The Value of Human SDRS Compared to AI

I was wrong. AI is not going to "kill the SDR" anytime soon. In fact, here’s two specific use cases where AI actually makes the SDR 10x MORE valuable: 1. DATA HYGIENE Some reports say SDRs spend as much as 40% of their time updating bad data and contact information from the CRM. AI coupled with web-scraping tools can integrate databases and information sources to create a MUCH MORE accurate view of an individual and help ensure that SDRs are connecting directly to relevant contacts a higher % of time. Revenue leaders like Kyle Norton at Owner.com are adamant they want SDRs with as high a connect rate as possible and Owner is executing on that premise in an industry (restaurants) that has historically low connect rates.  And yet, the unit economics powering the Owner(.)com machine are powerful and even with an SMB sale, the business can have SDRs supporting AEs. 2. TRUE PERSONALIZATION AT SCALE Over the past 10 years, we’ve been sold the idea of “personalization at scale” from the revenue orchestration and sales engagement companies.  But we knew it wasn’t really possible.  Sending the same email to 10,000 people using a mail merge to add their name is NOT personalization at scale. It’s just spam. But today, using AI tools like Copy.ai, you can create truly personalized messages, leveraging your contact’s entire online presence to write compelling messages that go deeper than where your prospect went to college or what their favorite hobby is. In this world, SDRs are still needed to oversee and orchestrate the campaigns and, of course, to have useful and meaningful conversations with a prospect who engages.  TAKEAWAY: Contrary to what I've said the last few years, the SDR is still here and the role is still valuable.  AI doesn’t REPLACE SDRS. It make the best SDRs MORE PRODUCTIVE.  

Last month, a Fortune 100 CIO said their company spent millions on an AI decision system that their team actively sabotages daily. Why? Because it optimizes for data they can measure, not outcomes they actually need. This isn't isolated. After years advising tech leaders, I'm seeing a dangerous pattern: organizations over-indexing on AI for decisions that demand human judgment. Research confirms it. University of Washington studies found a "human oversight paradox" where AI-generated explanations significantly increased people's tendency to follow algorithmic recommendations, especially when AI recommended rejecting solutions. The problem isn't the technology. It's how we're using it. WHERE AI ACTUALLY SHINES: - Data processing at scale - Pattern recognition across vast datasets - Consistency in routine operations - Speed in known scenarios - But here's what your AI vendor won't tell you: WHERE HUMAN JUDGMENT STILL WINS: 1. Contextual Understanding AI lacks the lived experience of your organization's politics, culture, and history. It can't feel the tension in a room or read between the lines. When a healthcare client's AI recommended cutting a struggling legacy system, it missed critical context: the CTO who built it sat on the board. The algorithms couldn't measure the relationship capital at stake. 2. Values-Based Decision Making AI optimizes for what we tell it to measure. But the most consequential leadership decisions involve competing values that resist quantification. 3. Adaptive Leadership in Uncertainty When market conditions shifted overnight during a recent crisis, every AI prediction system faltered. The companies that navigated successfully? Those whose leaders relied on judgment, relationships, and first principles thinking. 4. Innovation Through Constraint AI excels at finding optimal paths within known parameters. Humans excel at changing the parameters entirely. THE BALANCED APPROACH THAT WORKS: Unpopular opinion: Your AI is making you a worse leader. The future isn't AI vs. human judgment. It's developing what researchers call "AI interaction expertise" - knowing when to use algorithms and when to override them. The leaders mastering this balance: -Let AI handle routine decisions while preserving human bandwidth for strategic ones -Build systems where humans can audit and override AI recommendations -Create metrics that value both optimization AND exploration -Train teams to question AI recommendations with the same rigor they'd question a human By 2026, the companies still thriving will be those that mastered when NOT to listen to their AI. Tech leadership in the AI era isn't about surrendering judgment to algorithms. It's about knowing exactly when human judgment matters most. What's one decision in your organization where human judgment saved the day despite what the data suggested? Share your story below.

The AI SDR bubble just popped. Startup 11x allegedly faked their way to a $350M valuation by claiming $10M ARR (when they only had ~$2M). Suddenly, Silicon Valley’s $500M bet that AI will replace salespeople is looking disastrous. It's time to kill the fantasy of AI SDRs once and for all. For the record, this isn’t coming from an AI skeptic. I’m a believer. The first time I used ChatGPT, it felt like holding the iPhone in 2007. And today, real AI is transforming how we work. Faster research, smarter marketing, better code. But let’s not confuse “writing better words” with selling. My Chief Scientist said last week: “LLMs are amazing at producing believable BS at scale.” And that’s the point. Sales isn't about “believable BS.” If your job is just to generate words… sure, AI is a threat. Yes, it’s a tough time to be a junior contracts attorney. But if your job is to build trust, influence decisions, and lead change? You're safe. Silicon Valley doesn’t get this. They’ve poured over $500M into 32+ AI SDR startups. Hoping agents can do what humans do best. But great sales isn’t about the words. It’s about the connection. I don’t respond to cold emails that mention my college. But I’ll always engage when someone: - Gets my business - Asks real questions - Genuinely wants to help That can’t be automated. That’s human-to-human sales. And that’s exactly what these AI SDR companies forget. They’re selling magic beans. “Don’t hire reps—just plug in the AI. It’ll say all the right things.” But it doesn’t work. 11x raised almost $80M, but it's being said 80% of their customers churn within 90 days. Their traction? Mostly smoke and mirrors (even more meaningless words!) - and now lawsuits. Because when you rip out the human element from sales, it breaks. Good sellers don’t need saving from AI. They need to double down on what makes them irreplaceable: - Curiosity - Context - Connection - Conviction That’s how deals get done. That’s how trust gets built. AI can do a lot. But it can’t replace salespeople.

AI SDRs promised to revolutionize sales. What AI SDRs promised: - 24/7 prospecting without burnout - A steady stream of perfectly qualified leads - More time for sellers to focus on closing deals - Hyper-personalized outreach at scale - Free up sales teams for high-value conversations - Unique signals and triggers What AI SDRs delivered: - Spammy, robotic outreach that buyers ignore - High bounce rates and low engagement - Unqualified, low quality leads - More noise in inboxes, not more conversations - SDRs still overwhelmed, just in different ways - Commoditized and cheap signals The truth is this: AI SDRs were supposed to replace SDRs. But it didn't. It made their role more strategic than ever. Because getting meetings and building a real pipeline? That’s become the hardest—and most crucial—task in the entire sales process. AI can support SDRs. But it’s the SDRs who have the context, the creativity, and the ability to build relationships that move the needle. That’s why I’m more bullish than ever on the role of the SDR.

Six months ago, my son started as an SDR at LinkedIn. I’m afraid that job won’t exist in two years. It’s one of the most common entry points into the tech industry for non-programmers: a marketing + sales on-ramp that’s launched hundreds of thousands of careers. You learn how to hustle, pitch, and take rejection. It’s how you get your first shot. Last week Dario Amodei said that 50% of entry-level jobs will be gone in a few years. But I disagree. It's not that entry-level jobs are dead. They just won’t be recognizable. Let's take the example of SDRs: They currently spend 80% of their time doing things AI does better – personalizing cold emails, researching leads, booking meetings. That 80% will be gone. Tomorrow's SDRs will be doing the remaining 20%, the human stuff. Here’s what an SDR could look like by 2030: 1. AI Sales Analyst - Orchestrates a stack of specialized agents to surface buyer intent signals, then filters the noise / refines with human taste and expertise. 2. Customer Success Onboarder - Compliments the automated-avatar onboarding process, risk management and high-stakes conversations with customers. 3. Sales Ops Coordinator - Maintains the GTM stack by debugging workflows, training AI agents, and ensuring clean, real-time data flow. But here’s the real risk no one wants to say out loud: What if it takes 2 years to sunset the old SDR jobs, and 5 years to build the new ones? It's not a rhetorical question. We don’t know. And while everyone is fixated on job loss, almost no one is building the bridge. If even 100,000 entry-level sales roles disappear in that gap (and they will), that’s 100,000 careers stalled. Not from lack of talent or grit - but because the system failed to evolve fast enough to catch them. My advice: Don’t fight the end of the SDR job. Design what comes next.