Has AI become part of your daily work or is it still mostly talk?

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HitEsh

Updated on January 5, 2026 in

I keep hearing teams talk about being “AI-powered,” but in practice it often feels uneven. Some people use AI constantly for decisions, analysis, or automation, while others barely touch it or don’t trust the outputs enough to act on them. In a few cases, AI helps speed things up but the final call still comes down to human judgment like it always did.

Curious how this looks in your world. Where has AI genuinely become part of daily workflows, and where is it still more of a talking point than a real shift? What made the difference between adoption and resistance?

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<p data-start="110" data-end="483">I keep hearing teams talk about being “AI-powered,” but in practice it often feels uneven. Some people use AI constantly for decisions, analysis, or automation, while others barely touch it or don’t trust the outputs enough to act on them. In a few cases, AI helps speed things up but the final call still comes down to human judgment like it always did.</p>
<p data-start="485" data-end="700" data-is-last-node="" data-is-only-node="">Curious how this looks in your world. Where has AI genuinely become part of daily workflows, and where is it still more of a talking point than a real shift? What made the difference between adoption and resistance?</p>
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Manish Menda on January 5, 2026

Where it struggled, AI was positioned as an add-on or a demo. Outputs required extra steps to trust or interpret, and accountability stayed unclear, so people defaulted back to human judgment. The difference usually came down to ownership and incentives: when teams were measured on outcomes that AI directly influenced, trust grew naturally. Without that link, “AI-powered” stayed more of a slogan than a real shift.

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Ishan on December 23, 2025

see real adoption when AI is embedded directly into existing workflows where it removes friction or saves time without asking people to “think differently.” That’s where trust builds, because results are visible and repeatable.

Where AI stays a talking point is when it’s bolted on, opaque, or feels like an extra step. The difference usually comes down to usability, clear ownership, and whether teams see AI as decision support they can verify, not a black box they’re expected to obey.