🎥 Watch the convo
Justin Hudon (Vasco) and Jacob Fleisher (Attention) brought frontline perspectives on the promises and pitfalls of AI in sales.
Prefer reading? Scroll down for a text summary.
1. The biggest day-to-day change for reps
The most immediate impact of AI is on efficiency and productivity. Routine tasks like follow-up emails or CRM updates, traditionally time-consuming and often dreaded, are now handled in minutes rather than hours. AI automates AND enhances: meeting summaries are more accurate, methodologies like SPICED or MEDDICC can be filled directly into CRMs, and reps can focus more on customer conversations instead of admin work.
The result? More time back in the day, higher-quality customer interactions, and a smoother onboarding process for both new hires and new customers.
“A 10 or 15 minute task now takes one or two minutes. Multiply that over five or six meetings a day, five days a week… that’s a lot of time saved, but also a lot more high-quality touch you’re putting in front of prospects.” — Jacob
2. Workflow wins vs. wrecks
Not all AI implementations have been smooth sailing. On the positive side, AI-powered prospecting and task orchestration have improved targeting and timing. At the same time, overreliance on tools like ChatGPT can backfire when tasks could be completed faster manually. Prompting, in particular, has become an art, and misuse can slow teams down.
Challenges also appear when adoption is left too open-ended. For instance, giving BDRs free rein to build their own account lists with AI can create inconsistency and inefficiency. A top-down approach to data enrichment and account prioritization helps ensure reps start with the right accounts and contacts, making AI much more effective at the top of the funnel.
"I've seen ChatGPT adoption get a little excessive. Sometimes it takes longer to write prompts and refine outputs than just writing the email manually." — Justin
3. Excited or fatigued?
Are reps tired of yet another wave of tools? Not quite. Most land somewhere between excited and skeptical. There’s enthusiasm for the productivity gains AI brings, but also hesitancy from top performers who wonder if new workflows really outperform their tried-and-true methods. Adoption tends to work best when AI integrates seamlessly into existing processes, rather than forcing reps into entirely new platforms.
"They're excited because the benefits of AI are great, but there's hesitancy from top performers — are they really going to rearchitect the way they've worked for 10 years?" — Jacob
4. The AI wish list
When imagining the “impossible” AI features of tomorrow, two pain points stand out:
- A self-updating CRM that automatically pulls structured data from calls, emails, and contracts, eliminating the need for manual input.
- An AI system that delivers a perfectly prioritized account list, enriched with context and signals, and even matched to the rep best suited to handle each prospect.
The industry isn’t there yet, but that’s the direction things are moving.
"Imagine an AI that not only builds your TAM but also prioritizes accounts with the right signals and even matches each to the rep best suited to handle them." — Jacob
5. What AI can’t replace
Despite the hype, some parts of sales remain firmly human. Business acumen and genuine curiosity during discovery calls are irreplaceable. AI can draft scripts, but it can’t replicate the thoughtful, real-time questioning that top reps use to uncover pain points.
Just as importantly, passion and energy still carry weight. Buyers respond to conviction, trust, and relationships: human qualities no algorithm can fake.
"Top performers use real-time questioning to uncover pain points. AI isn’t there" — Jacob
6. Buying AI tools
With new products launched daily, cutting through the noise is a challenge. Peer recommendations remain one of the most reliable ways to identify which tools truly add value. The real test is not whether a tool looks impressive, but whether it addresses a pressing business problem.
"There’s so much noise that I always come back to peer recommendations. If a tool is being used successfully by someone I trust, that cuts through faster than any ad." — Justin
7. HubSpot’s new ChatGPT plug-in: hit or miss?
Even with the hype, not every AI integration is ready for primetime. The new ChatGPT plug-in for HubSpot, for example, shows promise but struggles without the proper business context. Sales processes, lifecycle definitions, and go-to-market structures are often too nuanced for a generic AI layer to interpret accurately. Without clean, structured data, the output risks being more noise than insight.
"The issue is that ChatGPT doesn’t know your go-to-market structure or what actually defines an MQL or a sales-accepted lead. Without that business context, you’re not necessarily getting valuable output." — Justin
8. Predictions for 2026
Looking ahead, AI in sales is expected to become far more predictive and dynamic. Instead of surfacing generic best practices, tools will tailor insights to specific industries, buyer behaviors, and even rep strengths. AI will both support execution and help orchestrate creative, personalized engagement strategies that drive revenue.
"Instead of surfacing generic playbook items, it’ll give dynamic, contextual insights. Like, in the last five pharma deals CIOs got involved earlier, so maybe bring in the CIO now. Reps will execute at a much higher level." — Jacob
The takeaway
AI is already transforming sales workflows, from admin automation to smarter prospecting. But the real breakthroughs will come when AI systems can prioritize accounts with nuance, deliver predictive insights, and let reps focus on what only humans can do: building trust, asking the right questions, and selling with passion.
