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The barrier to creating AI-powered solutions has dropped dramatically. An HR team member with no AI expertise built a Slack bot trained on the employee handbook to answer common questions, saving hours of repetitive work. Every department should be empowered to identify and automate its own low-value, repetitive tasks using accessible AI tools.
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Instead of an abstract, top-down AI strategy, a practical starting point is to identify the most tedious, repetitive tasks your team performs. Focusing automation efforts on these "chores" provides a tangible win, builds momentum, and offers a low-risk environment for learning AI tools.
Instead of relying solely on top-down, consultant-led workflow automation, enterprises should empower individual employees with AI tools. This builds user fluency and intuition, allowing them to pull AI into their own workflows, resulting in greater overall impact and less disempowerment.
Before creating a new headcount for administrative or repetitive work, conduct a thought experiment: can an AI agent or an automation workflow fulfill these duties? This approach can reduce overhead and force a re-evaluation of how tasks are accomplished.
Run HR, finance, and legal using AI agents that operate based on codified rules. This creates an autonomous back office where human intervention is only required for exceptions, not routine patterns. The mantra is: "patterns deserve code, exceptions deserve people."
Don't underestimate very junior talent who are native to new AI tools. A recent Stanford grad at Laurel built a 'chief of staff' agent for the sales team, automating call prep by scraping internal and external data. This highlights a new source of high-leverage innovation.
The most effective way to integrate AI is not through individual training but by empowering teams to redesign their own work processes. This team-level approach fosters agency and ensures AI is used to solve real, shared problems, which is more powerful than simply making individuals 'AI literate'.
A new wave of AI automation is being driven by non-technical staff using agent-based platforms. These knowledge workers are building custom AI solutions for complex business processes, bypassing the need for new software purchases or dedicated engineering resources.
Flexport is upskilling its non-technical staff through a 90-day "AI boot camp." By giving domain experts one day a week to learn low-code AI tools, the company empowers them to automate their own repetitive tasks, turning them into "lightweight engineers" who are closest to the problems.
Anthropic has seen a proliferation of personalized work apps created by employees in roles like sales. Tools like Claude Code lower the barrier to building software, allowing teams to create tailored solutions for repetitive tasks instead of using generic tools.
To gain organizational buy-in for AI, start by asking teams to document their most draining, repetitive daily tasks. Building agents to eliminate these specific pain points creates immediate value, generates enthusiasm, and builds internal champions for broader strategic initiatives, making it an approachable path to adoption.
