Human-AI Intersectionr/artificial

Why Hasn’t AI Made Work Easier?

Monday, March 23, 2026Read original

ai-productivity-paradoxshallow-work-trapdeep-work-declineai-adoption-consequences

“AI users spent 100%+ more time on email/messaging and 9% less time on focused work—we're working faster on the wrong things”

Key takeaways

Large-scale study (164K workers, 180-day tracking) shows AI adoption doubled time spent on email/messaging/chat and increased business software use by 94%, but reduced focused work time by 9%
This represents a 'productivity paradox'—AI accelerates shallow, context-switching work while cannibalizing the deep work that drives actual value creation
Pattern repeats historical technology adoption cycles (email, mobile, video-conferencing) where efficiency tools paradoxically increased busyness without proportional output gains
The methodology is particularly strong: individual tracking before/after AI adoption with control group comparison, eliminating confounding variables
Represents emerging contrarian narrative against uncritical AI adoption—organizations need intentional frameworks to prevent AI from becoming another busyness multiplier

Why this matters for operators: Critical for companies implementing AI tools—need frameworks to prevent shallow work proliferation

I cover AI×GTM intelligence like this every Wednesday.

GTM OpsDemand Gen ReportVictor's pick

These are high % stats showing what we implicitly already know

Peer validation (73% trust) now dramatically outweighs traditional vendor marketing (55% trust vendor sites, 39% trust AI chatbots, 36% trust social media) in early-stage B2B buying
83% of B2B buyers complete self-directed research before sales engagement, with high-stakes categories (software, professional services, HR) taking several weeks to months in extended evaluation
Search engines serve as navigation layer, not destination—buyers use search to identify options then validate through peer communities like Reddit (121M daily users, 19% YoY growth), creating imperative for authentic community presence

community-led-growthback-to-basics-gtmhuman-first-sales

AI DevelopmentGTM AI Podcast & NewsletterVictor's pick

The move from user initiated to automated workflows is one of the main transitions with current agentic capabilities IMO

Claude Channels (launched March 20, 2026) enables event-driven AI automation via MCP protocol, shifting from pull-based (user-initiated) to push-based (event-triggered) workflows
Practical use case: CI/CD failures can trigger autonomous investigation, fix deployment, and resolution without human intervention - reducing 12-hour incident windows to near-zero
Technical implementation uses MCP servers connecting Claude Code to messaging platforms (Telegram/Discord at launch), with Bun runtime for 4x faster cold-start performance vs Node

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AI×GTMThe InformationVictor's pick

If you think white collar job displacement is a joke, or a distant future concern, this is just one more sign it is most definitely NOT. It's here.

AWS is deploying AI agents to handle technical sales support functions previously performed by thousands of specialists
The AI automation directly correlates with recent layoffs of hundreds in sales, business development, and technical specialist roles
Major cloud provider is using its own AI capabilities to reduce headcount in customer-facing technical roles, signaling broader industry trend

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This analysis was produced using the STEEPWORKS system — the same agents, skills, and knowledge architecture available in the GrowthOS package.