AI User Experience Will Get Way Better, as Did Internet Experiences

One suspects the user experience of artificial intelligence will change as much as did our experience of internet apps: basic functionality that over time gets really sophisticated.

AI Evolution (Next 2 Yrs)	Internet Evolution (Past 20 Yrs)	Key Functional Change
Tools → Companions	Web 1.0 → Web 2.0 (Read-Only to Social)	Focus shifted from delivering documents to enabling user-generated content (UGC) and two-way interaction.
Assistants → Agents	CGI Scripts → AJAX/SPA	Functionality moved from server-side, full-page reloads to client-side, asynchronous data processing, creating smooth, native-app-like experiences.
Chatbots → Personalities	Generic HTML Sites → Brand/Personal Platforms	Web experiences became highly customizable, responsive, and designed with specific User Experience (UX) patterns to elicit certain feelings/behaviors.
Models → Ecosystems	Isolated Sites → APIs/Cloud Computing	Applications began integrating services across platforms using APIs (Application Programming Interfaces), enabling collaboration and data sharing.

We’ll move from using tools to having companions. AI will shift apps from acting as a transactional utility (a tool you use for a specific, one-off task) to becoming an interpersonal entity designed for ongoing engagement and emotional support.

As a corollary, observers also expect the AI to shift from generic to personal, where the chatbots, for example, have personas. 

Our uses of AI assistants will shift to using them as agents that do not wait for explicit instructions, but instead act as autonomous actors.

AI also will move from being a standalone, single-purpose program to a deeply integrated ecosystem that permeates all aspects of the user's digital life. In many instances, that might also mean the AI creates functionality “on the fly.” 

So users might not have to consciously choose an app to “do something,” but tell the AI what is desired and the functionality is produced on the spot, in real time. 

Of course, there are some likely limits. There are casual consumer uses and then different professional use cases that require more granular control. Apps are likely to remain better for the latter. 

For highly detailed or specialized tasks, such as creating a pixel-perfect logo, detailed CAD drawing, or performing precise color grading, the granular control offered by a dedicated app remains superior. 

Originality and Context: AI systems, by nature, train on existing data. Human designers and creators bring unique, cultural, and emotional context to their work that AI struggles to grasp. The "app" becomes the co-pilot that handles the tedious, repetitive tasks (like masking or code completion), freeing the human to focus on high-level creative and strategic decisions.

The New Interface: The "app" might not disappear; its interface is simply changing. Instead of being a canvas full of buttons and menus, the new interface is often a text box—a conversational AI agent that can be queried, similar to how you interact with me.

Feature	Traditional App (e.g., Photoshop)	AI-Driven Interaction (e.g., AI Generator)
Input Method	Manual operation, clicking tools, adjusting settings.	Natural Language Prompt ("Add a realistic looking alien doing a peace sign," "Change the lighting to sunset").
User Skill Required	High, requires training and expertise.	Low, requires clarity in expressing the desired outcome.
Core Value	Provides a toolkit for maximum control and precision.	Provides a direct solution or output, prioritizing speed and accessibility.
Goal	Editing/Creation Process (You control how it's done).	Final Output (The AI controls how it's done).