How to Make AI Work in GTM Workflows

Over the past two years, AI has dominated conversations in every boardroom, Slack channel, and LinkedIn feed. One week, it feels like CEOs are bragging about cutting half their teams in favor of AI, and the next week, studies remind us that the vast majority of AI pilots fail. Consulting firms report that nearly 80% of companies are “advanced AI users,” while real-world data often paints a very different picture. The truth lies somewhere in between, and if you are in GTM workflows, the real challenge is figuring out how to distinguish between hype and impact.

What the Data Really Shows

Recently, a study analyzed more than 1,000 sales conversations across industries. Their findings are telling: 60% of companies still rely heavily on manual work that mainstream AI could already handle, 29% are experimenting with fragmented AI projects, and only 11% have advanced AI implementations that tie together workflows end-to-end. If you feel behind, you are not alone. In fact, most of the market is still trying to bridge the gap between experimentation and execution.

Why Workflows Come First

The opportunity is not to adopt “any AI” but to implement AI or AI agents in ways that bring measurable ROI. And the best place to start is not with tools or hype-driven experiments, but with workflows. GTM motions, predictable, scalable ways to reach and convert customers, are ripe for rethinking with AI. Instead of tinkering with side projects, companies can ask where they already spend significant time and where AI can meaningfully reduce friction or add leverage.

Inbound often represents the majority of the pipeline, yet it is bogged down by repetitive tasks and slow content cycles. By mapping the workflow, identifying bottlenecks, and layering in AI thoughtfully, leaders are seeing real gains. That can mean deploying research agents that surface competitive insights, AI writing assistants that reduce content hours, or fit-assessment agents that help identify the right prospects faster. The point is not to replace human strategy but to amplify it with AI.

Gluon and the Workflow Advantage

This is where companies like Gluon are stepping in. Rather than pushing vague promises about AI transformation, Gluon is building AI-first solutions for lifecycle marketing that integrate directly into GTM workflows. By optimizing personalization, outreach, and campaign execution, they allow teams to cut down on operational drag and focus on proving ROI. It is not about shiny dashboards or experimental tools, but about embedding AI into the very motions that drive growth.

The way to succeed with AI in GTM is also about how we guide the technology. When teams learn to communicate clearly with AI systems, hallucinations drop and the outputs become reliable assets, not gimmicks.

The Human Edge in an AI-First World

Still, AI agents cannot do everything. The best GTM leaders know that trust, empathy, and stakeholder management are more valuable than ever. No AI can replicate the nuance of human judgment or the influence required to align teams around a strategy. AI should automate the busywork data cleaning, clustering feedback, and copywriting so humans can double down on the higher-order skills that move markets and build relationships.

The AI hype cycle may tempt us to chase headlines, but the real defensible moat lies in workflows. Start where your teams spend the most time and do not lose sight of the distinctly human skills that technology cannot replace.

If the last wave of SaaS taught us patience in finding product-market fit, the AI era is teaching us speed. The companies that win will not be those chasing hype but those embedding AI intelligently into GTM workflows, making their motions faster, smarter, and ultimately, more human.

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