sales Director (Digital Natives), Confluent
Rules-Based Data Analytics and AI-Driven Insights: Why Timeline Matters
During the session, speakers highlighted the critical importance of real-time information and the increasing complexity of managing the information explosion. With the rise of cloud computing, easy access to massive data sets and AI-driven data analytics are taking center stage. However, it is crucial to differentiate between a human-centric and an AI-driven approach to analyzing insights from data and making data-driven decisions.
Alok Dubey of Embitel compared these two solutions to better understand their suitability and benefits. “We mainly see two aspects of data analysis. First, how soon should I want the data to be analyzed? This is the fundamental question. If you are in an e-commerce or fast commerce business, you need to quickly analyze certain data sets/patterns. This is often rule-based analysis (uses a set of rules to classify data into predefined categories). But adding ML tools or AI engines will not add any value,” he explained.
“Then there is another aspect of getting insights into AI/ML. This requires generating larger data sets over a longer period of time and data analysis will take time. If we are willing to put in that time, it will produce something meaningful.
How the Flywheel Effect Drives Business Performance
A well-designed strategic data roadmap – a plan that details how organizations can manage, analyze and execute on real-time data-driven insights – is also essential to achieving business goals. Naturally, this will require resources to build the data infrastructure and an implementation timeline before businesses can optimize the use of data for decision-making on all fronts.
StarTree’s Kishore Gopalakrishna further explained how data could drive business performance and improve consumer experience.
“Take, for example, Uber Eats, DoorDash or Zomato. Their customers choose restaurants based on the data provided (offer, reviews, etc.), while businesses have access to primary user data. But today’s companies have gone further; they want to use the new data sets well. This is where the experience part comes in and your end users start generating more data. Think of data as a flywheel that can influence your customers and generate data so you can create more products and refine them based on the insights the data provides,” he said.
This “flywheel effect” becomes crucial for companies seeking product innovation. It also creates a feedback loop, which results in a better user experience.
Confluent’s Sheshanth Bhambore highlighted another strategic element: converting raw data into coveted products using AI-driven analysis.
“Our mission is to keep this data available to every user, to every data scientist, to every decision maker, so that they know what data is flowing, how much data is flowing (volume), whether the data sets fit and what are the results. will be. We also evaluate our analytics and operations to make things simpler for our customers.
Access to vast consumer data also allows Confluent to extract deeper insights and equip businesses to create products based on the use cases that emerge during the data-to-insights journey.
Emerging Professional Roles Across the Data Analytics Continuum
As AI-GenAI continues to evolve and gain traction across industries, new roles are emerging to replace routine tasks and traditional functions. Experts believe this will transform work as we know it and open up many new opportunities.
Ankur Sharma, co-founder and CPO at Instamojo, is particularly excited about the talent he’s scouting across the data analytics continuum.
“I also think that a new role, probably very specialized, is likely to emerge – the role of a person (I call him the interviewer) who can ask the right questions at the end (to determine value) . Yes, we have very powerful AI assistants and lots of data at our fingertips. But unless we know how to ask the right questions, pointed and insightful queries, we will find ourselves in a classic case of “trash within trash”. The value of data will always depend on the questions we ask.
He said the emerging talent pool is evolving in sync with rapid technological developments. But other new roles will emerge, including those like the “interviewer,” who can ask GenAI the right kinds of questions.
Overcoming Data Analysis Challenges
As businesses increasingly embark on a complex journey, the challenges are numerous. Naveen Budda of KarmaLifeAI mentioned the challenges one would face in monetizing data. While data remains a critical asset and a powerful engine of growth, harnessing its value in all its aspects can contribute to a company’s bottom line.
Instamojo’s Sharma also cited poor documentation as a major obstacle. According to him, the sheer volume of data generated is difficult to manage and segregate based on metadata.
Despite these challenges, the benefits of data processing, analytics and insights are clear. Startups and businesses across the country have integrated AI-driven data analytics into their core strategies for growth-driven decision-making and long-term success. It is perhaps the most consistent way to quickly capture market trends, changes in consumer behavior, technological developments and all other challenges that hinder business growth.
