The big idea 

As AI continues to reshape the research industry, the greatest risk isn’t failure. It’s standing still. According to Pravin Shekar, successful innovation requires experimentation, adaptability, and a willingness to openly discuss setbacks. The future belongs to organizations and individuals who embrace continuous learning, remain curious, and view failure as a critical part of progress. 

Key themes 

The Value of Saying “I Don’t Know” 

In an AI-powered world, information is increasingly accessible, but knowledge and understanding remain distinct. 

• AI can provide answers, but it cannot replace critical thinking. 
• Leaders must understand the limits of what they know. 
• Admitting uncertainty can build trust and credibility. 
• Human judgment remains essential, even as AI becomes more capable. 

Why Failure Drives Innovation 

Pravin believes experimentation inevitably involves setbacks. 

• Early efforts in synthetic data and digital twins struggled because the market was not yet ready. 
• Some promising AI initiatives became obsolete almost overnight due to the pace of technology development. 
• Innovation requires fast iteration rather than fear of failure. 
• Every unsuccessful experiment provides valuable learning for the next one.  

Creating an Industry That Learns from Mistakes 

The insights industry often celebrates successes while overlooking failures. 

• Open conversations about failure can accelerate learning across the sector. 
• Organizations should create safe spaces for experimentation. 
• Sharing lessons learned helps others avoid repeating mistakes. 
• Failure is often the foundation of future success.  

AI Is Another Wave of Change, Not the End of Research 

Every major innovation creates uncertainty. 

• Similar concerns emerged during the rise of online research and big data. 
• AI is prompting anxiety across parts of the industry today. 
• Adaptation has always been part of the research profession. 
• Businesses that remain agile are more likely to find opportunities than threats. 

New Opportunities Emerging in India 

Pravin highlights the rapid growth of direct-to-consumer (D2C) businesses across India. 

• D2C brands are creating entirely new audiences for insights and research. 
• These businesses often have direct access to consumer data. 
• AI and research can help unlock greater value from that information. 
• New sectors and business models create opportunities for innovation-focused researchers.  

Understanding Gen Z Beyond the Stereotypes 

Pravin challenges common assumptions about younger generations. 

• Gen Z should not be viewed as a single, uniform group. 
• Some embrace AI enthusiastically, while others remain cautious. 
• The research industry must adapt to changing work preferences and expectations. 
• Understanding how new generations think and work is essential for future growth. 

The future of experimentation in research 

According to Pravin, the future belongs to those willing to explore new ideas while remaining grounded in human understanding. 

Future success will require: 

• A willingness to experiment continuously. 
• Faster iteration and learning cycles. 
• Human-cantered thinking alongside technological innovation. 
• Greater openness about failures and lessons learned. 
• Adaptability in response to rapid change.  

The Dynata lens 

The conversation reinforces an important principle for the insights industry: innovation is not just about technology. It is about how organizations adopt, test, refine, and scale new ideas. High-quality data, human expertise, and a culture of experimentation remain critical ingredients for success in an AI-driven future.  

Final takeaway 

AI may be transforming research, but curiosity, adaptability, and human judgment remain at the heart of the profession. As Pravin Shekar explains, the organizations that thrive will be those willing to experiment, learn from failure, and continuously evolve alongside the technologies shaping the future.