Humans actually prefer talking to an AI than a support person, says gas giant as it cuts jobs


I keep seeing the same debate pop up: is Claude smarter than Gemini, is Chat GPT still ahead, whatever. Honestly? Wrong question entirely. The stuff that’s actually going to matter is happening quietly, in places most people aren’t even looking.
I’ve been using these tools since they were basically novelties the kind of thing you showed your coworkers as a party trick. Ask around now and most people will tell you the future is “better answers” or “smarter writing.” That’s not really where this is going.
The bigger shift is in what these things fundamentally are, not how well they perform on some benchmark. Here’s my read on it, based on where the money and the engineering effort have actually been going.

Right now you type a question, you get an answer, that’s the whole interaction. That model has an expiration date on it.
The next phase is AI that actually does things instead of just describing them: books your flight, cleans up your spreadsheet, pushes a code fix. This isn’t a prediction; it’s already happening in early form. The labs have shipped versions of this that can browse the web, click through interfaces, run code.
What’s holding it back isn’t capability, it’s trust. Nobody wants software that deletes the wrong file or emails the wrong person by mistake. So a lot of what’s coming isn’t going to be flashier intelligence — it’s going to be boring stuff like permission systems, confirmation steps, undo buttons. The unglamorous plumbing that makes people comfortable handing over real responsibility.
Most AI still forgets you exist the second you close the tab. A few companies have bolted memory features on top, but it’s early.
What’s coming is assistants that actually track your ongoing projects and how you write and what you keep running into problems with — without you re-explaining your whole situation every single time. That’s genuinely useful. It also raises uncomfortable questions about data retention and consent. My guess is the tools that win here won’t just remember more — they’ll let you actually see what’s stored and delete it, rather than just saying “trust us.”
“It can look at pictures now” used to be a headline feature. Soon that’ll just be table stakes. Voice, video, live camera feeds — these are going to merge into one conversation rather than sitting in separate menus you have to hunt for.
Point your phone at something broken, get spoken help back instead of typing out three paragraphs describing the problem. This stuff already exists in rough form. What’s actually improving is speed and reliability, not whether it’s possible at all.
There’s a whole separate competition happening that has nothing to do with which model tops the leaderboard. It’s about which company can get something genuinely useful running on your phone without needing a data center behind it.
On-device matters because it’s faster, it’s private, and it’s cheaper to run. Expect a split forming — giant models for heavy lifting, small efficient ones baked directly into your phone for everyday tasks.
Most assistants sound pretty interchangeable right now — competent, a little bland. That’s going to change. Some will stay blunt and no-nonsense. Others will lean warm, or get tuned specifically for law or medicine or teaching.
This matters more than it sounds like it should, because tone is tied directly to trust, and trust is what decides whether someone actually uses this thing for something that matters health, money, their kid’s homework.
This is the part that gets ignored in most of these takes. Governments in the US, EU, and across Asia are actively writing the rules right now around transparency, copyright, data use. These aren’t theoretical debates. They decide what actually ships.
Expect more labeling on AI-generated content, clearer ways to opt out of training data, tighter restrictions around healthcare and hiring and anything involving kids. The companies that get ahead of this instead of fighting it are probably going to end up with an advantage that outlasts a few missed product launches.
Benchmark scores make for good headlines. They don’t decide who actually wins long-term. What decides that is whether people trust a tool enough to hand it something real.
That trust gets built through consistency and honesty about limitations and through how a company handles it when something breaks. An assistant that says “I’m not sure” when it isn’t sure will probably earn more loyalty over years than one that scores a point higher on some test nobody outside a research lab has heard of.
Not some dramatic leap forward. More like a slow accumulation of smaller changes tools that remember more, act more on their own, run faster locally, and get shaped as much by regulators as by engineers. What you’re using today is a rough draft, not a finished product.
The real race isn’t about who has the smartest model. It’s about who builds something boring enough, reliable enough, that you stop noticing you’re even using it.
Curious what you think — five years from now, do these feel more like tools to you, or more like teammates? Drop your take below.
Everyone’s Asking the Wrong Question About AI Chatbots was originally published in Coinmonks on Medium, where people are continuing the conversation by highlighting and responding to this story.

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The post Microsoft’s ‘Project Perception’ Could Challenge Anthropic’s Mythos in AI Security appeared first on TechRepublic.
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Microsoft is reportedly developing Project Perception, a lower-cost AI security tool that would use multiple models to identify enterprise vulnerabilities.
The post Microsoft’s ‘Project Perception’ Could Challenge Anthropic’s Mythos in AI Security appeared first on TechRepublic.
Moonshot AI’s 2.8-trillion-parameter Kimi K3 raises China’s open-model ambitions while posing major infrastructure and cost questio
The post Moonshot AI Launches World’s Largest Open-Source Model appeared first on TechRepublic.

Learn what Google’s major AI models do, including Gemini, Veo, Imagen, Nano Banana, Gemma, Lyria, Chirp, and Gemini Nano.
The post Google AI Models Explained: Gemini, Veo, Nano Banana & More appeared first on TechRepublic.
Learn what Google’s major AI models do, including Gemini, Veo, Imagen, Nano Banana, Gemma, Lyria, Chirp, and Gemini Nano.
The post Google AI Models Explained: Gemini, Veo, Nano Banana & More appeared first on TechRepublic.
AI mental health tools may support journaling, reflection and routine guidance, but current evidence does not support using them as replacements for licensed therapists. HR and IT leaders need product-specific evidence, strict data controls and reliable human escalation before deployment.
The post Can AI Replace Therapists? What HR and IT Leaders Need to Know appeared first on TechRepublic.
AI mental health tools may support journaling, reflection and routine guidance, but current evidence does not support using them as replacements for licensed therapists. HR and IT leaders need product-specific evidence, strict data controls and reliable human escalation before deployment.
The post Can AI Replace Therapists? What HR and IT Leaders Need to Know appeared first on TechRepublic.
China warned organizations to remove certain Claude Code versions over alleged backdoor risks, while Anthropic called the feature anti-abuse protection.
The post China Warns of Claude Code ‘Backdoor’ Security Risk appeared first on TechRepublic.
China warned organizations to remove certain Claude Code versions over alleged backdoor risks, while Anthropic called the feature anti-abuse protection.
The post China Warns of Claude Code ‘Backdoor’ Security Risk appeared first on TechRepublic.
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The post Meta’s Muse Image Explained: What to Know About the New AI Image Model appeared first on TechRepublic.
Meta Muse Image brings AI image generation to Instagram, WhatsApp, and Meta AI. Here’s what users should know about features and privacy.
The post Meta’s Muse Image Explained: What to Know About the New AI Image Model appeared first on TechRepublic.
A June 2026 research review found that AI chatbot warning labels may be a weak safeguard for organization-backed AI advisors, raising new audit questions for IT, security, and compliance teams.
The post AI Chatbot Warnings May Not Stop Hallucinations, Researchers Say appeared first on TechRepublic.
A June 2026 research review found that AI chatbot warning labels may be a weak safeguard for organization-backed AI advisors, raising new audit questions for IT, security, and compliance teams.
The post AI Chatbot Warnings May Not Stop Hallucinations, Researchers Say appeared first on TechRepublic.