Will Spendlove, VP of Product and Solutions Marketing at Alteryx, joins host Amy Cook on the Go-to-Market podcast to share why the AI SDR debate misses the point and how career longevity comes down to grace, not grind.

“AI models don’t understand human emotion. They don’t understand the nuances of an emotion.” – Will Spendlove

The AI SDR Question Everyone Is Getting Wrong

The debate is everywhere: AI SDRs will replace humans, or AI SDRs will fail spectacularly and we will return to all-human teams.

Will sees it differently. The answer depends entirely on whether the buyer requires personal touch.

“If a customer didn’t want that engagement, they wanted it to be more challenger selling type of a model, the model would have to understand how to modify the way that it’s engaging with a customer in order to do that. And I think that’s really complicated.”

Current AI assistants default to positive reinforcement. They tell you your questions are smart. They validate rather than challenge. That works for some interactions, but it falls apart when buyers need a real conversation.

“Unless you tell it, don’t do that, do not give me that, actually challenge me, it’ll just automatically give you a positive response.”

The nuance required for challenger selling, for reading emotional cues, for knowing when to push and when to listen, that is where AI still falls short.

Human Connection Cannot Be Automated

Will shared a story about a friend who takes inbound calls for a retirement services company. Many callers do not need product information. They need someone to listen.

“A lot of the inbound calls, they just need to talk because they’re at their retirement age, and they need a person to listen to them. Oftentimes they’ll spend five minutes just talking about their grandkids.”

That conversation does not look like pipeline activity. But it directly impacts customer success scores and retention.

The insight is simple: some of the most valuable sales and service interactions cannot be measured by call efficiency metrics. They require a human who can recognize what the buyer actually needs in that moment.

Data Democratization Is the Real AI Opportunity

Rather than replacing people, the strongest use case for AI is removing barriers between business users and their own data.

Alteryx has spent 25 years helping non-technical users pull analytics from complex systems without needing SQL or Python expertise. AI accelerates that mission.

“A sales leader could just go into ChatGPT and say, what are my highest performing territories? Or they could ask which reps are the most effective, or where’s the highest risk of churn?”

The key is injecting company-specific data and business logic into LLMs so they can answer questions that matter, not just generic queries from public training data.

“It doesn’t have the business logic. It doesn’t understand your policies, it doesn’t understand your specific data. We’re able to take that, make it into a usable data set and then inject it back into a LLM.”

Rev ops teams still control permissions and governance. But business users can self-serve without waiting for IT or requesting custom reports.

Partnerships Work When You Focus on Jobs to Be Done

Will emphasized that the best partnerships come from breaking down specific use cases rather than running generic sales plays.

“Rather than just sort of randomly coming with marketing or selling sales plays, it was like, let’s look at a really specific use case or job to be done and figure that out. It just made it so much more tangible for a customer.”

That means asking: what is the job description of an SDR? What happens after a lead is handed off? Where do deals actually stall?

When both sides share that operational understanding, partnerships move faster and produce better outcomes.

Longevity Comes From Grace, Not Grind

After decades in marketing leadership, Will credits sustained performance to something simple: positivity and giving people the benefit of the doubt.

“Having a big picture view of my career, having a big picture view of my role, having clear understanding of what success looks like, and knowing that there’s a really good chance I’m never gonna hit what I believe is perfection.”

That mindset extends to teams and organizations. Mistakes are part of the process. Grace creates space for people to recover and improve.

“Giving myself and my team and my organization grace to make mistakes or stumble, and knowing that that is part of the process, really to me, has helped me to continue to drive not only myself, but my career and my teams.”

Final Thoughts

AI will handle more repetitive SDR tasks. Chatbots will take inbound inquiries. Workflows will automate list building and first outreach.

But the deals that require trust, the buyers who need to be heard, the moments where emotion matters more than efficiency—those still need humans.

Use AI to democratize data access and remove low-value manual work. Keep humans where nuance, empathy, and real conversation determine the outcome. And if you want a long career in go-to-market, lead with positivity and give your team room to grow.