AI is Breathing New Life Into Sales Enablement. Here’s How

EDITOR’S NOTE:  Because extended enterprise learning involves multiple disciplines and perspectives, we regularly invite learning technology experts to share their insights. Today, Pifini President, Brett Strauss, discusses how AI improves sales enablement outcomes.

Why does sales training often fail, even before reps apply it?

I’ve been in this business a long time, and I’ll tell you something nobody wants to say out loud: Companies waste a staggering amount of money on sales enablement that doesn’t work.

It’s not because the content is bad, the trainers are bad, or salespeople are bad learners. Training fails because of how it’s delivered.

For decades, the numbers have told a brutal story:

• In a well-known Xerox study, sales training participants forgot nearly 90% of content within 30 days.
• Other studies found that 70% of sales training was forgotten within 24 hours, with up to 90% gone in 90 days.
• More recent research concluded that after 120 days, 85-90% of programs had no lasting impact.

When this happens, sales performance suffers. In what ways? Consider these statistics from the 2026 Salesforce State of Sales Report:

• 52% of reps say traditional enablement doesn’t give them the skills they need.
• 75% think they’re more likely to hit their targets with a coach or mentor.
• However, 46% rarely receive feedback on conversations that matter.

Put plainly, companies spend an enormous amount of money teaching people things they won’t remember when they need those things most. This isn’t a content problem. It’s a delivery problem.

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If one-and-done training doesn’t stick, why is it still here?

The pattern is familiar. Your company onboards a new seller. You run reps through some product training. Maybe you deliver a refresh when there’s a launch, or a big workshop at the annual sales kickoff. And then? Nothing, until the next event.

This frustrates many enablement leaders, because everyone knows better. We’re all familiar with learning reinforcement. We know spaced practice beats a single session. So, why does this model survive?

Because historically, the right approach has been painful to scale.

It’s not practical for a live coach to join every sales call. A product expert can’t be standing by to answer every question from every partner at the moment it comes up. You can’t run personalized practice sessions every week for hundreds of reps across dozens of regions. And you certainly can’t expect every manager to sit down and review every call conducted by every seller.

No wonder sales enablement collapsed into events. They’re the only thing that scales with a team’s size and budget. But the forgetting curve takes a tremendous toll.

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Hasn’t AI solved this yet?

AI is everywhere now. And although it is showing significant progress, it still deserves some healthy skepticism. Here’s why:

• According to McKinsey, 88% of organizations regularly use AI in at least one business function. Yet, only about 39% are seeing meaningful bottom-line impact.

• Salesforce says 94% of sales leaders that use AI tools consider them essential to growth. Still, reps continue to spend 70% of their time on non-selling tasks.

There’s a reason for this gap. Thus far, most of what’s been sold as “AI for sales enablement” is a smarter version of the same old thing. AI tags your content library. It summarizes a call recording. And then it drafts an email.

Useful? Sure. But none of this addresses the root problem. On any given Tuesday, a seller on a call at 2 p.m. is alone with whatever they happen to remember from a workshop 6 weeks ago.

The question was never whether AI belongs in sales enablement. It does. The question is where in the sales cycle you apply it. And the wins I see right now are showing up in a very specific pattern.

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How does this new approach work?

The shift is simple to describe, even if it took a while to become possible. Stop treating sales enablement as a series of events and start treating it as a continuous presence with each seller through every stage of a deal.

This means training, coaching, and support don’t end when a rep completes onboarding. They show up again before, during, and after a call. And they return throughout the selling process, whenever the rep has a question.

Here’s what it looks like in practice, stage by stage:

1. Onboarding and foundational learning still matter, but they live in a smarter context

A modern sales enablement platform doesn’t end at course completion. It connects whatever someone learns to their certifications, as well as the content they’ll use in the field, and the coaching they’ll receive in the future. In other words, learning is the starting point, not the destination. (This is our vision at Pifini, so it’s the logic behind our enterprise learning platform.)

2. AI does the prep work

Before the call, AI briefs the seller on the account, the buyer’s history, the relevant playbook, and any objections that are likely to arise. Because the seller is informed in advance, they don’t need to improvise. This capability is far superior to traditional event-based training.

3. Practice happens on demand, not on a schedule

AI role-play lets sellers and partners rehearse real conversations with an AI buyer who raises objections, pushes back, and adapts to the product and persona. Reps can practice at their convenience — no coordinating with a manager or waiting for a workshop. With reinforcement available anytime between formal training sessions, learning becomes far more effective.

4. During a call, backup is available to the seller

A live call copilot listens, surfaces the right talking point, suggests responses to objections, and immediately presents product details whenever they’re needed. This frees the rep from having to recall prior training because the system delivers it on demand. (Although this may sound too good to be true, it is already available on the Pifini platform.)

5. After the call, feedback shows up fast

Every call is automatically scored against criteria that matter most. Reps get personalized coaching within minutes, rather than having to wait for a quarterly review when details have faded. And managers always have a timely, realistic view of what’s happening across the team. This means they no longer need to guess based on a handful of calls they happened to join.

6. Answers are always available

Reps immediately receive an authoritative response to whatever they ask about a product, pricing, competition, or process. This rapidly transforms partner programs because it eliminates the bottleneck where channel managers spend 80% of their time repeating answers to common questions.

7. Sellers also learn from each other

Peer learning is powerful stuff. So, rather than replacing it, AI makes it more visible. It surfaces what’s working across the team and routes the right insight to the right person, at the right moment, so they can move forward more efficiently.

8. The buyer experience is pulled in, not bolted on

A digital sales room turns the deal into a shared workspace: content, conversations, and next steps are all available in one coordinated space for the buyer and seller to navigate together.

9. Everything links back to business outcomes

Training scores, role-play results, call scores, and buyer engagement are all pulled together, so you can see the big picture. It’s not just about who finishes which course, but what is actually driving revenue. (In Pifini, the training impact analysis layer ties all the details together.)

Although I’ve described 9 elements in this process, keep in mind that they aren’t separate steps. This is really one continuous loop. A weak spot on a live call becomes the next role-play prompt. A winning behavior becomes coachable content for the rest of the team. All the pieces are deeply interconnected.

Practice feeds performance. Performance feeds practice. It’s a flywheel.

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When the full cycle supports sellers, what changes?

Every situation is different. But I can tell you what happens when the flywheel is working:

Reps walk into every call prepared to lead the conversation, instead of just winging it. They receive personalized help when and where it counts. In addition, they receive feedback while a call is still fresh in their mind (not weeks later when it’s too late to improve). And they build valuable skills through practice that plays out over time (which is the best way to reinforce learning).

New hires ramp faster, because the system carries knowledge that previously lived only in tribal memory. Channel partners (often the hardest group to train because you can’t control their calendar), get the same quality of support as your direct sales team. And managers are freed from unnecessary administrative work, so they can focus on their primary mission — to develop people.

The point isn’t to replace sales managers or trainers. It’s about giving them tools they can leverage in meaningful ways. When your learning system handles the first pass on every sales call, one good manager can coach many more sellers much more effectively.

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What does this mean for sales enablement leaders?

This isn’t about deciding whether to use AI. Almost everyone is already using it in some form.

The critical question is about whether you want to create business value. Are you using AI incrementally to improve existing event-based training with faster decks, smarter search, and prettier dashboards? Or are you fundamentally redefining sales enablement with a continuous presence that guides and reinforces sellers through every stage of the deal?

The first approach makes broken training a little less broken. The second addresses the forgetting curve where it actually breaks down: in the field, on the call, in the moment of need.

That’s where AI is starting to deliver on its promise. This shift is exciting. And it’s where sales enablement is finally becoming the revenue lever leaders have always said it should be.

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3 Key Takeaways

1. Most sales training is killed by the forgetting curve, not bad content

When 87% of what we teach vanishes within a month, the curriculum isn’t the problem. It’s the delivery model. Events alone will never beat the way the human brain forgets.

2. Until now, most AI was bolted onto the old sales enablement model

Faster content development, search tools, and summarized recordings are helpful AI improvements, but they don’t make a difference when sales reps are alone in the moments that matter. Much stronger business benefits are happening where AI provides a continuous enablement presence across the entire sales cycle.

3. The best model is continuous, not episodic

Onboarding, on-demand practice, pre-call prep, in-call support, post-call coaching, instant answers, and connected analytics. Together, these form one self-reinforcing loop. This is where measurable impact is showing up in seller ramp time, win rates, and overall partner performance.

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Frequently Asked Questions

Does AI-powered sales enablement replace sales managers and trainers?

No. It gives them leverage. The system handles the first pass on coaching, the routine questions, and the consistent practice. Managers and trainers focus on the higher-value work of developing people, addressing complex situations, and building team culture. Most managers tell me they can support significantly more sellers when AI carries the routine reinforcement load.

How is this different from AI features already built into major sales enablement platforms?

Most AI features in legacy platforms are layered on top of a content library or a learning catalog. They make existing functions faster. The shift I’m describing is different. It’s about whether a rep has support in the actual moments of selling, not just better tools for searching content between calls.

Will sellers and partners actually use this kind of AI-powered sales enablement?

Adoption is the real test, and that depends on whether the tools live where a seller already works and whether they make daily tasks easier. Pre-call prep, in-call assistance, and instant answers all pass that test because they save the seller time and reduce stress on every deal. Sellers use practice tools when they see the connection between practicing and winning more business. So, if your AI investment doesn’t pass that test, the adoption problem isn’t a tool problem.

Channel partners don’t work for us. How does this help them?

The impact is often greatest among channel partners. This is the hardest group to train because you don’t control their time or their calendar. With on-demand answers, on-demand practice, and the same call support your direct team uses, you remove friction that usually holds partner programs back. It also frees your channel managers from the constant grind of repeatedly answering the same questions.

What should we measure to know if this sales training method is working?

Course completion, alone, is not a useful measure. The point of enablement is performance, not attendance. So, look at ramp time for new hires and compare win rates for deals when reps used these tools, versus when they didn’t. Also consider partner-sourced pipeline, consistency of message across the team, and manager leverage (how many sellers each manager is coaching effectively).

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