AI has disrupted GTM more quickly and more completely than anything we’ve seen before. I should know: I’ve been covering GTM tech disruptions as an analyst since marketing automation burst on the scene in 2008, and I’m old enough to remember when Salesforce.com was the new kid on the block. GTM AI is in a whole different stratosphere from the marketing and sales tech revolutions I used to get excited about.
In May of this year, my team and I surveyed 275 GTM leaders to understand their use of AI, and here’s what we found: two-thirds of B2B GTM teams are already using AI regularly. If we start the clock at the launch of ChatGPT in November 2022, that means AI has achieved over 50% penetration in three years. That’s really, really fast. To understand just how fast that is, consider that cloud-based apps took 13 years to reach 50% penetration among SMBs [CR1]. Industry analyst Scott Brinker sums it up: “In three years, GTM AI went from zero to ubiquitous. We’ve never seen a technology transform GTM work this quickly.”
With this level of adoption, there are three big questions to answer:
Where are we (really)?
Where are we going?
How do we get there?
Where we are: This is the era of AI-driven productivity. Embrace it
I acknowledge that the fact this transformation is moving so fast doesn’t necessarily mean that it’s working. Except that it is. Today, 40% of AI adopters are getting high impact, and most of that impact is coming from productivity gains.
92% of marketers using AI have seen increased productivity, largely powered by low-hanging-fruit use cases like drafting messaging (97% of AI adopters) and conducting research (73%). These tasks, though fairly simple for AI, were extraordinarily laborious and time-consuming for human teams. As Sydney Sloan, CMO of G2, puts it, “with AI, marketing teams are producing more assets in a single quarter than they used to in an entire year. Every campaign, every audience segment demands relevant and timely content, and AI has become the only way to keep pace.”
And the marketers aren’t getting all the fun: 87% of sales teams using AI regularly have already given meaningful time back to their reps. Just three years ago, Salesforce found that reps spend 28% of their time actually selling; AI is changing that [CR2]. Organizations have tackled the time consuming bottlenecks in sales rep efficiency by using AI to automate account research/scoring (88%), draft outreach/messaging (85%), and enrich prospect or customer data (84%).
Still, many commenters bemoan the perceived absence of ROI from AI adoption today. How can we square the fact that our teams are obviously getting more productive with the fact that many have yet to see impact on their board-level metrics? I think we can do so by recognizing three facts:
Translating efficiency into increased output or decreased cost requires change management, which itself takes time. In other words, there’s a lag at play.
We need new metrics at the board level: measuring efficiency properly requires ratios (e.g., net new ARR per GTM FTE) rather than absolute figures (e.g., net new ARR, GTM FTEs).
As Latané Conant wrote last week, automating entire workflows, rather than one-off activities, is the key to turning productivity into board-level impact. In our survey, high-impact adopters were using AI for twice as many use cases as low-impact adopters. Teams that increased productivity without seeing meaningful ROI have likely not yet woven AI throughout their core processes.
Nonetheless, it’s true that this first phase of GTM AI adoption has an indirect, rather than direct, impact on the metrics we care about most. That will change in the next phase.
Where we’re going: The next phase of GTM AI is about quality rather than quantity
If the current phase of GTM AI is about doing more with less (i.e., increasing quantity), the next phase is about doing better (i.e., increasing quality). In marketing, for example, doing better means using AI to power campaign analysis and account scoring; teams using AI for both use cases are 3x likelier to see increased pipeline volume and 5x likelier to see higher conversion rates.
Meanwhile, sales teams leveraging AI to coach reps and guide their next best actions at each stage in the deal cycle are 3x more likely to see higher win rates. Additionally, 22% of them have already increased their quota attainment. As Neil Harrington, Sales Leader at Lean Data, explains, “using AI to analyze our call transcripts, we’ve been able to dig deeper into our sales process and find the underlying issues that are holding us back.”
These are the sorts of quality-focused activities that directly move the needle. If you aren’t already pursuing them, seek them out and get started.
How we’ll get there: The GTM AI Playbook
Based the survey and the dozens of interviews my team and I have done with GTM leaders, we’ve put together an nine-rule GTM AI playbook to help you spin up your first use cases and/or graduate to new ones: