AI in Sales Enablement

The skills your reps need today aren't the skills that got them hired. Every quarter the bar moves, and most training doesn't move with it. It just tells people what changed. It doesn't make them ready for it.

— Ken Lawshe, CRO at Synthesia

Gartner predicts that by 2029, sales organizations with AI-driven enablement will move through sales stages 40% faster than those still using traditional enablement methods.

This transformation likely isn’t going to come from implementing a tool (only 1 in 50 AI investments deliver transformational value).

It is going to come from transforming your sales enablement into an organizational capability that anticipates the needs of your reps, helping them keep up with the moving bar.

5 ways to transform sales enablement with AI 

When I ask people to describe sales enablement at their company, I often get a list of responsibilities. Things like onboarding new hires, facilitating product training, and supporting kickoffs or summits. Or I get a list of assets. Playbooks, competitive intelligence, dashboards and hubs (oh my). 

What they’re describing is a reactive function. One that responds to requests and supports the rhythm of the business. I’ve never heard sales enablement described as the performance driver of the business. Until AI.

If you're here because you want to use AI to transform sales enablement at your organization into a capability that changes behavior, here are five ways to do that.

1. Diagnose skill gaps ‍

I once led a training on root cause analysis for a group of sales reps because a VP was convinced that was why they couldn’t close deals. (Spoiler: it wasn’t.) Turns out the team was quite good at structured problem-solving. What they weren’t great at was active listening.

According to LinkedIn, only 14% of organizations can effectively identify skill gaps in their workforce. These organizations are building scalable systems to help anticipate their needs as the economy, and their industry, evolves. 

That could look like AI mining your data (things like job descriptions, performance reviews, or even patterns from top performers) to draft a new competency model for your sales org. Then, a member of the enablement team reviews the model to confirm it reflects what actually separates strong performers from the rest.

2. Catch the hidden signals 

If you're using AI to diagnose skill gaps, you'll need to complement that periodic work with ongoing analysis of rep interactions. This gives you insights into how reps are performing, and into the market.

If you notice a handful of reps constantly struggle with discovery calls, you can provide them targeted coaching. If the entire cohort is struggling, that's a reason to reevaluate your discovery call training. Similarly, if you notice a trend, like a spike in competitor mentions, it may be a signal that they've released a new feature or changed their pricing. Meaning you need to update your competitive positioning.

AI intelligence platforms, like Gong and Outreach, make this data collection possible by recording calls and generating transcripts and call summaries. You may consider using in-tool analytics to surface these hidden signals, or use an API to a business intelligence platform for more custom reporting.

This data collection may depend on how your reps sell, and your industry. If your reps are selling in-person, that data collection may depend upon a manager's observations or a recording of the interaction. There are emerging AI tools designed for in-person sales.

3. Keep content up-to-date 

It’s a tale as old as workplace learning. You design a training, get it localized, deliver it, and then, something changes. A product is re-named (and re-named, and re-named). A tool is swapped out or a workflow changes, and that leaves you sitting on stale content. The old version is still circulating until you can revise it, leaving reps providing outdated pricing or missing feature updates. 

AI-training tools, from AI-native learning platforms to AI video platforms, have redefined what it means to keep content current. With AI assistance, you can quickly identify what needs to be changed in an eLearning, review, and publish a new version.

You can also consider creating internal agents that track your content library, and regularly scan company knowledge (e.g., messages, wikis, newsletters) to flag when you may need to update training.

If you’re interested in seeing how a real organization transformed their sales enablement through AI video training, read more about Druva. 

4. Surface the right assets

Employees are not searching for training materials in an LMS or enablement content platform when they’re preparing for a call. They’re going to an LLM or other AI agent, asking a question, and getting a response. Lean into this. 

Confirm your enablement resources (playbooks, slides, videos, onboarding materials) can be surfaced by your internal AI search and delivered in the flow of work. That doesn’t necessarily require a sophisticated API integration, but well-structured materials. Anything you produce should have metadata: titles, keywords, and descriptions. If a rep asks an LLM, “how do I handle objections?” you want the LLM to recommend your one-pager titled “Handling Objections”. 

If your content lives in a tool that doesn't integrate with an LLM, reconsider your approach to content management. Leave anything that needs to be tracked for evaluation in the platform, and move additional resources (or links to them) into sales tools, shared drives, or wikis. Anywhere they're more likely to be used. Just don't forget to deprecate outdated material.

It isn't an ideal solution, but bring AI compatibility up the next time you're considering renewing any content management tool.

5. Scale coaching without managers  

Managers are often responsible for coaching and providing feedback to their reps. The problem is, managers are swamped, leaving reps with few opportunities to practice important conversations. (And that's not to mention that, in my experience, most managers are inconsistently trained on how to coach and give feedback.)

That's why teams are turning to AI agents to scale coaching. These range from simple agents that provide tips based on a buyer's profile to AI avatars that provide real practice to reps.

Depending on how your reps sell, there may not be a post-call AI coaching solution available, at least yet. Consider scaling practice and feedback with AI, and save post-call feedback for managers. You can still design an agent to automate call transcript reviews, and provide a summary, and even coaching tips for managers before their 1-on-1s.

Why invest in AI coaching 

The old way of ramping a rep was: hand them a deck, hope they retain it, and find out what they missed the hard way, on a live call. With AI coaching, they practice the actual pitch, get coached in real time, and walk into real conversations having already made their mistakes somewhere safe.

— Mollie Sonnenberg, Head of Revenue Enablement at Synthesia

Most teams start their sales enablement transformation focusing on the diagnostics and operations layers. Those are natural places to incorporate AI. In my experience, those layers, even in new sales teams, are more likely to already be data-driven. Scaling coaching without managers isn't as simple. (There's a reason exec coaches can still command such hefty fees; a good coach can be invaluable to a leader.)

First, you need to make sure there's a shared foundation for all coaches. That means teaching, and then modeling, what good looks like in specific scenarios. Then, you need to give a rep a chance to try that out before giving them actionable and objective feedback. And finally, the rep needs to try again, immediately implementing that feedback.

That's the loop: learn, watch, practice, get feedback, try again.

Meet Roleplay Sessions

If your reps aren't practicing with you, they're practicing on your customers. 

— Will Eves, Senior Director of Sales at Synthesia 

Synthesia has spent nearly a decade supporting sales enablement. But we know that's not enough to drive learning transfer. For that to happen, reps have to have the opportunity to build and practice skills.

That's why we've built Roleplay Sessions into our platform. Roleplay Sessions closes the loop between knowing and doing.

Here's how it works.

1. Sales enablement partners with our experts to design a compelling scenario, like how to cold call, tailored to your organization.
2. Reps jump on a call with one of our AI avatars, practicing the cold call. Our interactive avatars don't just repeat a canned script. They push back, ask follow-up questions, and listen (unless reps are talking too much, in which case the avatar lets them know they're wasting its time). Just like a real cold call.
3. AI coaches ask reps to assess how the call went before delivering an overall score, plus a breakdown of how they performed across the skills being practiced.
4. Reps try again, immediately, or whenever they want to practice building their skill.

If you’re wondering, yes, reps do opt into more coaching. In a pilot with a Fortune 10 company, 68% of reps returned for repeat practice. Voluntarily. 

Don’t just take my word for it. In Deloitte’s 2026 Global Human Capital Trends report, they reported that 80% of workers agreed an AI coach that provides real-time guidance, feedback, and support would help them navigate and adapt to change. 

How to prioritize AI in your enablement plan 

It is easy to get carried away with integrating AI into your sales enablement plan. You read a list like the one above and think, "I should do all of these things." I would advise against that.

Sales enablement teams are facing resistance when it comes to the proliferation of tools in their team's tech stack. Nearly half of sales reps say they're overwhelmed by the volume of tool sprawl, especially since they're managing an average of 8 tools.

Unfortunately, sales enablement often has little control over that. You likely rely on tools managed by your sales operations (e.g., a CRM, an intelligence platform), IT (e.g., an LLM, productivity suites), and L&D (e.g., an LMS/LXP). Each of these tools likely has "AI," whether that's agents added onto a legacy product or an AI-native platform. 

What you do have control over is how, and when, you add to that list, which is why I recommend asking two questions before incorporating any new AI tool: 

1. Is this tied to your strategy and roadmap?
2. Is this feasible with your existing tech stack or do you need to acquire a new tool (if so, ask a few more questions)? 

I'm not saying you can't add to your roadmap or tech stack, but I encourage you to scrutinize your decision to do either. If you're adding to your roadmap, what can be deprioritized or realigned? If you're adding to your tech stack, is there a way to consolidate the tools you use?

The "best" enablement plans aren't the ones with the most AI. They're the ones using AI strategically to close the gap between what your reps know and what they can do.

Synthesia makes it so you don't have to choose between a tool that closes the loop and adding to tech sprawl. Schedule some time with our team to see how our platform can support your enablement transformation.