The Rise of 'Feature AI': Why Your Favorite Apps Are Filling Up With Useless Gadgets

The Gimmick in the Machine

This week, podcasting platform Riverside rolled out "Rewind," an AI-powered year-in-review feature. It creates quirky video collages of you laughing, a supercut of your verbal tics like "umm," and identifies the single word you used most. It’s a fun, shareable piece of digital confetti. But for any executive, creator, or investor paying attention, it's also a clear signal of a troubling trend: the rise of 'Feature AI'—gimmicky, low-utility applications of artificial intelligence tacked onto products as a marketing ploy.

While mildly entertaining, these features represent a fundamental miscalculation of what users actually need. They are the AI equivalent of corporate greenwashing—a superficial nod to a trend without any substantive value. This isn't just about one podcasting app; it's a symptom of a broader identity crisis in the tech industry as companies scramble to find a meaningful AI strategy beyond the chatbot.

Why It Matters: The Coming AI Backlash

The proliferation of 'Feature AI' has significant second-order effects that most companies are ignoring in their rush to appear innovative. The primary risk is AI fatigue. When users are constantly bombarded with novel but useless AI tools, they begin to associate AI with digital clutter rather than genuine utility. This devalues the entire category and makes it harder for truly transformative AI applications to gain traction.

Furthermore, it points to a concerning trend in product development: technology in search of a problem. Instead of starting with a user need, companies are starting with a powerful new technology (LLMs, generative AI) and desperately trying to shoehorn it into their existing products. This isn't innovation; it's decoration. And in a competitive market, users will ultimately abandon bloated, unfocused products for streamlined, effective alternatives.

The Analysis: A Spectrum of AI Implementation

From Valuable Tool to Dangerous Toy

To understand the current moment, we must see AI implementation as a spectrum. On one end, you have high-utility, low-glamour tools that are genuinely transformative. Riverside's own AI-powered transcription is a perfect example. It solves a tedious, time-consuming problem for creators, enhances accessibility, and works reliably in the background. This is AI as a powerful tool, augmenting human capability.

In the middle, you have Riverside's "Rewind." It's AI as a novelty—a fun, harmless gimmick designed for social sharing. It doesn't solve a problem or improve a workflow, but it generates a quick laugh and some brand engagement. It's a toy.

But on the far end of the spectrum, you have the outright dangerous misapplications. The source article's mention of The Washington Post's experiment with AI-generated news podcasts is the critical cautionary tale. When the same logic of "let's automate this creative process" is applied to journalism, the result is factual errors and fabricated quotes, eroding the very trust the institution is built on. It reveals a profound misunderstanding of how LLMs function—they are probability engines, not truth engines. The failure rate of 68-84% in the Post's internal tests is a damning indictment of applying AI to tasks that require editorial judgment and accountability.

PRISM Insight: Navigating the 'Feature AI' Bubble

For Creators & Businesses: An AI Evaluation Framework

The key for creators and business leaders is to become ruthless in evaluating AI tools. Don't be swayed by marketing hype. Before integrating any new AI feature into your workflow or product, ask three simple questions:

• Does it eliminate drudgery? A valuable AI tool takes over a repetitive, low-skill task that consumes time and energy (e.g., transcribing audio, removing filler words, generating basic show notes).
• Does it enhance creativity? A good AI partner can act as a sounding board, suggest alternate phrasings, or help brainstorm ideas—but it shouldn't make final creative decisions. It should be a co-pilot, not the pilot.
• Is the output reliable? For any task requiring factual accuracy, the AI's output must be considered a first draft that requires human verification. Never trust, always verify.

Any tool that doesn't provide a clear "yes" to at least one of these questions is likely 'Feature AI'—a distraction at best and a liability at worst.

PRISM's Take

Riverside's "Rewind" isn't a failure; it's a clarification. It perfectly encapsulates the current adolescent phase of the AI boom, where the industry is infatuated with novelty over utility. This period of playful, low-stakes experimentation is necessary, but it's also a distraction from the real work to be done. The future of AI in creative and professional fields will not be defined by laughter montages, but by seamless, invisible tools that augment human intellect and eliminate tedious work. The companies that win won't be the ones that shout "We use AI!" the loudest, but those that quietly integrate it so effectively that users simply feel more capable, creative, and productive.