At SaaStr + AI Summit 2025, Jason Lemkin and Kyle Norton CRO of $1B+ vertical SaaS leader Owner (where Jason is on the board) did a deep dive on AI in Sales today.
And where it will be very soon.
The AI-Native CRO: How Revenue Leaders Must Evolve or Risk Obsolescence
4 Top Learnings for Revenue Leaders
1. AI Curiosity Is Now a Firing Offense to Lack. By the end of this quarter, team members who aren’t genuinely AI-curious should be let go. This isn’t about being an AI expert—it’s about demonstrating active engagement with AI tools and genuine interest in how they can transform sales outcomes.
2. The 50/50 Team Is Coming Fast. CROs will need to manage teams that are 50% AI agents and 50% human by end of year. This requires entirely new management skills focused on systems optimization, not just people leadership.
3. AI Amplifies Performance Gaps Top performers will see exponential gains from AI augmentation while average performers struggle to adapt. The performance distribution in sales teams will become dramatically wider, forcing tough talent strategy decisions.
4. Revenue-Generating Time for Reps Can Hit 70-80% With AI. Companies are currently achieving 25-30% increases in revenue-generating activity time through intelligent automation. The goal is 70-80% revenue-focused work, compared to the traditional 20-30% most reps achieve today. This is one of Kyle’s top AI goals for his team.
The New Reality: AI Isn’t Coming, It’s Here
The uncomfortable truth that every CRO needs to hear: By the end of the quarter, team members who aren’t genuinely AI-curious should be shown the door. That’s not hyperbole—that’s the new competitive reality. Just talking about AI isn’t enough. They need to be using it to improve efficiency every single day.
Companies like Bamboo HR and Scale AI are already automating their entire sales and revenue operations using AI-powered customer conversation analysis. Meanwhile, others are seeing 3-4x productivity increases per rep through intelligent automation. The delta between adopters and laggards isn’t just growing—it’s becoming insurmountable.
At Owner, selling ~$10K ACV deals to tiny businesses that “don’t typically buy software,” the AI transformation has been mission-critical. They’ve increased revenue-generating activity time by 25-30% by automating CRM updates, note-taking, and pipeline management.
The CRO Hiring Playbook Has Forever Changed
The interview process for revenue leadership roles now at Owner includes a mandatory AI component. Candidates are evaluated on:
- What they’re actively doing with AI tools (not just awareness)
- How they’re implementing AI in their current stack
- Their genuine curiosity about AI applications (fake it ’til you make it doesn’t work here)
The goal isn’t to hire AI experts—it’s to hire AI-native leaders who understand that their role is evolving from people management to hybrid human-AI team orchestration.
The 70-80% Revenue Activity Target
The math is simple but transformative. Traditional sales reps spend maybe 20-30% of their time on actual revenue-generating activities. AI automation is pushing high-performing teams toward 70-80% revenue-generating time.
The ideal AI-augmented sales day:
- 4 demos
- 2 strategic follow-ups
- Healthy white space for pipeline generation and opportunity advancement
- Zero time on CRM hygiene, note-taking, or administrative tasks
But here’s the critical caveat: poor AI orchestration creates terrible customer experiences. Irrelevant automated emails and generic follow-ups can destroy deals faster than no automation at all. The customer journey must be thoughtfully architected, not just automated.
The Management Intelligence Revolution
The most sophisticated revenue teams are building “management intelligence layers”—always-on AI systems that provide rep-by-rep insights and proactive alerts when deals go off track. This isn’t about surveillance; it’s about coaching amplification.
When coaching becomes your number one activity as a CRO (which it should), AI becomes your force multiplier. The systems can identify coaching moments, surface deal risks, and provide data-driven insights that would take hours of manual analysis.
Specialization vs. Generalization: The Great Reshuffling
AI is blurring the traditional lines between self-serve, commercial, and mid-market sales motions. The result? More specialization in human roles, with AI handling the connective tissue between specialized functions.
Humans will focus on:
- High-value demos and discovery
- Complex onboarding and implementation
- Strategic relationship building
- Deal structuring and negotiation
AI will own:
- Initial qualification and nurturing
- Cross-sell signal identification
- CRM management and data enrichment
- Basic customer support and FAQ handling
The Performance Distribution Effect
Here’s what most CROs aren’t talking about: AI will dramatically widen the performance gap between elite and mediocre sellers. Top performers will see exponential gains from AI augmentation, while average performers may struggle to adapt and could find themselves displaced.
This creates a talent strategy challenge. Do you invest in upskilling your middle performers, or do you focus resources on amplifying your stars? The companies winning this transition are making tough choices about where to place their bets.
Contact Centers: The Canary in the Coal Mine
The contact center transformation is a preview of what’s coming for sales. Companies are already laying off 25-30% of support teams due to AI’s ability to handle tier 1 tickets. Some organizations are running 20,000+ AI-driven interactions across their customer base.
The delta between AI marketing claims and reality is still significant, but the trajectory is clear. Revenue leaders who wait for “perfect” AI solutions will find themselves managing teams that can’t compete on cost or efficiency.
The 50/50 Future: Managing Hybrid Teams
By end of year, successful CROs will need to manage teams that are 50% AI agents and 50% human. This isn’t science fiction—it’s operational reality for forward-thinking revenue organizations.
This requires entirely new management skills:
- Systems engineering mindset for AI agent optimization
- Continuous improvement processes for AI performance tuning
- Quality assurance frameworks for AI-human handoffs
- Performance metrics that account for hybrid productivity
The Digital SE Revolution
The next frontier? Digital Sales Engineers (SEs) that join every customer call. These AI agents will have complete product knowledge, proactively correct misinformation, and provide real-time support during demos and discovery calls.
This isn’t optional technology—it will become table stakes for B2B sales, just like CRM systems became non-negotiable in the 2000s.
The Lazy AI Approach Will Fail
Here’s what won’t work: hiring an agency to “handle your AI strategy” while you focus on traditional sales management. Recent LinkedIn polling shows only 2% of companies successfully implementing AI SDRs—because most take a hands-off approach.
Successful AI implementation requires:
- Weekly refinement and optimization cycles
- Continuous training and feedback loops
- Deep understanding of what each AI tool can and cannot do
- Active involvement from revenue leadership in AI system performance
The Challenger Sale Meets AI
The best-performing sales profile has always been the challenger—someone who can teach, tailor, and take control of the sales process. Here’s the reality check: AI can potentially do teaching and tailoring better than 90% of human salespeople.
This doesn’t eliminate the need for human sellers—it elevates the bar. The humans who remain will need to excel at the uniquely human aspects of selling: relationship building, complex problem solving, and strategic influence.
The CRO Evolution: From People Person to Systems Architect
CROs who are great with people but weak on product and systems thinking will struggle in this new world. The role is evolving toward infrastructure management and systems optimization, with people management becoming one component of a broader orchestration challenge.
The revenue leaders who thrive will combine:
- Traditional sales leadership and coaching skills
- Systems thinking and process optimization
- AI tool evaluation and implementation expertise
- Hybrid team management capabilities
The Competitive Advantage Window
Companies that move quickly on AI implementation can create sustainable competitive advantages, but only with continuous improvement commitment. The organizations that treat AI as a “set it and forget it” solution will find themselves outpaced by competitors who iterate weekly on their AI systems.
The window for competitive advantage is narrowing fast. Revenue teams that aren’t AI-native by 2025 will find themselves competing with fundamentally more efficient organizations that can invest more in marketing, product development, and customer success while maintaining superior sales productivity.
The Bottom Line for CROs
The transition to AI-augmented sales isn’t a future consideration—it’s a current competitive requirement. Revenue leaders have a choice: become AI-native quickly and expand their impact, or watch their roles diminish as more adaptable leaders take the reins.
The bifurcation is already happening. The CROs who embrace this transformation will see their influence and results grow exponentially. Those who don’t will find themselves managing increasingly irrelevant teams in an AI-first sales world.
The question isn’t whether AI will transform your revenue organization. The question is whether you’ll lead that transformation or be replaced by someone who will.
Kyle’s Top 3 AI Implementation Mistakes to Avoid
Mistake #1: The Lazy Agency Approach “Don’t hire an agency to handle your AI strategy while you focus on traditional sales management. Only 2% of companies successfully implement AI SDRs because most take a hands-off approach. You need weekly refinement cycles and deep involvement from revenue leadership.”
Mistake #2: Poor Customer Journey Orchestration
“Bad AI automation creates terrible customer experiences faster than no automation at all. I’ve seen irrelevant automated emails and generic follow-ups destroy deals. You must thoughtfully architect the customer journey, not just automate existing processes.”
Mistake #3: Treating AI as ‘Set It and Forget It’ “Continuous improvement is crucial for AI systems to reach their potential. Companies that don’t commit to weekly updates and refinements will find themselves outpaced by competitors who iterate constantly on their AI systems. There’s no magic solution—just consistent optimization work.”
