What popular AI chatbots copied from ChatGPT: key features and strategies that now define artificial intelligence

The centrality of the text-based conversational interface as the paradigm for interaction with generative AI.

ChatGPT established a form of interaction based on a continuous text chat, where every request and every response are elements of a thread that remains available and editable over time, with a “history” that can be consulted at will. Before ChatGPT, tools like Google Assistant or Alexa provided single responses, without retaining or displaying conversations. After the success of ChatGPT, practically all other AIs (Claude, Gemini, Grok, Meta AI) adopted the continuous thread chat metaphor: even subsequent questions are contextual, the history is saved, responses are organized in separate chat windows, often with the ability to name, pin, or export each conversation. This shifted the focus from one-off use to persistent dialogue, making the AI something to “talk to” and not just “ask”.

OpenAI’s intuition was to turn an advanced language model into a true “conversation companion”, where the user can revisit previous interactions, correct, deepen, and resume a discussion even after days, as if it were a chat with a real person. This sense of “presence” and “continuity” radically changed public expectations, so that today AIs are no longer perceived as mere single-command tools, but as digital entities with which to establish complex dialogues, leading to the introduction of thematic threads, automatic saves, chronological filters, and advanced conversation management across all competing platforms.

The approach to prompts: from rigid commands to natural language dialogue, the ChatGPT effect

One of the most significant revolutions brought by ChatGPT, and immediately adopted by all major competitors, is the shift from input based on rigid commands or keywords to the possibility of expressing prompts in natural, conversational language. While early chatbots required users to phrase their requests in a specific way—often relying on lists, code-like syntax, or minimal phrases—ChatGPT established the paradigm that you can interact with AI as if you were talking to a person, using long sentences, follow-ups, and even imprecise or ambiguous language. This approach lowered the barrier to entry for millions of users and pushed other AI providers to quickly reengineer their input systems. Claude, Gemini, Grok, and Meta AI have since all optimized their models to understand prompts in varied and natural forms, allowing for greater flexibility, fewer misunderstandings, and a much more intuitive experience, especially for non-technical users.

The shaping of answers: from short facts to detailed, structured responses that simulate real conversations

ChatGPT also radically transformed the way AI answers are generated and presented... Instead of delivering only dry facts, bullet points, or minimal feedback, the model began to offer responses that are rich in explanations, context, examples, and even reasoning behind certain suggestions. The tone adopted is friendly, attentive, and calibrated to the user’s style, sometimes even offering clarifying questions or anticipating follow-up needs. This “human-like” way of responding has now become the gold standard: competitors like Claude and Gemini have followed suit by enriching their output, moving from simple answers to articulated explanations, step-by-step guides, and even multiple options for the user to choose from. This evolution has made interactions with AI more useful, educational, and engaging, raising the expectations of users across the entire sector.

The concept of a limited free version alongside a Plus plan with access to the most advanced models.

When OpenAI launched ChatGPT Plus, offering priority access, better models, and additional features, it created a business model that is now the industry standard. Claude imitated this setup, offering the basic Sonnet model for free and leaving Opus (the more advanced one) as paid-only; Gemini created a free version with the Flash model and a “Pro” (2.5) reserved for subscribers; Grok is included as a plus in X’s premium package. This has also changed user expectations: today, everyone expects to be able to try a base for free and pay for the maximum. The “freemium” structure is now the norm for AIs, and differentiation by model and capabilities (context, upload, memory) has become a standard practice virtually everywhere.

The commercial architecture inaugurated by OpenAI, which sharply distinguishes between what is free and what is reserved for subscribers, has redefined the perception of value in the AI world: access to the most powerful models, processing of the most complex files, or multimodal capabilities are now seen as a “privilege” tied to a subscription, while the basic offer serves as a showcase to attract millions of users and then convert them to paid services. This subdivision, systematically adopted by competitors, has generated a race for exclusivity in the most advanced features (longer token context, voice processing, dedicated APIs, usage priority), creating real premium ecosystems that drive commercial innovation as much as technological innovation.

The friendly, neutral, but in-depth tone: balancing accessibility and authority.

One of the most copied elements of ChatGPT is its ability to be understandable but never excessively simplistic, always courteous but never too informal, with a tone suitable for both technical questions and everyday queries. Before ChatGPT, many AIs were perceived as robotic or too dry (think of Google and Amazon assistants), or excessively formal and not “human” enough. Claude, Meta AI, and Gemini had to reinvent their linguistic register, emulating the naturalness, empathy, and clarity of ChatGPT. The result is that almost all assistants now use “human” responses, elaborate explanations, and sentence structures that recall real conversations, with a depth of reasoning that reflects the OpenAI model.

The effect of this stylistic transformation is especially evident in responses to complex or delicate questions, where rival AIs have adopted discursive techniques—such as the use of practical examples, transparent disclaimers, and personalized suggestions—that were previously the prerogative of ChatGPT. Today, every major chatbot strives to “reassure” the user by offering verbose and detailed explanations, alternating clarity with invitations to continue the conversation, maintaining a subtle balance between formality and immediacy, always with the aim of being accessible to all user levels while at the same time conveying competence and analytical depth.

The introduction of voice mode, with spoken input and natural responses, as part of the user experience.

The transition from text-only chat to the ability to interact via voice was accelerated by ChatGPT, which integrated voice input and output (via Whisper and TTS models). This move led Claude, Gemini, and Meta AI to develop similar functions, announcing gradual rollouts of voice modes. Today, voice is no longer seen as a marginal addition but as a fundamental component, especially on mobile. Gemini on Android integrates into the Home screen as a true “voice AI assistant”, Meta AI is testing audio in Facebook Messenger and Instagram, and Claude announces its own voice AI as “coming soon”. The goal is to create the most natural experiences possible, exploiting the continuity between spoken and written language that OpenAI made current.

This rush toward voice interaction is not only about dictation or reading responses but extends toward the simulation of a fluid dialogue, with expressive intonation and the ability to understand complex commands and ambiguous contexts typical of human conversation. Rival companies have rushed to improve their voice recognition pipelines, the quality of synthetic voices, and the management of emotions in speech, aiming for experiences increasingly indistinguishable from those of a human assistant. This is bringing AI to new use cases: from home automation to voice messaging, from customer support to assistance for the disabled, radically redefining the concept of “user interface” thanks to ChatGPT’s example.

The extension to multimodal vision and reading of images, tables, files, and charts within the chat.

ChatGPT popularized the idea that an AI should be able to see, analyze, and discuss not only text but also images, PDFs, screenshots, tabular data, and charts. The integration of Vision with GPT-4o radically changed expectations: today, Claude 4 allows PDF, image, and Excel table uploads (up to 200,000 tokens), Gemini allows the upload of images and screenshots (even if the parsing of long documents is not yet at ChatGPT’s level), and Meta AI supports images and visual search. The possibility of receiving responses “on the content” of a document led other AIs to accelerate the integration of multimodal modules, sometimes with higher limits than the early OpenAI models, but always chasing ChatGPT’s user experience.

This evolution has not only broadened the possibilities of use, but also given rise to new use cases and greater expectations from users, who now take it for granted that their AI should be able to read a PDF, understand a formula in an image, recognize a chart, or analyze an Excel table, saving time on previously manual and often laborious tasks. The leap toward multimodality forced other players not only to update their core models, but also to develop suitable graphic interfaces, annotation tools, and more flexible workflows, redefining the boundaries of what is expected from a “modern” AI platform.

The integration with external tools (such as Office, Drive, APIs) was pushed by ChatGPT and then replicated.

The “AI that also does other things”—that is, an assistant capable of managing files, writing code, generating images, browsing the internet, accessing cloud documents—became a reality with ChatGPT, with its plugins, code interpreter, integrated DALL·E, and native browser. After these developments:

• Gemini was integrated into Google Workspace products (Docs, Sheets, Gmail).

• Claude integrated business apps such as Notion, Slack, and API systems.

• Grok still has limited functions but is aiming for integration with X/Tesla products. This “race to the super-app” was accelerated by the pressure from ChatGPT, which set a new level of expectations: today, anyone offering a chatbot must also offer integrated tools and complete workflows.

This race to integrate with external tools has raised the level of interoperability required of AI assistants, leading to a revolution both in the needs of professional users—who now demand direct access to spreadsheets, presentations, reports, and databases—and in those of consumers, who ask for automation across their apps and personal devices. The domino effect has forced every player to build more advanced partnerships and APIs, creating an ecosystem of increasingly interconnected services, where AI acts as the central node and privileged point of access to digital resources and tools.

The choice of avatar, design, tone of voice, and branding reminiscent of ChatGPT’s sober and professional style.

Minimalist design and a “text first” approach have become the rule after ChatGPT’s success. The essential interface, with readable fonts, neutral colors, and no unnecessary decorations, has been adopted almost identically by Gemini, Claude, and Meta AI. The “serious” branding (abstract logo, sober tones, absence of mascots) has been adopted everywhere, precisely to convey reliability and universality. Even in marketing, the visual narrative has changed: today, “cartoonish futurism” is avoided, and the focus is on conveying seriousness and authority, with light palettes and a central logo.

ChatGPT’s influence is also evident in the choices of microcopy, button texts, chat titles, and terminology for functions and options, always aimed at clarity and reducing the superfluous. This visual and conceptual minimalism, designed to inspire trust and professionalism, has become the dominant model, relegating to the margins any style that is too playful, colorful, or decorative, and creating a new aesthetic for conversational technology, now recognizable throughout the sector.

The adoption of conversational memory (history, preferences, projects) following ChatGPT’s example.

The ability to save history, retrieve old conversations, set preferences, and manage “projects” or “folders” was systematically introduced by ChatGPT, which developed a system for storing chats and personal preferences. Claude and Gemini had to adapt: today, Claude offers session memory and the ability to reopen files and threads, Gemini maintains persistent threads, even if it does not yet offer the same granularity in saving and retrieving. This allows for a continuity of use that was previously unknown and has shifted the user experience from a “single prompt” to a “long-term relationship” with AI.

The conversational memory model introduced by ChatGPT has paved the way for the evolution of AIs from passive tools to true “digital companions”, capable of remembering preferences, goals, notes, and even recurring trends in conversations. Competing companies are trying to close the gap with new features for personalized saving, projects, and thematic histories, which help users reconstruct complex processes and workflows over time, contributing to a more personal and rooted usage relationship.

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