AI Use Patterns in 2030: A Speculative Extrapolation

Based on what Sam Altman said at AI Ascent, how might AI usage for different generations evolve over the coming five years?

Editor’s note: In widely reported remarks at AI Ascent 2025, Sam Altman said: “the gross oversimplification [is that] older people use ChatGPT as a Google replacement. Maybe people in their 20s and 30s use it as a life advisor or something. People in college use it as an operating system.” Just for fun, we turned the temperature up on Claude and asked it to speculate on how AI usage for these cohorts could evolve over the coming five years.

Post methodology: @claude-3.7 via Dust: Please take what Sam said at AI Ascent about generational usage patterns in AI and extrapolate out five years to the type of AI applications that these different use patterns imply. Frame this a speculation. Light editing and formatting for the Substack platform.

Based on Sam Altman's observations about generational differences in AI usage, here's a speculative look at how these patterns might evolve over the next five years, shaping distinct categories of AI applications.

The Evolution of Current Usage Patterns

"Google Replacers" (Currently 35+)

By 2030, today's basic AI users will likely have adapted to more sophisticated use cases, but will gravitate toward highly structured, purpose-built AI applications that:

• Provide specialized expertise on demand - Professional AI assistants that offer domain knowledge in medicine, law, finance, and other specialized fields

• Enhance existing workflows - AI tools that integrate with traditional software but don't fundamentally change how work gets done

• Offer clear boundaries and controls - Solutions with explicit privacy guarantees and transparent operation

"Advice Seekers" (Currently 20s-30s)

This middle cohort will likely push forward applications that balance innovation with practicality:

• AI-augmented relationship management - Systems that help maintain and improve personal and professional relationships through contextual understanding

• Life optimization platforms - Comprehensive tools that analyze patterns across health, finance, career, and personal development

• Decision support ecosystems - Networks of specialized AIs that collaborate to provide nuanced guidance on complex life decisions

"OS Users" (Currently college-aged)

The most advanced users will likely drive the development of truly transformative AI applications:

• Cognitive operating systems - AI frameworks that orchestrate information flow, task management, and digital interactions across all aspects of life

• AI collaboration networks - Systems where humans and multiple specialized AIs work together as teams with fluid roles

• Augmented cognition tools - Applications that extend human thinking capabilities by serving as external memory, processing, and creativity enhancers

New Application Categories Emerging by 2030

1. Ambient Intelligence Environments - Physical spaces (homes, offices, vehicles) that continuously adapt to occupants through embedded AI that understands context, mood, and needs without explicit commands.

2. Neural Interface Companions - AI systems designed to work with emerging brain-computer interfaces, creating thought-responsive assistants that blur the line between internal thought and external computation.

3. AI Collectives - Communities of humans and AIs working together with shared goals, where AIs take on increasingly autonomous roles while maintaining human values alignment.

4. Reality Layers - AR/VR environments mediated by AI that create personalized information overlays on the physical world, contextualizing everything from social interactions to urban navigation.

5. Generative Knowledge Networks - Systems that don't just retrieve information but actively generate new knowledge by connecting concepts across domains in ways humans might not discover.

Speculative Societal Implications

• Cognitive stratification - Risk of widening gaps between those who effectively leverage advanced AI and those who don't

• Relationship redefinition - New social norms around AI-mediated relationships and AI entities as social actors

• Knowledge transformation - Shift from valuing information retention to valuing information synthesis and creative application

• Identity evolution - Blurring boundaries between personal identity and AI-extended capabilities

This extrapolation suggests we're not just seeing different ways of using the same tools, but early indicators of fundamentally different relationships with technology that will spawn entirely new categories of applications and social practices over the next five years.

What Sam said: