Many AI tools promise to automate the entire sales process, forcing leaders into a false choice: replace reps or ignore the technology. Craig Daly, Chief Revenue Officer at Nectar, argues for a third option. The most effective AI sales strategy is not about removing humans, but about making them more effective.
Drawing from his experience at Qualtrics and Podium, Daly offers a framework for using AI as a “bulldozer, not just a shovel.” This approach accelerates revenue while deepening customer relationships.
It provides a practical guide for integrating AI to validate your market thesis in hours and identify revenue lost to inefficient lead routing. You can also empower reps with behavioral forecasting and use AI-assisted personal touches that competitors cannot match.
Using AI To Validate And Sharpen Your GTM Strategy
Before deploying AI for outreach, the most significant gains come from using it to analyze your strategy. Craig Daly’s team uses AI to test core assumptions, ensuring they target the right markets with the right message. This turns weeks of manual analysis into rapid, data-backed decisions.
Using AI to validate your GTM strategy before execution prevents costly missteps and aligns your team around the highest-potential opportunities.
This upfront strategic work is the foundation of a successfulย market-driven revenue plan.
Ask AI Where Your Biggest Problems Reside
For Daly, AI’s first and best use is to challenge internal beliefs. Instead of relying on assumptions, his team uses large language models like ChatGPT to validate their go-to-market thesis. “We use AI a ton…more for validation,” Daly explains, “to make sure that we have the right messaging, the right teams, and the right customer profiles.”
They feed the models detailed prompts to confirm their ideal customer profile (ICP) and targeting strategy. By asking questions like, “Where are these problems most prominent?” and “What are the biggest challenges in these specific verticals?”, they can quickly confirm if their focus aligns with real-world market pain.
This approach ensures their sales team is aimed at high-potential segments from the start.
Optimize For Impact
Beyond validating the market, Daly’s team uses AI to optimize the machine itself. In one powerful example, they uploaded historical closing data for their account executives into an AI model to find the most profitable way to distribute leads. The model analyzed close rates by AE, deal size, and lead source to reveal the ideal routing path.
The result was a clear, data-driven directive. Daly recalls the model returned a clear, data-driven directive. “It quickly said, look, the most optimal path to drive and maximize revenues would have been if you waited your lead flow in said fashion.”
The AI-generated plan showed precisely how reallocating leads to AEs who were more proficient in certain segments could have generated several hundred thousand dollars in additional revenue in a single quarter. This high-impact optimization allows modernย Fullcast for RevOpsย teams to maximize revenue potential with existing resources.
“These things normally would’ve taken us weeks,” Daly notes.
Empowering Reps With Actionable AI Insights
Daly is adamant that technology should be an empowerment tool, not a replacement. “Back then I was using a shovel,” he says of his early career. “Tech today should just be an empowerment.”
The goal is to create a “super SDR” or AE who can achieve three times the output by leveraging AI for efficiency and intelligence.ย By automating low-value tasks like research and forecasting, AI gives reps more time to focus on building relationships and closing deals.
Turn Pre-Call Planning From Hours Into Minutes
One of the most immediate gains comes from automating pre-call research. AI tools now scrape the web and internal data sources to give reps a concise, relevant brief on a prospect’s business, their strategic priorities, and recent news moments before a call.
This efficiency creates a strategic advantage, allowing AEs to spend more time selling and less time on administrative tasks. It mirrors the kind ofย dramatic efficiency gains seen by companies like Udemy, which slashed its GTM planning time by 80% through intelligent automation.
Build A Smarter Forecast Based On Behavior, Not Guesswork
At Nectar, forecasting has moved beyond subjective predictions from sales leaders. “Our forecasting is purely AI-based,” Daly states. The system analyzes behavioral signals from conversation intelligence tools like Gong, looking at how reps manage (or mismanage) their pipeline, the sentiment of conversations, and patterns of engagement.
This data creates a more accurate, weighted forecast that proactively identifies opportunities and risks. The AI flags signals that are “indicative of a potential relationship that we’re gonna lose” or, conversely, those showing strong momentum.
That allows sales leaders to intervene where it matters most, coaching reps on at-risk deals or reinforcing promising ones. This behavioral approach provides a far more realistic picture of pipeline health than traditional methods, a key theme explored in the 2025 Benchmarks Report.
Where Authenticity Wins In An AI-Saturated World
As AI floods every channel with automated messaging, authentic human connection becomes a more powerful advantage. Daly argues that leaders should be wary of fully automated solutions. Instead, they should focus on an AI strategy that preserves the human touch where it matters most.
As competitors lean into mass automation, investing in genuine, AI-assisted personal touches creates a memorable experience that builds trust.
Why Cold Calling Isn’t Dead (And Is Getting Stronger)
Daly disputes the popular narrative that “cold calling is dead.” In fact, he sees its value increasing.
As email and LinkedIn inboxes become saturated with low-quality, AI-generated spam, the phone has become a less crowded and more direct channel. “I kind of hope everybody feels like cold calling’s dead,” he jokes, “because that just means there’s gonna be less calls and better ratios for my team to actually connect.”
His team sees strong connect rates and continues to invest in dialing, viewing the decline in calls from competitors as a strategic advantage. The proof is in his own purchasing behavior.
“I’ve bought technologies from cold calls in the last six months,” Daly admits. “I can’t think of emails I’ve bought from.” This is a powerful lesson fromย a CRO’s perspectiveย on what truly works in today’s market.
Innovate Your Outreach
To stand out, Daly’s team uses a unique, AI-assisted approach to a classic tactic: the handwritten note. After a prospect completes a demo, an automated system extracts key details and personal touches from the conversation. It then uses a robot with a real ink pen to write a personalized, seemingly handwritten thank-you card.
“We work with a partner that will curate a very specific handwritten note using robots, but the content is extracted from conversations that we’re having,” he explains. This strategy brilliantly combines the efficiency of AI with the high-impact, personal touch of a traditional note. It creates a memorable experience that demonstrates a level of care fully automated emails cannot replicate.
Build Cyborgs, Not Terminators
As Craig Daly makes clear, the goal of a modern AI strategy is not to build terminators that replace your team. It is to create cyborgs: humans augmented by technology to become smarter, faster, and more effective. This playbook shows how to use AI first as a strategic tool to validate your market thesis and optimize lead flow for maximum impact.
From there, AI becomes a bulldozer for your reps, automating research and creating behavior-based forecasts. This frees them to focus on building relationships, which in turn powers authentic human connection.
By embracing this philosophy, revenue leaders can build a go-to-market machine that is both technologically advanced and deeply human. To hear more of Craig Daly’s practical insights on building a winning revenue engine, listen to his full conversation with Amy Cook onย The Go-to-Market Podcast.
