Francisco - Tulxy.com

Today, many purchasing decisions no longer start on Google.
They start with a question to an AI.

When users ask which brand to choose, which company is more reliable, or which product or service is the best option, AI doesn’t return endless lists of links. It answers. It summarizes, compares, and recommends — before any click happens.

What makes this shift truly significant is not just the technology itself, but the speed at which users are adopting it. The data shows rapid, large-scale adoption and growing trust in AI as a decision-making assistant. And that is precisely why, when AI decides before the click, brand reputation is no longer shaped only in search results, but in how AI understands and talks about your brand.

1. Scale and adoption of AI assistants

Global usage

ChatGPT exceeds 700 million weekly active users
(reported by OpenAI, 2025)
More than 2.5 billion prompts are sent to ChatGPT every day
(approximately 330 million from the United States)
The free version accounts for the majority of usage, indicating mass adoption beyond purely professional or enterprise use.

Web traffic

chatgpt.com is the 4th most visited website globally
Approximately 5.6 billion monthly visits
Average session duration: 12 minutes 41 seconds
Bounce rate: ~39%

(Sources: aggregated web analytics data, 2025)

2. AI as a functional replacement for search engines

Shift in user behavior

According to consumer research:

56% of users describe AI as their primary source of information, functionally equivalent to a search engine.
58% of consumers have already replaced traditional search engines with generative AI for product and service recommendations
(up from 25% in 2023).

Source: Capgemini Research Institute, 2025

3. Direct influence on purchasing decisions

Recommendations and conversion

53% of consumers have already made a purchase based on AI recommendations
64% are willing to buy products recommended by AI
71% want AI to be integrated into their shopping experiences
92% say AI improves their overall shopping experience
87% trust AI for complex or higher-value purchases

Source: Capgemini Research Institute + sector surveys (2024–2025)

4. Traffic generated by AI to brands and commerce

Growth of the AI channel

Digital analytics data shows that traffic from AI tools to ecommerce and service websites has grown dramatically:

+1,300% during the 2024 holiday shopping season
+1,200% in February 2025 compared to July 2024
The channel’s growth rate is doubling approximately every two months

Source: Adobe Inc. Analytics, 2025

5. Quality of AI-generated traffic

Compared to other digital channels, traffic coming from AI shows:

+8% longer time spent on site
+12% more pages per visit
–23% lower bounce rate

However:

Direct conversion is still ~9% lower than other channels
This gap has narrowed significantly (down from –43% just months earlier)

Conclusion:
AI is primarily used during research and decision-making phases, not only for impulsive purchases.

Source: Adobe Analytics

6. AI as a primary information channel

Stated user preference

According to strategic research:

44% of AI search users consider AI their main source of information, outperforming:
- Traditional search engines (31%)
- Brand websites (9%)
- Review sites (6%)

Source: McKinsey & Company, AI Discovery Survey 2025

7. Expected impact on traffic and revenue

Medium-term projections

Between 20% and 50% of traditional search traffic is at risk
if brands fail to adapt to AI-driven search and recommendations.
By 2028:
- Approximately $750 billion in revenue could flow through AI-powered search and recommendation experiences.

Source: McKinsey, 2025

Brand reputation is no longer shaped by what companies say about themselves—it’s defined by what AI systems tell millions of users every day. Generative Reputation explains how AI models form opinions about brands and why managing this invisible influence has become a critical business priority.

The new frontier of Brand Reputation in the AI era

Perfecto, aquí va la adaptación de ese bloque completo. Voy a ajustar estructura y punch para el mercado internacional:

Generative Reputation defines this emerging field: the collection of opinions, descriptions, comparisons, and recommendations that AI systems generate about a brand—often before a potential customer ever visits your website or reads a review. In this landscape, reputation is no longer built solely through human interactions; it’s synthesized within language models.

Large language models have evolved far beyond answering generic questions. Today, they summarize brands, compare competitors, make recommendations, explain value propositions, and form opinions about companies billions of times per day.

Search behavior has fundamentally shifted. Users no longer type “best X” into Google and click through results. Instead, they ask AI assistants like ChatGPT, Claude, or Gemini directly. When this happens, the model doesn’t crawl your website in real-time—it retrieves the perception it has already formed about your brand from the knowledge it absorbed during training and through retrieval-augmented generation.

If you don’t know what that perception is, you’re operating blind. And if you’re not actively shaping it, someone else is doing it for you—competitors, critics, or outdated information. This is why Generative Reputation matters now: AI-generated reputation is becoming your primary reputation.

What is Generative Reputation?

Generative Reputation is the perception AI systems construct about a brand when they describe it, compare it against competitors, or recommend it to users. It doesn’t depend solely on what a company publishes on its website—it’s shaped by how AI models interpret signals distributed across multiple sources, contexts, and narratives.

In the AI era, reputation is no longer created exclusively through customers, media coverage, or market dynamics. It’s also forged inside language models themselves, which synthesize information, identify patterns, and generate judgments that directly influence purchasing decisions and brand perception.

Why you can’t ignore Generative Reputation anymore

AI is no longer a future trend—it’s the primary intermediary between people and information. More decisions are now made based on AI-generated responses that summarize and recommend options without ever showing a list of links.

When a user asks about a brand, the model doesn’t “search” Google in real-time: it remembers. It recalls the dominant narrative, associated attributes, implicit comparisons, and facts it has accepted as valid during training and through its knowledge base.

If a brand doesn’t understand how it’s being represented inside these systems, it loses the ability to influence perception. If it doesn’t actively manage its Generative Reputation, that space gets filled by competitors, assumptions, or incomplete information—none of which the brand controls.

Introducing GRO: Generative Reputation Optimization

GRO is the discipline that explains how artificial intelligence forms opinions about brands—and how those opinions can be understood, measured, influenced, and improved.

GRO provides a common framework for understanding how AI models interpret a brand’s identity, how they decide what to say about it, how they compare it against alternatives, and how these opinions propagate across different AI systems, ultimately influencing real customer decisions.

GRO is not a tool, a proprietary technique, or a closed methodology. It’s an open field of knowledge and a new way of thinking about brand reputation in a world where perception is constructed before people consciously form their own opinions.

At its core lies one fundamental premise: every brand today has an AI-generated reputation, and that reputation can be optimized.

The Framework GRO®

The GRO® Framework is the structure that enables brands to analyze, understand, and optimize the opinions AI forms about them. It organizes Generative Reputation into five key dimensions, each representing a distinct way AI models interpret, describe, and compare brands.

Generative Visibility measures how frequently AI mentions a brand across different queries. Generative Positioning analyzes how AI frames the brand and situates it within its category. Factual Precision evaluates the accuracy of data, facts, and distinctions when AI discusses the brand. Brand Attributes capture the qualities, strengths, and weaknesses models associate with it. And Contextual Consistency examines how that perception holds across different models, prompts, and contexts.

Together, these dimensions reveal how a brand exists inside language models—and where real optimization opportunities lie.

The five hidden forces shaping your Generative Reputation

Even when a brand does nothing, AI systems are constantly forming opinions about it. They do so through mechanisms invisible to most companies.

Spontaneous attributes emerge when AI generates subjective claims based on patterns—like “good value for money,” “innovative brand,” or “somewhat slow service”—even without explicit data. Implicit comparisons appear when models automatically position a brand against competitors, even when no one asked for a comparison. Synthetic facts occur when information is incomplete, ambiguous, or outdated, and AI fills the gaps with assumptions users rarely question.

Adding to this are industry narratives—inherited beliefs about sectors and categories that models project directly onto brands—and external signals from reviews, Wikipedia, press coverage, forums, and third-party sites, which often influence AI perception more than a company’s own corporate website.

These mechanisms operate continuously, shaping AI’s opinion of a brand whether it’s managed or not. GRO makes them visible, measurable, and optimizable.

The future of Reputation is already Generative

Competition no longer happens solely in rankings, ads, or brand awareness. It happens in the invisible space where AI decides which brands deserve to be mentioned, compared, or recommended.

Understanding and managing Generative Reputation isn’t an advanced option or a theoretical concept. It’s the new baseline for any brand that wants to remain relevant in a world where AI mediates perception before people make decisions.