To shift a services-oriented company to a product mindset, frame productization as a competitive advantage. Repeatable, productized solutions offer greater market differentiation than purely custom builds, leading to more effective competition and new deal wins. This tangible benefit helps secure buy-in from sales and leadership.

Don't just replace human tasks with AI. Deploy AI agents to handle leads your sales team ignores, like small deals or low-scored prospects. This untapped segment, as SaaStr found with a 15% ticket revenue lift, represents significant growth potential by filling a gap in your GTM process that humans create themselves.

Most companies are not Vanguard tech firms. Rather than pursuing speculative, high-failure-rate AI projects, small and medium-sized businesses will see a faster and more reliable ROI by using existing AI tools to automate tedious, routine internal processes.

Focusing on AI for cost savings yields incremental gains. The transformative value comes from rethinking entire workflows to drive top-line growth. This is achieved by either delivering a service much faster or by expanding a high-touch service to a vastly larger audience ("do more").

For service-based businesses, speed-to-lead is everything. An AI-powered office manager using advanced voice AI can provide 24/7, instant responses to inquiries. This isn't just a cost-saving measure; it's a revenue-generating tool that captures leads competitors miss due to slow, manual follow-up, dramatically increasing the likelihood of winning the job.

An advanced inbound AI agent does more than book meetings. By ingesting your website, tracking visitor behavior, and having contextual conversations, it provides the sales team with such deep pre-qualification that the initial discovery call becomes unnecessary, allowing reps to jump directly into problem-solving.

Beyond booking meetings for high-value deals, AI agents can be empowered to handle the full sales cycle for lower-priced products. They can answer questions, provide discount codes, and conduct follow-up, creating a significant, automated revenue stream with no human sales involvement.

A killer app for AI in IT is automating tedious but critical tasks. For example, investigating why daily cloud spend deviates by more than 5%. This simple-sounding query requires complex data analysis across multiple services—a perfect, high-value problem for an AI agent to solve.

Previously, building 'just a feature' was a flawed strategy. Now, an AI feature that replaces a human role (e.g., a receptionist) can command a high enough price to be a viable company wedge, even before it becomes a full product.