In the 1950s, Alan Turing - the father of theoretical computing - asked a simple question: “Can machines think?” At the time, it was largely a philosophical provocation. Today, it has become a practical reality, shaping how farmers grow crops, how health workers learn and how courts function.
To truly understand the scope of artificial intelligence, it helps to understand intelligence itself. Intelligence evolves in stages - from learning (absorbing patterns), to understanding (making sense of those patterns), to reasoning (using that understanding to make decisions) and finally to creativity (combining ideas to generate something new and useful).
Today, AI has crossed into this fourth stage. Machines no longer just read or classify. They can now generate language, images, music, insights and decisions. This single shift changes the scale at which systems can operate.
Imagine a small farmer in rural Maharashtra. He notices his cotton leaves turning yellow after unseasonal rain. He speaks into his phone in Marathi. AI converts his voice into text and intent, pulls his context - crop type, location, soil conditions - and processes it against vast agronomy and weather databases. Within moments, he receives clear guidance in his own language on what might be happening and what action to take. In under a minute, years of research, advisories and real-time data are compressed into a practical decision on a farm.
The true power of AI today lies in personalisation and optimisation.
The same pattern is repeating across the social sector. Newborns are being screened for health risks using just a smartphone video through Shishu Maapan by Wadhwani AI. Frontline health workers are learning and receiving personalised refresher training through WhatsApp using Mobile Academy by ARMMAN. Court proceedings are being transcribed and digitised in real time by Adalat AI. Children are learning at their own pace through adaptive platforms like AXL by EkStep Foundation. Train delays are being predicted in advance using network-wide data by IRCTC. These are not futuristic ideas - they are live systems already operating at scale.
And AI works in 2 ways. Backend AI strengthens organisations by processing data, detecting fraud, predicting risk and optimising resources. Frontend AI strengthens individuals through chatbots, voice assistants, learning companions, health advisors, and translation tools. Real transformation happens when both evolve together.
For adoption to increase it is crucial to align tech with user behaviour. If an AI tool does not reflect how people actually think, decide, speak, hesitate and trust, adoption will always remain shallow. The future of AI here will be shaped not only by engineers, but also by designers who deeply understand users.
Grateful to Mentor Together for the opportunity to engage with such curious, reflective minds at the Mentor Summit. Conversations like these give me real optimism about where this journey is headed.