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AI is everywhere in modern sales organizations, embedded in prospecting tools, powering guided selling systems, and writing emails reps used to spend hours crafting. With all this automation, it's logical to ask: when will AI replace sellers themselves?
According to Gartner®, revenue teams shouldn't be alarmed, but they should be ready to adapt: "AI won't replace sellers, but it will assume a growing portion of sales activities, fundamentally reshaping the role of sellers."
That nuance is critical. Yes, AI is taking on routine tasks. But in complex B2B sales cycles, with long deal timelines, multiple stakeholders, and high-dollar contracts, humans are still essential. The shift isn't in headcount. It's in how we define and measure what great sellers do.
The most disruptive effect of AI on Sales won't be job loss — it will be metric loss. The performance KPIs we've used for decades are no longer fit for purpose.
AI Is Changing the Definition of "Seller Productivity"
Traditional productivity metrics, like number of calls, meetings booked, or pipeline volume, were designed in a world where humans did everything. They measured effort, not necessarily value.
That system breaks down once AI sales agents enter the picture.
According to Gartner, "Traditional sales productivity metrics will lose relevance, failing to capture the true value of human contribution."
In other words, if AI is handling outreach, qualification, and even negotiation for simple deals, then a rep's activity metrics no longer reflect their true contribution. A sales dashboard might show record-high email volume, but if 80% of those were AI-generated, who's actually performing?
Activity goes up. Revenue stays flat. And reps are left competing against a sea of AI-generated noise.
If CSOs don't adjust their metrics, they risk rewarding automation instead of value, and misidentifying who their real top performers are.
The Rise of EQ KPIs
We think a big takeaway from the Gartner 2026 recommendations isn't about tools. It's about people.
"By 2031, 35% of sales organizations will introduce EQ-related productivity metrics as a result of AI's role in the sales cycle."
For years, emotional intelligence (EQ) has been treated as a "soft skill": valuable, but hard to measure or reward. Now, it's poised to be a primary differentiator.
As machines take over more of the sales execution layer, human reps are left with the most complex, nuanced work in the sales cycle:
- Navigating ambiguity in enterprise buying committees
- Resolving conflict across stakeholders
- Building trust with skeptical champions
- Reading tone, timing, and context in sensitive negotiations
- Keeping high-stakes deals alive over long cycles
These aren't soft skills. They're survival skills. And they're measurable through buyer feedback, deal velocity, and qualitative indicators like objection resolution and buyer sentiment.
AI will do more of the doing. Humans will be measured on how well they lead, influence, and adapt.
AI Can Direct Decisions, But Humans Will Drive Deals
There's a clear division of labor forming in Sales.
AI Will Handle:
- Prospecting and outreach
- Lead scoring and qualification
- Routine negotiations
- CRM updates and task nudges
- In-the-moment advice on next steps and deal decisions
Humans Will Handle:
- Strategic messaging and relationship building
- Navigating complex buying dynamics
- High-stakes, custom deal structures
- Reading buyer signals and adapting in real time
Gartner projects that by 2028, AI will close 70% of sales cycles by automating prospecting, lead qualification, and negotiations.
That leaves human sellers responsible for fewer, more critical activities, ones that demand judgment, EQ, and strategic thinking.
The new productivity question isn't "How many activities did this rep complete?"
It's "How much faster and more effectively did this rep move the deal forward, with AI as their teammate?"
Sales leaders must now measure not just output, but orchestration: how reps use AI to reduce cycle time, improve buyer confidence, and accelerate complex deals.
Why Current Metrics Are Failing
At a glance, it may seem like your team is more productive than ever. CRM activity is up. Sequences are firing. Outreach is happening.
But something's off. Reps are disengaged. Forecasts are unpredictable. Why?
Because the metrics are misleading.
According to Gartner, "Traditional productivity metrics will no longer accurately reflect sellers' true contributions or distinguish high versus low performers."
The causes?
- AI-generated activity inflates CRM data, making it hard to distinguish human effort from automation
- Volume gets rewarded over impact, incentivizing busywork rather than results
- Coaching frameworks fall behind, prioritizing call logs over context and strategy
- Recognition is misaligned, leaving top reps invisible on dashboards
Sellers who feel unseen or misjudged lose motivation. High performers look elsewhere. And leadership continues optimizing against the wrong signal.
What the New Productivity Scorecard Should Measure
To thrive in the AI era, Sales organizations must replace their legacy scorecards with metrics that reflect what humans uniquely bring to the table.
New High-Value Metrics:
- Deal acceleration impact — shows how reps reduce friction in complex sales cycles
- Buyer engagement quality — moves beyond email opens to reflect genuine buyer intent and trust
- Objection resolution effectiveness — captures emotional intelligence and persuasion in key moments
- Stakeholder alignment success — reflects ability to manage internal and external complexity
- Strategic use of AI tools — rewards reps who know when and how to use agents to drive outcomes
New Sales Skills to Coach:
- Adaptive communication — tailoring approach to buyer dynamics
- High-EQ negotiation — navigating difficult conversations with poise
- Contextual storytelling — aligning solutions to buyer challenges
- AI collaboration fluency — using agents as partners, not crutches
We think Gartner emphasizes a fail-forward, experiment-driven culture — one where metrics evolve continuously as AI and human workflows mature.
How Sales Enablement Should Prepare for This Shift
Enablement has a critical role to play in the transformation of sales performance, not just supporting it, but leading it.
To prepare sellers for the hybrid AI-human future, enablement leaders must:
- Build EQ-first training: Soft skills need to become structured competencies — with frameworks, benchmarks, and practice scenarios
- Redesign competency models: Move away from activity-based rubrics and incorporate behavioral traits like empathy, adaptability, and collaboration
- Coach AI fluency: Help reps understand not just how to use AI, but when to trust it, challenge it, or override it
- Update onboarding and coaching: From day one, sellers should be taught the mechanics of how to work alongside AI during sales calls before, during, and after every conversation
Enablement won't just teach sellers to succeed. It will redefine what success looks like.
What Your Top Seller Looks Like in 2026
In 2026, your best sellers won't be the ones with the most activities in Salesforce.
They'll be the ones who:
- Navigate ambiguity better than their peers
- Understand the emotional dynamics of complex deals
- Move stakeholders toward consensus faster
- Use AI to amplify their insight, not automate their inbox
According to Gartner, "Top performers will be those who combine human empathy with AI-powered insights to deliver exceptional buyer experiences."
AI isn't replacing sellers. But it's raising the bar for what makes a great one.
Let us show you how Vivun helps Sales teams thrive in this new era, by reimagining performance, redefining success, and unlocking the full potential of your human and AI team. Discover how Ava helps you sell smarter, sell faster, and sell more with AI as your sales teammate.
Source: Gartner, Predicts 2026: Leading Sales in the Age of AI Contradictions, Sandhya Mahadevan, Melissa Hilbert, Dan Gottlieb, Wendy Butler-Mafuz, Alyssa Cruz, 4 November 2025.
GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.
