AI is everywhere. Every casual conversation, every business pitch, every LinkedIn post. But most revenue teams are still figuring out how to get real impact out of this technology.
That’s what we dug into during our virtual event, How Sellers Are Winning with AI. Showpad was joined by two experienced minds in the revenue space: Alex Wakefield, Chief Revenue Officer at medtech sales platform AcuityMD, and Morgan DUARTE, Global Commercial Excellence Leader at Schneider Electric, a digital automation and energy management giant. Together, we unpacked what it takes to move from AI hype to measurable, AI-powered revenue outcomes.
This wasn’t an hour of AI theory. They talked about what’s really working in the field: how to align AI to your sales strategy, how to train your sales teams to embrace it, and how to measure whether it’s making a difference.
Expect AI’s impact to be only as strong as your human-led strategy
One of the first things we aligned on was that AI isn’t a silver bullet. You can’t just plug in a tool and presume results. It has to be part of a larger revenue strategy.
Morgan put it plainly: “The companies seeing success with AI aren’t asking ‘How do we use AI?’ They’re asking ‘How do we sell better?’ and figuring out where AI fits into that.”
At Showpad, we recently conducted a global survey with the research firm Dynata, surveying nearly 700 revenue professionals across complex industries like manufacturing, medical devices, enterprise tech, and CPG. While 70% of sellers said they were excited about AI, only 39% were using it regularly.
Of sellers are using or are eager to use AI in their workflows
Of sellers are using AI regularly
That gap tells us most teams still haven’t nailed down where AI fits into their workflows… or what problems it’s actually solving.
Shift your focus from AI for automation to AI for elevation
The early use cases for AI in sales were mostly task-based execution such as meeting scheduling or follow-up reminders. Helpful. Not transformative. The best sales teams are figuring out how to use AI to finesse the sales motion, not just speed up the workflow.
What does that look like in practice? It means using AI to deliver smarter content recommendations based on buyer behavior. It means providing real-time coaching feedback that helps reps adjust in the moment. And it means helping sellers tailor their messaging to specific stakeholders, automatically.
Alex mentioned how they’re doing exactly this at AcuityMD noting, “We can highlight those AI insights to the sellers in an automated fashion… so when sellers have conversations with customers, they can be way more specific in what might be interesting and what might resonate with each decision-maker.”
When AI is deployed this way, it doesn’t just save time. It increases deal quality. It builds seller confidence. And, most importantly, it helps sellers show up as trusted advisors.
“This type of change is not something training alone can solve — it’s really the company culture.”
Morgan DUARTE
Global Commercial Excellence Leader, Schneider Electric
Skip AI change management at your own risk
Even the most promising inventions fail without the right attitude, and both Alex and Morgan made this crystal clear.
First, “AI is led in an organization… by setting it up with change management, creating the right mindset to adopt new technology,” Alex told us. Morgan echoed this sentiment noting, “This type of change is not something training alone can solve — it’s really the company culture that needs to evolve to be a lot more agile.”
Second, Alex emphasized the importance of leaning on internal champions. “You want to lean into your sellers that are innovative thinkers, early adopters, and those who are curious.” And it helps if they’re already successful, because when other sellers see top performers embracing AI, it sends a powerful signal.
And finally, Morgan suggested following in Schneider Electric’s footsteps, giving every rep access to AI tools with the expectation they’ll experiment with low-stakes tasks. His guidance? Don’t be afraid to let your revenue team tinker, but be smart and educate them on how not to share confidential company information or proprietary data. That low-pressure, high-curiosity approach helps reps build familiarity and confidence with AI before it becomes part of their everyday deal flow.
AI enablement is about cultural buy-in. You need sellers and managers who are empowered and excited to explore new ways of working.
Foster seller motivation (and retention) with AI
Morgan’s most compelling insight during the session had nothing to do with emerging technology and everything to do with seller motivation.
“When sellers are engaged in meaningful work that leverages their skills and expertise — not just updating the CRM — they’re more fulfilled, more motivated, and more effective,” noted Morgan.
It’s a simple idea, but a powerful one. AI can actually unlock purpose and performance. As an example, Morgan’s team at Schneider Electric has equipped more than 15,000 sellers with AI tools. But the company’s goal isn’t just scale. It’s impact.
By using AI to handle rote tasks like data entry and follow-ups, sellers can reinvest their time in what really moves the needle. They can focus on deepening customer relationships and broadening their networks. “It’s about making sure that time saved is reinvested into the business — whether that’s visiting more customers or expanding pipeline,” Morgan explained.
He also pointed out that this shift has another important effect: increasing seller autonomy. “Salespeople are becoming more empowered. They’re making decisions that used to be escalated [to sales managers]. AI is giving them access to better information, so companies can delegate more.”
When AI is applied thoughtfully, it makes your team more effective and more energized. That’s not just good for morale. It’s good for sales team retention and bottom-line performance.
"We didn’t just track usage. We tracked impact.”
Alex Wakefield
CRO, AcuityMD
Measure what matters with AI
A core moment from the session was when Alex talked about how his team aligns AI to performance metrics.
“We didn’t just track usage,” he said. “We tracked impact — time in each stage of a deal, competitive win rate, and deal size.” Alex’s example illustrates the need to connect the dots between AI usage and the outcomes the sales team cares about. Then, the conversation is no longer about AI adoption, it’s about business value.
That’s a key shift. If you’re not tying AI investments to clear sales outcomes, you’re going to struggle to make the case to your CEO and board about continued investment.
It also reinforces a broader truth: enablement is the bridge between great strategy and great execution. And AI, when used correctly, makes that bridge stronger.
The AI bottom line
If there’s one thing to take away from the conversation with Alex and Morgan, it’s this: using AI isn’t optional anymore. But using it well? That’s where the competitive advantage lies.
To recap:
- Start with a strong sales strategy, then figure out where AI can help.
- Use AI to elevate selling, not just automate tasks.
- Invest in AI change management early.
- Give sellers the space to do what they’re best at with AI.
- Measure AI’s impact, not just activity.
The future of selling will be shaped by teams who know how to combine the art of human connection with the science of AI’s speed and insights. That’s what we’re building toward at Showpad. I’m more convinced than ever that AI will not replace sellers. Instead, it will help every seller show up more effectively.
What the future of AI for field-selling organizations should look like.
By Showpad's CRO, Amanda Bedborough
Frequently asked questions
Start with your sales strategy, not the technology. Identify the specific challenges your team faces — whether that’s deal quality, ramp time, content relevance, or coaching consistency — and then figure out where AI can address those problems. Teams that start with “How do we sell better?” and work backward to AI get far more value than those who adopt AI for its own sake.
Adoption gaps usually come down to three things: unclear strategy (teams don’t know where AI fits), lack of change management (reps aren’t given the mindset or training to embrace new workflows), and no connection to outcomes (leadership can’t see AI’s impact on revenue metrics). Addressing all three — strategy, culture, and measurement — is what separates teams that get real value from AI from those still experimenting.
The best teams don’t just track AI usage or adoption rates. They tie AI to the metrics that matter: time in each deal stage, competitive win rate, deal size, pipeline velocity, and ramp time. When you connect AI investment to business outcomes, the conversation shifts from “Are people using it?” to “Is it driving revenue?” — which is the only conversation that sustains executive buy-in.
Effective AI change management starts with leadership setting the right mindset, not just rolling out training. Identify internal champions — sellers who are curious, innovative, and already performing well — and let them model what good AI usage looks like. Give every rep access to AI with permission to experiment on low-stakes tasks. And educate the team on responsible use, including how to protect confidential and proprietary information. The goal is to build familiarity and confidence before AI becomes part of everyday deal execution.
When AI handles rote tasks like data entry and follow-ups, sellers can reinvest that time in the work they actually signed up for — building customer relationships, expanding their networks, and closing deals. That shift from administrative burden to meaningful, strategic work increases fulfillment and autonomy. Sellers who feel capable and energized are more likely to stay and perform at a higher level.
In industries like manufacturing, medical devices, and enterprise tech, leading companies are using AI to deliver relevant content recommendations based on deal context, prepare reps with account intelligence before meetings, provide AI-assisted roleplay for practice, and connect training and content usage to revenue outcomes. The common thread is that AI supports the seller in the field — it doesn’t replace the human relationship that drives these high-stakes deals.
The biggest mistake is treating AI as a standalone solution rather than part of a broader revenue strategy. Plugging in AI without clear use cases, change management, or outcome metrics leads to low adoption and wasted investment. The companies getting real results start with the sales challenges they want to solve, build AI into existing workflows, and measure impact against revenue metrics from day one.