AI and Automation: Smarter Adoption Strategies for GTM Teams That Don’t Chase Trends

Watch the full discussion on how GTM leaders are using AI to scale without losing the human advantage.

What’s the Real Opportunity of AI and Automation for GTM Teams?

AI only drives revenue when the underlying data, workflows, and guardrails are solid.

In B2B environments, where complexity, buying groups, and cross-functional handoffs matter, automation works best when it supports humans, not replaces them. That was the through-line of a recent conversation between Kristen Diamond, Head of Client Strategy at Wheels Up Collective and Phuong Pham, Senior Director of Marketing & Sales Development at JumpCloud.

This article breaks down Phuong’s most valuable insights: what AI is actually good for, why data quality is non-negotiable, and how GTM teams should prepare for 2026.

Why Data Quality Determines Whether AI Helps or Hurts

AI cannot outperform the quality of the data it’s fed. According to Phuong, AI initiatives fail most often because teams skip foundational work on enrichment, normalization, and workflow integrity.

“If your data isn’t structured, accurate, and consistent, AI tools cannot personalize, automate, or scale GTM flows effectively.”

During pre-Covid hyper-growth at Automation Anywhere, even strong tools like Marketo were bottlenecked not by strategy, not by creativity, but by data issues.

And now industry signals the stakes are higher than ever: AI in the marketing industry is projected to reach $47.32 billion in global revenue by 2025, nearly quadrupling from 2020. Heading into 2026, use of AI is nearly foundational.

How Smart Automation Scales Teams 

JumpCloud’s current approach is all about using AI to enhance, not replace, human capacity. Their BDR team doubled account coverage not by removing people, but by removing repetitive tasks. The result, according to Phuong: “Automation multiplies the impact of your existing team by removing repetitive tasks so people can focus on conversations, strategy, and creativity.”

This aligns with broader trends: 83% of marketers say AI frees up their time to focus on more strategic or creative work, according to Statista.

That’s what separates “just automation” from intelligent GTM strategy.

Why Guardrails Matter More Than Novel Tools

AI moves fast. But if you’re not building with security, compliance, and cross-functional alignment, your “innovation” becomes risky. 

Phuong shared how they mitigate this at JumpCloud with internal hackathons, clear “path to production” playbooks, and a realistic view of what tools like ChatGPT should, and shouldn’t, be used for.

What CMOs Must Get Right Going Into 2026

Phuong’s advice for modern GTM and marketing leaders?

• Obsess over retention and customer base health: Acquisition efficiency will continue to decline; expansion and retention will decide winners

• Build a stable operating foundation before adding tools: Shiny objects don’t fix system debt

• Invest in “systems thinkers”, not tool operators: GTM teams need people who can connect dots across Ops, Sales, and Marketing

And as AI and automation reshape how we work, that old 80/20 rule needs an update. Today, it’s closer to 60/40. According to Phuong, ”winning GTM teams in 2026 will balance bold experimentation with disciplined operational rigor.”

Which AI Tools Matter Most Right Now?

When asked for a “must-have,” Phuong pointed to Clay, but cautioned against tool-first thinking.

“Tools only create value when they’re aligned to a use case, backed by clean data, and integrated into cross-functional workflows.”

At WheelsUp Collective, we see this daily, and we help teams connect strategy to systems. If you’re evaluating your stack, use this curated list of 15 GTM Tools Quietly Powering Pipeline Strategies.

Key Takeaways

• AI only works when your data does

• Automation should scale humans, not replace them

• Guardrails make innovation safer and more sustainable

• 2026 GTM teams win on retention, systems thinking, and operational maturity

• Choose tools based on strategy, not hype

Final thought: The teams that win the next wave of AI aren’t the ones with the biggest tool stack, they’re the ones willing to test, refine, and experiment with intention. Strategy sets the direction, but experimentation builds the advantage.

FAQ

1. Why is data quality so important for AI in GTM?

Data quality is important for GTM because AI can’t correct messy, duplicated, or unstructured data. Its outputs are only as good as the inputs.

2. How does automation help BDR and SDR teams?

Automation helps BDR and SDR teams by removing repetitive steps like research, list building, enrichment, and routing. This frees reps up for actual selling.

3. What guardrails should companies put around AI?

In terms of guardrails to put around AI, companies should consider security, compliance reviews, usage guidelines, cross-functional alignment, and a clear “path to production.”

4. What GTM trends matter most heading into 2026?

The GTM trends that matter most heading into 2026 are: retention, customer health, systems thinking, operational excellence, and smarter experimentation.

5. What’s the best AI tool for GTM teams?

In terms of the best AI tools for GTM teams, Clay is powerful, but only when paired with a defined use case and structured data.