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.

Instead of replacing top performers, AI should be used to do work humans physically cannot. Salesforce targeted a backlog of 100 million 'orphan leads,' using an AI agent to work through 8,000 dormant leads in three weeks. This generated $500,000 in pipeline that would have otherwise been zero.

Instead of relying on subjective feedback from account executives, Vercel uses an AI agent to analyze all communications (Gong transcripts, emails, Slack) for lost deals. The bot often uncovers the real reasons for losing (e.g., failure to contact the economic buyer) versus the stated reason (e.g., price).

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.

Vercel's CTO Malte Ubl suggests a simple method for finding valuable internal automation tasks: ask people, "What do you hate most about your job?" This uncovers tedious work that requires some human judgment, making it a perfect sweet spot for the capabilities of current-generation AI agents.

Unlike older sales tools, AI agents shouldn't be handed to individual SDRs to manage. This approach leads to failure. Instead, centralize the strategy: a core team must own agent training, contact routing, and performance tuning to ensure a consistent and effective GTM motion across the entire organization.

Traditional pre-qualification uses rigid scripts, potentially missing high-value clients who don't fit the mold. Agentic AI analyzes conversation nuances to identify various customer archetypes and high-intent signals beyond the primary avatar, ensuring top prospects aren't overlooked.

This emerging role applies engineering and AI to GTM functions, building agents to automate tasks like lead qualification and personalized outreach. This dramatically increases efficiency, allowing one person, with an AI agent, to do the work of ten.