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In the rapidly evolving landscape of artificial intelligence, a surprising generational divide is emerging: while Generation Z (ages 18-26) experiments with AI across a wider array of tasks, it's their older Millennial counterparts (ages 27-40) who are more likely to actually spend money on the technology. This insight comes from a comprehensive new study by media company Future, which surveyed over 2,000 individuals across the US and UK, providing a nuanced look at how different age groups are adopting — and resisting — generative AI tools.

The Experimenters vs. The Spenders

The research, reported by ZDNET, highlights a clear pattern: Gen Z leads in exploratory usage across nearly all categories. A notable 55% of Gen Z respondents use AI for creating imagery or art versus 46% of Millennials. Similar gaps appear in applications like learning assistance, content generation, and creative writing. Yet Millennials surpass all generations in two critical areas:
- Purchasing intent: 33% would buy AI-advertised tech (vs. 24% of Gen Z)
- Commercial use: 48% leverage AI for product recommendations (narrowly edging out Gen Z's 47%)

"Gen Z pushes boundaries in how AI can be used, but Millennials drive monetization—a crucial insight for product teams," notes the Future report.

Barriers and Beliefs Across Generations

Resistance to AI adoption also varies significantly:
- Gen Z most frequently reported being "happy without AI"
- Baby Boomers prioritized privacy concerns
- Millennials showed fewer adoption barriers overall

Philosophical opposition to AI grew by 11% year-over-year—the only barrier that increased—signaling rising ethical concerns across demographics. Meanwhile, skills-based barriers dropped sharply, suggesting improved tool accessibility.

Implications for Developers and the AI Industry

  1. Product Strategy: Gen Z's broad experimentation indicates demand for versatile, multi-use tools, while Millennials' spending patterns highlight the need for clear ROI demonstrations in professional or commercial contexts.

  2. Monetization Models: Subscription services and premium features may resonate more with Millennials, whereas Gen Z favors freemium access for exploration.

  3. Ethical Design: Growing philosophical opposition necessitates transparent AI development and communication—especially for privacy-sensitive applications targeting older users.

This generational split reveals that adoption isn't monolithic. Success requires tailored approaches: tools that captivate Gen Z's curiosity while delivering tangible value for Millennials' wallets. As AI permeates daily life, understanding these divides will separate industry leaders from the rest.

Source: Future Media Study, September 2025 (via ZDNET)