Contrary to the impulse to automate busywork, leaders should focus their initial AI efforts on their most critical strategic challenges. Parkinson's Law dictates that low-value tasks will always expand to fill available time. Go straight to the highest-leverage applications to see immediate, significant results.

To maximize ROI from AI, evaluate potential use cases on two axes: the value they provide (time saved, revenue generated) and the amount of ongoing "babysitting" they require (maintenance, monitoring, support). Prioritize high-value, low-babysitting tasks first.

Don't try to optimize your strongest departments with your first AI project. Instead, target 'layup roles'—areas where processes are broken or work isn't getting done. The bar for success is lower, making it easier to get a quick, impactful win.

The ideal tasks for agents are those a human could theoretically do but would never have the patience for, like reading every single log file. Don't try to automate creativity; instead, focus on high-volume, repetitive, or tedious processes that are currently bottlenecks.

Instead of pursuing broad, top-down AI governance, leaders should first target specific business problems where departments intersect and cause delays, such as Sales and Legal on contracts. Use AI as a "thought leader" in a cross-functional team to solve these high-friction issues.

Businesses should prioritize AI projects that can completely automate a recurring workflow. Transforming a multi-week manual process into an instantaneous one delivers transformative value, far exceeding the gains from projects that only offer partial assistance to a human user.

The true power of an AI agent is its capacity to handle the mundane, repetitive work that humans—both internal teams and external agencies—often neglect or de-prioritize. SaaStr couldn't find people willing to consistently manage hundreds of follow-ups, a task their AI now handles flawlessly.

Instead of replacing successful processes, use AI agents to tackle areas that are underperforming or completely ignored, like re-engaging lapsed customers. This strategy ensures any positive result is a net gain and minimizes risk, making even small yields feel magical.

Leadership often imposes AI automation on processes without understanding the nuances. The employees executing daily tasks are best positioned to identify high-impact opportunities. A bottom-up approach ensures AI solves real problems and delivers meaningful impact, avoiding top-down miscalculations.