Decoding GenAI: The Next Revolution in Consumer Experiences in India

The buzz around Generative AI (GenAI) predominantly highlights breakthroughs in Large Language Models (LLMs), but we’re yet to see significant advancements at the application layer in consumer apps.

This piece shifts focus from foundational models to the transformative potential of GenAI in consumer applications, emphasizing how it can both accelerate existing consumer behaviors and foster new ones by mainstreaming interactions with machines in our native language.

The reality behind the hype

While GenAI has sparked considerable excitement, especially with applications like ChatGPT, Character.AI, and Replika.AI, a significant disparity exists between the hype and real-world usage.

Ultimately, GenAI is a tool, and its value is realized through thoughtful, contextual implementation. A spate of GenAI-first consumer startups from Y Combinator show promise, yet the Indian market, with its unique economic conditions and consumer behaviors, presents distinct challenges and demands innovative incubation models.

Rethinking GenAI Through Consumer Behavior

The future of consumer GenAI is multimodal, agentic and will include intelligent interfaces.

Traditional segmentation of GenAI applications often focuses on function or sector. In contrast, I’ve put together a behavior-centric framework to squarely focus on how this technology is and will shape consumer behavior.

• Companionship: In an era where human reliability wavers, the potential for AI companions that exist continuously in users’ digital lives, remember past interactions and evolve based on user interactions hold strong promise. The film “Her” offers a glimpse into future possibilities where digital entities become more than tools. The idea of digital companionship is becoming more tangible through startups like Hume and Wysa. Hume is innovating in emotional AI, understanding and interacting with human emotions, while Wysa, a company in our portfolio, is focusing on mental health companionship. Furthermore, applications like Astrotalk are tapping into cultural niches, providing digital companionship through astrology, which is particularly resonant in India.
• Creative and Intellectual Partnership: Beyond companionship, there’s a vast landscape where AI can enhance human capabilities, especially in creative and intellectual endeavors. This partnership could redefine roles in various professional fields, including education, healthcare, and legal, where AI doesn’t replace but augments human efforts, by acting as a personal assistant to enhance learning and decision-making, offering tailored advice or recommendations based on individual user data. For example, AI-driven platforms like Jasper aid in content creation, while RunwayML facilitates automated video editing. In education, AI tutors that provide personalized learning experiences through platforms like Supernova, which focuses on English language learning are making significant inroads. In healthcare, platforms like Babylon Health are pioneering AI-driven medical consultations and AI-driven wellness apps are providing personalized health recommendations, mental health coaching, and fitness training, adapting to the user’s progress and changing needs.
• Interaction & Immersion: As we venture deeper into digital realms, the demand for immersive experiences grows. This involves AI systems that create or modify content in real time to increase user engagement. Examples include video games that adapt to the player’s skill level, studios building infinite games and increasingly immersive worlds, agentic players or interactive learning platforms that adjust content based on the user’s retention and understanding. Social networks that focus on AI friends and AI influencers are already mushrooming. The next generation of breakout social networks and gaming platforms will likely be AI-first. Immersive learning and personal robotic assistants are other nascent use cases.
• Personalisation: While heavily emphasized as a use-case, personalization isn’t new. We’ve experienced tailored digital interactions for years. The real question is how GenAI can enhance this beyond current offerings to create truly individualized experiences without infringing on privacy. Beyond the familiar terrain of personalized recommendations seen in platforms like Netflix or Spotify, in retail and e-commerce, GenAI can drive sophisticated recommendation engines that predict what products consumers might like, not just based on past purchases but also through analysis of similar user behaviors and preferences. This extends to services like The Yes and Stitch Fix, which personalize clothing items for consumers.
• Discovery: GenAI can revolutionize how consumers find information, moving beyond traditional search engines to more intuitive, conversational interfaces that understand context and nuance, such as Perplexity.

A Matrix to Navigate GenAI Applications

To further explore the implications of GenAI in consumer technology, I’ve put together a matrix to categorize GenAI applications based on their impact on consumers and the degree of autonomy retained by users:

• High Autonomy, High Influence: Applications like AI-driven health advisory systems empower users with significant insights yet leave the final decisions to them.
• High Autonomy, Low Influence: Technologies such as autonomous vehicles take over critical decision-making, requiring high trust from users.
• Low Autonomy, High Influence: Platforms like Netflix enhance daily leisure with minimal risk, suggesting entertainment options.
• Low Autonomy, Low Influence: Tools like smart thermostats autonomously manage routine tasks, optimizing comfort without direct user interaction.

This matrix can help identify how much trust and control users are likely to expect from different types of applications and can guide user interface design, marketing strategies, and feature development. Understanding the balance between autonomy and decision influence also assists in predicting user acceptance and satisfaction, crucial for successful product adoption and long-term engagement.

The Indian Perspective

India’s developmental trajectory in technology mirrors early trends seen in the U.S. but is poised to forge its own path due to its unique socio-economic and cultural landscapes as the economy matures. Factors like trust, family dynamics, generational gaps, and varying behaviors across different city tiers necessitate a tailored approach to GenAI applications.

• Cultural Relevance: Any GenAI solution in India must resonate with local values, traditions, and social norms, acknowledging the shift towards nuclear families and the rise of Gen Z.
• Economic Diversity: Designing GenAI applications that cater to India’s diverse economic segments — from affluent urban consumers to the emerging middle class in smaller cities — is crucial.
• Technological Integration: As digital adoption accelerates, GenAI solutions must be seamlessly integrated into everyday lives, enhancing rather than complicating the user experience

The fusion of AI with vernacular content and multimodal interactions also presents a lot of room for innovation. This evolution is likely to lead to AI becoming a seamless part of daily consumer interactions, evident from the rising engagement in sectors like companionship and productivity, where AI is not just a tool but a companion.

Astrology and faith-based companions, AI matchmakers for arranged marriages could be particularly interesting.

Conclusion

The Indian market presents a fertile ground for deploying GenAI solutions that are globally scalable yet locally adaptable. Ensuring that AI applications are designed with a deep understanding of the user’s behavior, preferences, and needs is paramount.

Challenges such as privacy concerns, the hype surrounding AI capabilities versus their practical impact, and the sustainability of engagement metrics need to be actively managed, but the journey of GenAI in the consumer sector is just beginning, especially in a diverse and complex market like India.

By understanding and innovating according to specific consumer behaviors and needs, there is a monumental opportunity to lead a new wave of technological advancement that is deeply integrated into the fabric of everyday life.

Stay tuned for part II of this series.