Study: Consumers Actively Turned Off by AI
New research suggesting that consumers are less likely to choose products marketed as “AI-powered” is resonating with people who feel overwhelmed by hype and underwhelmed by results. Commenters point to bad customer-service bots, low-quality AI-generated content, and gimmicky features as reasons “AI” has become a signal for cheapness, unreliability, and cost-cutting at the user’s expense. Many argue that machine learning is valuable when it quietly improves search, organization, or productivity, but that companies should stop leading with the AI label and instead prove value through tangible, trustworthy features.
Overall reaction to “AI”-branded products
- Many commenters say “AI-powered” has become a negative signal: it implies cheapness, unreliability, or a cost-cutting move.
- AI branding is seen as investor/marketing-driven rather than user-driven, similar to past buzzwords like “blockchain” or “information superhighway.”
- Some note users care about outcomes, not tech labels; “AI” is like advertising a “30GB HDD” instead of “1000 songs in your pocket.”
Visible AI vs. Invisible ML Features
- Strong distinction between:
- Quiet, behind-the-scenes ML (photo search, classification, recommendations) that users often like or accept.
- In-your-face “AI assistants” that users are pushed to interact with.
- Several argue companies should stop marketing AI and just ship good features; people often like the function but dislike the AI label.
Customer Support, Chatbots, and UX
- Widespread frustration with AI chatbots on websites, travel apps, and support lines.
- Complaints: can’t actually perform actions, give circular or wrong answers, become upsell funnels, and act as barriers to reaching humans.
- Many equate “AI” with “annoying chatbots and low-quality content.”
Quality, Trust, and “Hallucinations”
- Errors, hallucinations, and mediocre output erode trust; branding errors as “hallucinations” is seen as spin.
- Some report bad meeting transcripts and flawed features leading organizations to roll back AI tools.
- Others report good experiences with speech-to-text and code assistants, emphasizing hardware/setup and expectations matter.
Cultural, Ethical, and Economic Concerns
- Generative AI is associated with spam, SEO sludge, cheap art, and “slop content,” seen as “poisoning culture” and devaluing human creativity.
- Fear that AI is mainly used to cut jobs, especially in customer service and creative work.
- Some call the current wave part of broader “enshittification” and profit-at-all-costs dynamics.
Positive Use Cases and Design Preferences
- Praised uses: coding assistants (Copilot, similar tools), summarization, pattern recognition, “boring” back-office or admin tasks, improved search/filtering.
- Preferred pattern: AI augments existing UIs, does tedious work, remains optional, is fast, and doesn’t pretend to be a person.
- Several advocate for “boring AI” — internal, task-focused, and not marketed as a headline feature.