How much do you trust AI agents?

I think the real trust line is not “AI agent or no AI agent.”

It’s: what is the agent allowed to do without me?

I’m very comfortable with AI helping me think, draft, summarize, prioritize, research, and spot things I would have missed. I’m much less comfortable with AI taking irreversible actions without approval — sending emails, spending money, publishing to social, messaging leads, changing customer records, or touching sensitive data.

That distinction is actually shaping how we’re building Traction. Our AI assistant, Orbit, is designed more like a strategic business partner than a rogue autopilot. It can recommend what to post, which leads need follow-up, where revenue is leaking, or what campaign to run next — but the human should stay in control of the final action.

For small businesses especially, trust matters because the stakes are not abstract. One weird auto-reply, one bad follow-up, one off-brand post, or one mishandled lead can cost real revenue and reputation.

So my answer is: I trust AI agents when they are operating inside clear boundaries:

• draft before send

• recommend before execute

• explain before automate

• log what happened

• let the business owner approve anything public, financial, or customer-facing

I don’t think the future is “AI does everything.” I think the better future is AI gives business owners leverage without taking away judgment.

Whatever these chatbots and agents do, I still believe the human mind needs to stay in control. I use AI as a tool, but I still review and oversee everything it generates to make sure it’s not affecting me negatively. Humans can still think from angles and intuition that AI simply cannot fully replicate yet and is still prone to making errors in decisions

Dedy's point is interesting, the opacity problem is real. Most people conflate "AI having access" with "AI having unchecked control." They're very different things. Read-only access vs write access, logged actions vs black box outputs, the architecture of trust matters as much as the intent.

Honestly, depends on what the AI agent is being trusted with. If it’s making fully autonomous decisions with zero human oversight, I’d be cautious. But if it’s acting like an always-on system that monitors things humans can’t constantly watch, spots issues early, and helps teams respond faster, then yeah, I think that’s where AI agents make real sense.

I recently came across JARVIS by Staqu, and it shifted my view a bit because the use cases felt practical rather than hype-driven.

For example:

In retail, it can spot queue build-up, customer movement patterns, low - engagement store zones, suspicious activity, and even help understand whether marketing campaigns are actually driving engagement.

In manufacturing, this feels even more useful honestly, monitoring plant floors, intrusion alerts, theft risks, safety compliance, restricted zone access, fire/smoke alerts, operational blind spots, etc. Humans simply can’t watch hundreds of camera feeds properly all day.

For warehouses/logistics, same story, vehicle movement, loading dock monitoring, unauthorised access, stock movement visibility.

For public safety / infrastructure, crowd monitoring, perimeter security, unusual movement detection, vehicle tracking.

That’s where AI agents feel valuable to me, not as decision-makers, but as systems that never get tired, never miss things because they looked away, and surface useful alerts in real time. That’s also why I think the future of analytics changes because of this.

Traditional analytics tells us “here’s what happened yesterday.” Whereas, AI-driven systems tells us “this is happening right now, do something.” That’s a huge difference.

So yeah, I trust AI agents more as continuous monitoring plus decision support systems, not as fully independent brains making business calls on their own.

I completely agree with your point of view! I also strongly don't want AI to have access to too much sensitive personal information about me, especially financial information and details of some of my private accounts. In addition, I am not very confident about the information provided by AI. Although the Agent now has capabilities such as online search and RAG, it still may have illusions or fail to accurately interpret my needs, not providing me with accurate information, or even fabricating information to fulfill my requirements. I will not completely rely on AI for my very important papers and research in my work.

trust is the wrong unit. what matters is reversibility. an agent that drafts an email, fine. an agent that sends payment instructions, not without a second pair of eyes and an audit trail. i grade actions on two axes, blast radius and reversibility, and only the bottom-left quadrant runs without human approval. the failure mode i see most is teams giving agents broad tool access in week one because the demo is impressive, then walking it back after the first incident. easier to start narrow and earn surface area than to claw it back after something is wrong in production.

I don’t think agents should be trusted with direct sensitive access. They should get permissions, limits, and logs.

 The areas I wouldn’t hand over raw access to are wallets/private keys, API keys with billing, inbox/DMs, health data, and anything involving identity or money movement.

 The pattern I prefer is: agent asks → user/policy approves → vault signs or performs the scoped action → everything is logged and revocable.

 This is the exact reason I’m building DCP, a local permission vault for agents. The agent can request access, but secrets stay encrypted locally, and the user keeps control.

 Curious whether people would tolerate that approval flow, or if it feels too high-friction.

For sandboxed, reversible tasks high trust. I let AI generate and run full HTML/JS components directly inside documents. The key word is sandboxed: iframe with allow-scripts only, no same-origin, no access to anything outside. Trust proportional to blast radius.

We humans have a unique way of living

1. create sci-fi terminator movie

2. build AI tools

3. shove it in everything

4. be dependent on AI

5. wonder why the sci-fi movie came true

I draw the line at anything irreversible. An agent can draft and propose all day, but the step that spends money or ships something gets a human check. The trick is making that check cheap: a clear diff or a capped budget beats blanket trust, because the failure that actually hurts is the confident wrong answer that looks fine.