Generative Interactive AI as a New Cognitive Episteme in Web Research

Abstract

The rise of generative interactive artificial intelligence (GIAI) is radically reshaping how individuals access, process, and validate online information. This article explores the ongoing transition from indexed keyword-based search (e.g., Google Search) to dialogic, contextual, and iterative inquiry, embodied by tools such as Copilot, ChatGPT, Claude, and Perplexity. Through comparative analysis, trend data, epistemological reflection, and an extended bibliography of over 100 academic and institutional sources, we offer a critical map of the emerging cognitive digital ecosystem.

1. Introduction: The End of Search as Navigation

“We are no longer searching for information. We are conversing with knowledge.” — Maria Silvano, Matrice Digitale, 2025

For over two decades, Google has dominated digital knowledge access. Its algorithmic architecture shaped not only how we search, but how we think. Today, the emergence of generative interactive AI (GIAI) — powered by large language models (LLMs) — is redefining the very concept of “search.” This is not merely a technological evolution, but an epistemological shift: from linear retrieval to dialogic construction.

2. Trend Data: The Rise of Generative AI in Web Research

“ChatGPT is now a household name in Italy: in April 2025, it reached 11 million unique users.” — ComScore, cited in La Repubblica, 2025

• Over 41 million users in Europe engage with ChatGPT Search monthly.

• In Italy, generative AI usage grew by 65% in the first four months of 2025.

• According to InfoData – Il Sole 24 Ore, “AI Mode is the most radical transformation of Google Search since its inception.”

• Adobe Research reports a 1200% increase in traffic from generative AI sources between July 2024 and February 2025.

3. Google AI Overviews vs. Generative Interactive AI: Two Divergent Models

“Google remains dominant, but its supremacy is now challenged by a new way of conceiving search: conversation.” — HDblog, 2025

3.1. Google AI Overviews

• Static synthesis of web sources

• Powered by Gemini 2.5 models

• Non-adaptive, non-interactive responses

“AI Overviews is a cognitive shortcut, not a dialogue.” — Key-One, 2025

3.2. Generative Interactive AI (Copilot, ChatGPT, Claude)

• Iterative, contextual dialogue

• Semantic personalization

• Direct, verifiable citations

“ChatGPT Search and Google AI Overview represent two divergent models: one synthesizes, the other converses.” — Matrice Digitale, 2025

3.3. Comparative Table

4. Cognitive and Epistemological Impacts

“Generative AI use may reduce our critical thinking capacity.” — Microsoft & Carnegie Mellon University, 2025

4.1. Cognitive Benefits

• Reduced cognitive load

• Enhanced working memory

• Simplified access to complex sources

4.2. Epistemic Risks

• Dependence on synthetic answers

• Erosion of evaluative judgment

• Risk of “delegated epistemology”

“Generative AI is profoundly transforming how we learn, work, and communicate.” — University of Bologna, 2025

5. Toward a New Digital Epistemology

“It’s not just Google being questioned, but an entire way of conceiving online research.” — Umanesimo Digitale, 2025

5.1. From Navigation to Understanding

• Users no longer seek links, but meaning

• Answers become nodes in a dialogue, not endpoints

5.2. AI as a Cognitive Co-Agent

• AI is not merely a tool, but a partner in epistemic construction

• A new form of distributed intelligence emerges

6. Future Perspectives: SXO, Convergence, and Authority Models

“SEO is dead. Welcome to SXO: Search Experience Optimization.” — Adobe Research, 2025

• Generative AI redefines authority and relevance

• User experience becomes central

• Search engines evolve into cognitive assistants

7. Conclusion: Toward Responsible and Critical Research

“Yes, we can use generative AI for research — but only by respecting certain principles.” — European Commission, 2025

The challenge is not only technological, but cultural. A new epistemic literacy is needed — one that integrates generative AI as a critical tool, not an oracle. For the scientific community, this entails:

• Training in AI interaction

• Source validation

• Monitoring cognitive effects

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