Editorial illustration for Gemini task automation: slow, clunky yet impressively handles clarification
Gemini AI Automates Tasks: Smart but Sluggish Workflow
Gemini task automation: slow, clunky yet impressively handles clarification
Dismissing Gemini’s Uber Eats demo as a mere party trick misses the entire story. Watch that video again. The AI taps methodically, slowly, across a screen designed for human eyes. That deliberate crawl reveals a brutal mismatch: we built these interfaces for brains that instantly parse icons and layouts, not for an intelligence that requires semantic clarity.
If the computer is going to get tripped up and ask for clarification when you forget that the restaurant calls your meal a "plate" and not a "combo," or if you ask for "slaw" instead of "shredded cabbage," then it's no more useful than the assistants we've been using for the past decade to set timers and play music. That said, watching Gemini tap and scroll around Uber Eats makes one thing painfully obvious: If you were designing an application for AI to use, it would look nothing like the ones we have today.
Forget the speed. The real lesson is in the clunkiness. When Gemini pauses to ask, “do you mean shredded cabbage?”, it isn’t failing.
It’s exposing the task itself as hopelessly vague. That hesitation proves the system is working—just not like a human. The future isn’t an AI perfectly mimicking a finger on a glass screen.
It’s an AI that can finally negotiate our messy, inconsistent digital language. Our software must adapt.
Related Reading
Browse all Google news →
LLMs & Generative AI ChatGPT's 'Nerdy' tweak rewards goblin metaphors in answers, study finds
LLMs & Generative AI Google tests visual 'magazine-style' UI for Gemini 3 Pro users
LLMs & Generative AI AI Engineers Face Rising Costs, Need New Strategies for Efficiency
Related Topic NVIDIA and Google Cloud let developers scale AI from prototype to production
Market Trends
Related Topic Google's FACTS benchmark shows 70% factuality ceiling across four tests
Research & Benchmarks
From Archives Amazon's ZeroOne, led by J Allard, develops 'Transformer' Alexa phone
From Archives Python decorator cycles fallback callables, adds logging for failure tracking
From Archives Google Search experiments with AI-generated headlines, may expand rollout
Research & Benchmarks
From Archives Google equips Fitbit AI health coach with medical record access
Industry Applications
Common Questions Answered
How does Gemini's task automation handle complex multi-step instructions?
Gemini can parse multi-step instructions and pull in calendar data to complete tasks like ordering food or drafting emails. However, the system is currently slow and often requires user intervention during the process.
What challenges does Gemini face when navigating food delivery apps?
Gemini struggles with precise menu terminology, often getting confused between terms like 'plate' and 'combo' or 'slaw' and 'shredded cabbage'. When encountering these discrepancies, the system pauses to ask for clarification, which can interrupt the task flow.
On which devices has Gemini's task automation been tested?
Gemini's task automation has been tested on the Pixel 10 Pro and Galaxy S26 Ultra, where it can launch food delivery and rideshare apps. Despite being functional, the system's performance is currently described as sluggish and not yet fully refined.
Further Reading
- Gemini can now automate some multi-step tasks on Android — TechCrunch
- Gemini rolls out Android app automation on Galaxy S26 — 9to5Google
- Google Expands Gemini Task Automation to Pixel 10 Series After Galaxy S26 Debut — The Hans India
- First the Galaxy S26 series, now Gemini task automation is rolling out to Pixel 10 — Android Authority
