From Rule-Based Systems to Transformers: The Rise of Modern AI

AI has been around for decades, evolving through different stages of growth and maturity. The timeline info graphic shows this progression, from early rule-based systems to today’s generative AI. While development has been steady over time, the pace of change has accelerated dramatically over the past 7 to 8 years.

In many ways, the modern AI industry is only about five years old. That shift was driven by the Transformer model, which enabled AI systems to scale and move beyond research into real-world, industrial use.

We’ve seen this kind of rapid growth before.

Ecommerce in India began to take shape around 2013–14 with the entry of Amazon, Flipkart, and a handful of others. What followed was fast and transformative. In less than five years, these platforms scaled into retail giants and changed how businesses marketed, sold, and understood their customers.

They introduced data-driven marketing at scale. Performance advertising became mainstream. Content adapted to shrinking attention spans. For the first time, brands had access to deep, real-time insights into customer behavior across the funnel.

AI is now at a similar inflection point.

Chatbots and generative AI are beginning to reshape search, discovery, and performance marketing in much the same way ecommerce reshaped retail. Search is becoming conversational. Content creation is accelerating. Personalization is moving from segments to individuals. And feedback loops are getting shorter and smarter.

Ecommerce took roughly five years to mature in terms of scale, adoption, and social impact. AI may not take that long. The pace of development, deployment, and adoption suggests this cycle could be significantly shorter.

If ecommerce taught us anything, it’s this: when technology unlocks scale, data, and usability at the same time, entire industries change faster than expected.