Forecasting the Great Migration: How RAG Engines Could Capture 25% of the ‘Search’ Market by 2027

Author(s): R. Thompson (PhD)

Originally published on Towards AI.

Every keystroke on Google was once seen as a small tribute to an unassailable empire. Billions entrusted a single platform to connect them with the world’s knowledge. But today, the ground is shifting beneath our feet. A slow yet unstoppable migration is underway — from searching to conversing, from clicking to trusting.

Perplexity AI, powered by Retrieval-Augmented Generation (RAG), is rapidly accelerating this shift. What if we could scientifically predict not just the magnitude but the trajectory of this disruption?

Today, we approach it through the rigorous lens of data science and predictive modeling.

“When information retrieval becomes predictive and contextual, control over knowledge reshapes civilization itself.”

Before embarking on forecasting, we must structure the disruption as a formal, analyzable system:

Primary Variables:

• Adoption Rate of RAG Engines: How fast users migrate to conversational search.

• User Behavior Metrics: Engagement levels among Gen Z, Millennials, and older demographics.

• Content Ecosystem Shift: From SEO-optimized web to citation-first, context-driven systems.

• Regulatory Environment: Impact of antitrust rulings, privacy laws like GDPR, and platform governance models.

• Technological Progress: Improvements in hallucination minimization, latency reduction, and real-time adaptability.

These factors are deeply interconnected, necessitating a multivariate nonlinear approach.

Understanding these variables is the first step to accurately project the coming tectonic realignment.

• Search… Read the full blog for free on Medium.

Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor.

Published via Towards AI