Businesses often get distracted by trendy technology like AI. However, if foundational business metrics, such as a call center booking rate below 85%, are underperforming, focusing on new tech is a mistake. Solidify core operations in marketing, finance, and sales first before chasing shiny objects.

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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.

Automating a sales lead follow-up process scales directly with business growth—more leads mean more value from the automation. In contrast, a personal assistant agent offers static productivity gains. To maximize long-term ROI, focus automation efforts on systems that grow in usage and impact as the business expands.

Over-investing in sales tech creates an environment where reps are drowning in logins, reporting, and process. This 'paucity of time' stifles creativity and prevents them from focusing on the essential human element of building rapport and trust, which is often what actually closes deals.

Marketing is an accompaniment to a great operations team, not a replacement. If your company culture, leadership, or service delivery is weak, increasing your marketing spend will only expose and accelerate those foundational flaws. You must fix the core business before scaling marketing efforts.

Don't get distracted by flashy AI demonstrations. The highest immediate ROI from AI comes from automating mundane, repetitive, and essential business functions. Focus on tasks like custom report generation and handling common customer service inquiries, as these deliver consistent, measurable value.

Open and click rates are ineffective for measuring AI-driven, two-way conversations. Instead, leaders should adopt new KPIs: outcome metrics (e.g., meetings booked), conversational quality (tracking an agent's 'I don't know' rate to measure trust), and, ultimately, customer lifetime value.

For companies wondering where to start with AI, target the most labor-intensive, process-driven functions. Customer support is an ideal starting point, as AI can handle repetitive tasks, leading to lower costs, faster response times, and an improved customer experience while freeing up human agents for more complex issues.

Getting approval for an operations hire is difficult because they aren't directly tied to new revenue. Instead of a vague promise of "efficiency," build a business case by quantifying the cost of a broken process—like a high lead disqualification rate—and show how the hire will unlock that hidden pipeline.

Instead of being swayed by new AI tools, business owners should first analyze their own processes to find inefficiencies. This allows them to select a specific tool that solves a real problem, thereby avoiding added complexity and ensuring a genuine return on investment.

Instead of broadly implementing AI, use the Theory of Constraints to identify the one process limiting your entire company's throughput. Target this single bottleneck—whether in support, sales, or delivery—with focused AI automation to achieve the highest possible leverage and unlock system-wide growth.