The discussion around AI often focuses on content creation, software development and financial management. However, one of the business processes being transformed fastest is the go-to-market (GTM) process, where marketing, sales, and product align to generate revenue.
For years, the formula to acquire and upsell customers relied on the “demand generation funnel,” built on CRM and marketing automation tools like Salesforce or HubSpot. This process tracked customer engagement, used scoring to classify marketing-qualified leads (MQLs) and sales-qualified leads (SQLs), and relied on email to nurture prospects toward a “closed won” status.
This formula has been upended by two major developments. Firstly, email and social channel deliverability has collapsed by over 50% due to changes in spam policies (Yahoo, Google, Microsoft) and, critically, an “oversaturation” of the outbound channel. Everyone is running the same playbook with the same democratized tools, making it nearly impossible to differentiate.
Secondly, conventional personalization — like sending a “Congratulations…” email based on a job promotion announcement on LinkedIn or similar — is now considered the “new generalization” in the AI era and no longer works. Marketers need to be far more creative in both their GTM stack and their approach to personalization.
Now it’s a speed-to-market game
Everyone has the same tools; it is no longer a tools game but a speed/systems game. Maybe we can coin the term “speed to market” (STM).
While the historic dropoff in deliverability and the declining effectiveness of conventional CRM systems were bad news for marketers, the good news is that a whole new slew of AI-powered tools have emerged. And they’re empowering marketers to shape and manage highly effective GTM pipelines at a scale and speed never before seen.
With the rise of AI, custom research and workflow automation have become much faster, so it’s easier to build, test and iterate. Speed-to-market tools such as Clay, n8n and Unify GTM enable marketers to automate workflows by combining AI capabilities with business process automation. Complex prospect-nurturing workflows that once would have required intensive code development and platform integrations can now be automated and managed directly by marketers without coding.
With these powerful capabilities, the most critical step in the GTM process becomes choosing the right intent signals to base action on. We call this approach GTM engineering, which depends on finding the right signal power spectrum to inform outreach: