AI for Sales & GTM

Most sales teams now use AI somewhere. Far fewer have changed how pipeline gets created and closed. This collection covers AI across the revenue motion: finding and prioritizing accounts, outbound that earns replies, live and recorded sales calls, forecasting, and the GTM engineering that connects it all. It is written for CROs, sales leaders and founders who own the number.

Start here

• How to Use AI in Sales: A CRO's Playbook for Revenue: where AI helps a revenue team and where it quietly adds work.
• Agentic AI for Sales: What Actually Works: when to restructure workflows around agents and when copilots are enough.
• What Is GTM Engineering: the discipline defined, and why AI underperforms in weak go-to-market systems.

Prospecting and lead generation

• AI Prospecting Guide: research and targeting workflows that hold up at scale.
• Signal-Based Selling: building outreach around buying signals and routing alerts into pipeline.
• AI Powered Lead Generation: What Actually Works: governing scoring, signals and routing before volume damages quality.
• How to Use AI for Lead Generation Without Burning the Funnel: personalization that lifts reply rates without burning the list.
• 10 AI Sales Prospecting Tools: ten tools compared on the job each one does.

Outbound and sales conversations

• AI Outbound: A Blueprint for Revenue: raising reply quality, and why more output usually makes outbound worse.
• AI Sales Calls: A Field-Tested Playbook: pre-call research, live assist and AI voice agents, each with its own conversion math.
• AI Agents for Sales That Actually Move Pipeline: choosing one workflow, testing incrementality and scaling after the controls work.

Team, productivity and forecasting

• AI Adoption for Sales Teams: getting reps to use the tools you bought, and the signals that predict it will stick.
• Improving Sales Productivity Beyond Workflow Redesign: winning back the time reps lose to nonselling work.
• 10 Sales Enablement Best Practices: enablement that changes rep behavior.
• GTM Engineer vs SDR: which role to hire for pipeline growth and when each pays back.
• AI for Sales Forecasting: improving forecast accuracy, and when not to trust the number.
• Best AI Sales Tools: the main platforms assessed on production readiness.

Common questions

How is AI used in B2B sales?

The most common uses are account research and prioritization, drafting and personalizing outreach, call recording and summaries, live guidance during calls, CRM updates after calls, and forecasting. AI voice agents for first-touch outbound are newer and work best on narrow, well-defined conversations with a clear handoff to a person.

What is GTM engineering?

GTM engineering is the practice of building the data, routing and automation that run a go-to-market motion: which signals trigger outreach, how leads reach the right rep, and how activity flows back into the CRM. It sits between sales operations and engineering, and it is usually the difference between AI tools that produce pipeline and AI tools that produce noise.

Should you hire an SDR or a GTM engineer?

If your targeting, data and routing are already solid and the bottleneck is conversations, an SDR adds capacity faster. If reps are working poor lists, missing signals or losing leads in handoffs, a GTM engineer fixes the system every future hire will depend on.

Does AI outbound hurt deliverability?

It can. Sending more AI-written email to weaker lists raises spam complaints and hurts domain reputation, which affects every future send. The safer pattern is fewer, better-targeted messages triggered by real buying signals, with volume limits and a person reviewing new sequences before they scale.