Artificial intelligence in sales has moved from a talking point to a dividing line.
In 2025, the companies that succeed with AI are pulling ahead rapidly, while those stuck in experimentation risk falling behind.
What separates the winners from the rest?
Simply driving user adoption is no longer the answer. Instead, teams that win with go-to-market (GTM) AI are the ones with a go-to-market AI strategy rooted in quality data, workflow integration, and measurable outcomes.
How AI is Used in Sales Today
ZoomInfo’s 2025 State of AI in Sales & Marketing Survey shows just how real the gains have become. Frontline professionals using AI report a 47% productivity boost, saving 12 hours per week by automating repetitive tasks
Sellers using AI weekly or more frequently also achieve significant performance improvements: 73% report larger deal sizes, 78% shorter deal cycles, and 80% higher win rates
The takeaway is clear: AI in sales is no longer a side experiment. It is an engine of efficiency and revenue growth.
Adoption among GTM teams is also strong. McKinsey found that business use of AI tools nearly doubled in just one year, with sales and marketing teams standing out as the most enthusiastic adopters.
Why AI in Sales Doesn’t Always Pay Off
But if AI’s potential in GTM is so powerful, why aren’t all companies seeing results? MIT’s State of AI in Business report points to what it calls the GenAI Divide. Despite $30-40 billion in enterprise investment, 95% of businesses report little or no measurable return on AI.
Tools like ChatGPT are widely piloted, with over 80% of companies testing them and nearly 40% deploying them. But most implementations plateau, enhancing individual productivity but failing to show P&L impact
Only 5% of companies studied by MIT have successfully scaled AI pilots into production systems that deliver millions in measurable value.
The difference isn’t model quality or regulation, researchers conclude, but approach. Businesses that succeed use AI that is grounded in a core of trustworthy data, learns from new information, and integrates into revenue workflows.
Meanwhile, those chasing flashy tools simply stall.
How to Translate AI Adoption into GTM Growth
Frequent sales AI users report the strongest gains. ZoomInfo’s survey found that frontline adoption is highest among younger professionals, who are embedding AI into daily workflows through chatbots, CRM assistants, and email drafting tools.
The payoff is clear: improved prospecting, better client relationships, and faster deal velocity.
But the MIT report cautions that most companies are still on the wrong side of the divide. Only two industries (tech and media) show meaningful structural disruption from AI, while seven others, from healthcare to financial services, show limited impact despite heavy investment.
The gap, MIT concludes, is one of specialization.
The most popular, easiest to use, and flexible AI tools on the market are built for mass adoption and broad applications. But they can’t retain enough context, learn from new specialized inputs, or integrate with enterprise systems well enough to drive meaningful business results.
Home-brewed AI sales tools face the opposite problem: While they may be more purpose-built, users crave the ease and functionality of consumer apps they’re used to.
Building a Go-to-Market AI Strategy That Delivers
To succeed with AI in sales, leaders must look beyond raw adoption to build a go-to-market AI strategy that scales.
The data points to four priorities:
1. Target high-impact sales use cases first
Prospecting, lead scoring, email generation, and forecasting consistently deliver early wins. These are the functions where AI is already tied to measurable revenue lift.
2. Invest in clean data
A separate MIT study found that poor data quality costs businesses up to 25% of potential revenue, even without the amplifying effects of sales AI tools. Without accurate inputs, even advanced AI models underperform.
3. Embed AI into daily workflows
Adoption spikes when AI is delivered inside the tools that sellers and GTM teams use to get their work done. MIT’s research reinforces this: successful companies demand process-specific customization and integration into existing systems.
4. Confront risks head-on
Trust and accuracy remain barriers, cited by 80% of non-users in ZoomInfo’s survey. MIT echoes this, finding that most enterprises stall because AI tools don’t learn or retain context. Building governance to address these risks is essential.
ZoomInfo Copilot: Proof of a Winning GTM AI Strategy
ZoomInfo Copilot illustrates how a well-designed go-to-market AI strategy produces results. Customers report:
43% increase in total addressable market
41% higher win rates
83% larger deal sizes
30% faster deal cycles
These outcomes align with MIT’s conclusion that real ROI comes when AI is embedded in workflows and designed to adapt over time.
The Road Ahead for AI in Sales
Sellers using AI effectively are more productive, close bigger deals, and win more often. But too many companies are still falling short.
That gap is not from slow adoption or overhyped technology, but rather a lack of specialized applications that leverage trustworthy data, respond to new information, and embed in critical daily workflows.
For sales leaders, the choice is clear. Will your team remain stuck on the wrong side of the GenAI Divide, or will you build a go-to-market AI strategy that delivers measurable revenue growth?
The companies prioritize trusted data, integrated workflows, and a commitment to scale will define the next decade of sales success.