Scope of Generative AI

Generative AI has far more to offer your site than simply mimicking a conversational ChatGPT-like experience or providing features like generating cover letters on resume sites.

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Let’s explore how you can integrate Generative AI with your product in diverse and innovative ways!

There are three key perspectives to consider when integrating Generative AI with your features: system scope, spatial relationship, and functional relationship.

System Scope — How much of your system is managed by AI?
Spatial Relationship — Where is AI positioned relative to your features?
Functional Relationship — How does AI interact with other features on the page or screen?

Each perspective offers a different lens for exploring integration pathways and can spark valuable conversations about melding AI with your product ecosystem. These categories aren’t mutually exclusive; instead, they overlap and provide flexible ways of envisioning AI’s role.

1. System Scope — The Reach of Generative AI in Your System

System scope refers to the breadth of integration within your system. By viewing integration from this angle, you can assess the role AI plays in managing your platform’s overall functionality. While these categories may overlap, they are useful in facilitating strategic conversations.

Component: AI is applied to individual elements. For instance, a table cell might display an AI-generated tooltip offering insights.
Flow: AI can replace, enhance, or even completely redesign user flows. Instead of following a multi-step process, AI could streamline tasks by eliminating unnecessary steps.
Feature: AI is incorporated as a specific tool to achieve an action, such as enabling users to generate content or insights with a single button click.
Application: AI is used to create purpose-built applications, like Rationale (for decision-making) or Julius AI (for data analysis and visualization), to deliver targeted experiences.
Platform: At this level, AI supports the ecosystem across multiple apps and industries, from individual-focused platforms (e.g., personal AI assistants like Rewind AI) to industry-specific solutions (e.g., legal or medical AI systems).

2. Spatial Relationships — Where AI Interacts with Features

Spatial relationships describe where AI features sit in relation to your platform’s functionality:

Separate: AI is located on a different page or screen than the core features, allowing users to experiment without disrupting the existing experience.
Alongside: AI exists alongside your functionality. This approach, like Microsoft Copilot or Google’s image generation in its office suite, integrates AI as an available but secondary tool.
Layered: AI appears as an overlay, such as Grammarly’s floating window, to offer suggestions or insights without altering the underlying content.
Integrated (Parent): Here, AI drives the entire experience, with features (e.g., forms or images) playing a supporting role. For example, Perplexity.ai integrates AI to aggregate and generate all content.
Integrated (Child): AI serves as a content provider, such as in Bing, where AI generates results that supplement the primary search functionality.
Point: AI is embedded directly into individual elements, like table cells or input fields, offering real-time contextual insights.

3. Functional Relationships — How AI Interacts with Features

Functional relationships determine how AI and platform features work together. This includes how users engage with AI and how AI content updates based on feature interactions:

Separate: AI operates independently from the platform’s features, requiring users to take specific actions for AI to provide content.
Aware of: AI updates based on user inputs but requires manual engagement. For example, Miro’s side panel responds to selections but needs user initiation to generate insights.
Acting upon: AI updates automatically based on user activity, modifying its outputs as interactions occur. However, this may come with cost constraints.
Feature Incorporates: AI-generated content is injected directly into features, enriching the overall experience. For instance, Perplexity.ai seamlessly integrates sources and insights into its results.
Uses Conversationally: AI features work within a conversational framework, allowing users to engage with the content naturally.