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As the noise around AI in sales grows louder, it’s easy to assume every revenue leader is racing to automate their go-to-market motions. But recent analysis tells a different story—one grounded in pragmatism, not hype.
Our breakdown of goal prioritization from 50 sales leaders across organizations—from high-growth mid-market to multi-billion-dollar enterprises—reveals a clear trend: while AI is on the radar, it’s still enablement, culture, and predictable growth that win the day.
Here’s what we uncovered and what it means for Technical Sales teams looking to align with executive priorities.
Across all company sizes and roles, several strategic goals consistently ranked highest:
These are foundational, execution-focused priorities that reflect what every CRO wants: a scalable, repeatable revenue engine.
What’s missing? Forwardly disruptive AI goals like “AI agents running your sales team” or “automated commission structures” ranked low. Sales leaders are focused on what works now—not futuristic plays that lack a clear ROI.
These themes were reflected in stated objectives and projects (listed in order of frequency):
These projects reflect that traditional goals have stayed the same, even in an era of massive technological shift. Instead, leaders are somewhat open to new solutions to age-old B2B challenges.
Unsurprisingly, CROs, CSOs, and SVPs gravitate toward goals that support long-term growth through culture, alignment, and enablement. Their top-ranked initiatives remain people-centric and measurable.
Takeaway: Senior sales leaders are open to AI—but mostly in the context of where it strengthens existing systems, not when it disrupts them completely.
While underrepresented in the data, VPs, Directors, and Heads of Sales showed broader openness to innovation.
High rankings for AI-enabled tools suggest a stronger desire than higher-ups to test and adopt tech that helps their teams execute better—especially if it's easy to implement.
Takeaway: These leaders are the most receptive to emerging tools. They’re your internal champions for AI pilots and early adoption.
The sample of leaders in this analysis were disproportionately at larger companies, as opposed to start-up and scale-up organizations. However, among these, we were able to dive deeper to see differences by company size, as defined by annual revenue.
Companies <$2B in revenue are laser-focused on fundamentals:
AI interest exists, but goals like “Automating commissions” or “Scaling training with AI” were mostly ranked low. Adoption is cautious and driven by resource constraints. Ironically, SMB sales teams can see the greatest lift from incorporating AI agents, so more market education needs to occur to help these businesses make educated investments.
Larger enterprises showed the most consistent prioritization across:
They’re engaged with AI—but more selective:
Insight: AI interest scales with company size, but trust doesn’t. Larger orgs are watching—but not yet buying into full automation and AI.
So where does AI really fit in a practical and achievable sales strategy?
Winning AI Use Cases:
Lower-Priority AI Use Cases:
Sales leaders aren’t anti-AI—they’re anti-gimmick. They want tools that accelerate time-to-value and amplify existing efforts. They are reluctant at this early stage to rethink processes entirely or take action that will require extensive change management.
At Vivun, we believe Technical Sales is uniquely positioned to bridge the gap between what AI can do and what sales leaders actually need. By translating real buyer priorities into actionable product value, Sales Engineering teams are the strategic link modern organizations demand.
Median revenue: 2.2 billion USD
Company revenue range: 200 million to 56 billion USD
Median budget for sales initiatives: 10 million USD
Seniority: 18 VP-level, 16 C-level 15 SVP level, 1 Director/Head
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