Just-in-Time Enablement in a World of AI: How Top Teams Learn Faster, Execute Better, and Win More

If you lead a revenue team today, you feel the tension. Product updates move weekly. Processes change daily. Buyers expect precision and speed. Yet the average rep still spends large chunks of time looking for answers, confirming whether content is current, or waiting on a manager to weigh in. The gap between what teams know and what they can actually apply in the moment is where deals slow down, errors creep in, and confidence dips.

Most leaders respond by adding more software or by shipping more training. That solves the wrong problem. The constraint isn’t access in a general sense. It’s access in the exact moment of need. The true blocker is friction inside the workflow. The solution is not more destinations. It’s smarter delivery in the flow of work.

That’s the promise of just-in-time enablement. It’s also why Spekit co-founder and CEO, Melanie Fellay, wrote the book on it. Now, any team can turn knowledge into execution without the clutter. 

If you want the book, along with free templates and guides, grab your copy here.

What just-in-time enablement really is

Just-in-time enablement is a system for delivering the smallest useful unit of guidance at the moment of application. It lives inside the tools your teams already use. When a rep opens an opportunity, drafts an email, or reviews a call, relevant guidance, talk tracks, or assets appear right there. The content is short, current, and tied to a task or decision.

Four principles define it:

1. Context before content: Reps shouldn’t hunt for resources. Signals from the workflow determine what shows up. Opportunity stage, buyer persona, product line, region, and even the language of an email can inform which content is surfaced.

2. Small, current, trustworthy: Knowledge is packaged into bite-sized, version-controlled cards that are easy to scan and easy to update. If the system cannot keep content fresh, trust erodes and usage falls.

3. Reinforcement over recall: Adults learn by doing. The goal is not to memorize a handbook. The goal is to repeatedly encounter the right prompt at the right time until the behavior sticks.

4. Closed-loop measurement: If enablement does not connect to outcomes, it becomes guesswork. Just-in-time systems attach engagement and usage to pipeline stages, conversion points, and revenue impact so leaders can double down on what works.

This isn’t a new set of slides. It is a different operating model.

Why legacy learning breaks in modern workflows

Traditional sales training assumed long sessions, fixed paths, and portals. That approach struggles in three predictable ways:

• Decay: People forget quickly when learning is detached from doing. A kick-off in January rarely helps with an objection in March.
• Destination drag: Opening another tab to search a repository breaks focus. Each switch costs time and attention, which lowers adoption and consistency.
• Staleness: When content lives in multiple places, versions diverge. Teams lose trust. Double checks multiply. Execution slows.

In a change-heavy environment, those frictions add up. The cost isn’t only time. It’s unpredictable performance. A few people keep mental maps. Everyone else compensates with extra work or extra pings. Neither scales.

AI’s role: from search to guidance to orchestration

AI inside enablement is most valuable when it reduces friction at three layers:

1) Retrieval: Natural-language questions should return precise, source-linked answers from your corpus. The assistant knows terms like AHT or ACV because it is grounded in your content and policies. This reduces guesswork and follow-ups.

2) Recommendation: Proactive suggestions based on what the rep is doing outperform generic search. If an email references pricing for a specific product in a specific region, the assistant can surface the relevant pricing sheet, a short talk track, and the right case study without a query. These turn enablement into a pull-when-needed and push-when-relevant system.

3) Orchestration: The most advanced teams let AI handle micro-workflows. Think curating a buyer room with the latest assets, drafting a follow-up that cites the exact paragraph a buyer viewed, or alerting a manager when a pattern of questions hints at a process gap. These are small steps, but across dozens of moments per rep per week, they compound.

The aim isn’t to replace human coaching. It’s to free up humans to coach where it matters and to let the system carry the repetitive load.

Personalization, not portals

Horizontal copilots are helpful for general tasks, yet they often miss what makes selling hard inside your company. Your best reps perform well because they know how your products map to your segments, which proof points resonate for a given persona, and which red flags appear at certain deal stages. That context is local and specific.

A just-in-time assistant should reflect that specificity. It should know that an enterprise RFP in healthcare requires a different path than a mid-market upsell in education. It should understand your approval policies, your objections, and your regional nuances. Personalization here isn’t novelty. It’s essential for reliable execution.

Practical markers that personalization is working:

• Recommendations feel relevant to the task at hand
• New hires ramp faster without constant hand-holding
• Tenured reps still “opt in” because they gain speed, not steps
• Managers spend less time re-explaining and more time improving the system

When the experience feels like a capable partner, adoption becomes the default.

Onboarding, everboarding, and the memory problem

Onboarding can’t cover everything. Even the best programs flood new hires with information that fades without use. The fix isn’t more material. It’s better timing.

Onboarding should establish foundations, show people how to self-serve in the moment, and set expectations for how guidance appears in their tools.

Everboarding continues daily. Short reinforcements appear when a rep changes a stage, opens a product in the CRM, or schedules a call with a new persona. If a policy changes, the system nudges the right audience with the smallest useful update and a path to practice it.

The result is less re-training and more consistent application. People remember what they use. So we help them use it.

Measuring impact: from activity to revenue signal

If you want executive support, connect just-in-time enablement to outcomes leaders already value. Three categories tend to resonate:

1. Speed and productivity: Time to answer. Minutes of handle time saved. Questions deflected. Hours of manager time reclaimed from fewer ad hoc pings. These add up quickly across a team.

2. Quality and confidence: Error rates. First contact resolution. QA scores. Consistency of talk tracks and process adherence. Fewer surprises mean a better buyer experience.

3. Revenue signal: Asset influence on stage progression. Buyer engagement is tied to pipeline and closed-won. Win rate deltas where guidance is adopted versus ignored. This moves the conversation from content views to content value.

Leaders don’t need perfect precision on day one. Directional proof that an assistant reduces time waste and moves deals forward is enough to green-light more investment. The sophistication can grow as your data matures.

A maturity model you can use next quarter

You don’t need to boil the ocean. Use a four-stage path and move one level at a time.

Level 1: Centralize and clean

• Consolidate scattered docs into one trusted source
• Convert long artifacts into short, versioned, searchable cards
• Set review cadences and owners so content stays current

Level 2: Deliver in the flow of work

• Surface guidance contextually in CRM, email, and sales tools
• Replace long messages with alerts and bite-sized updates
• Track usage by role and moment to locate friction

Level 3: Add AI retrieval and recommendations

• Ground answers in your content with clear citations
• Let AI recommend the next best asset based on real signals
• Teach reps to ask questions in natural language and to rate answers

Level 4: Orchestrate and optimize

• Automate micro-workflows like curating buyer rooms or drafting follow-ups
• Tie buyer engagement to pipeline and revenue
• Use analytics to retire low-value content and to expand what works

The distance from Level 1 to Level 2 is where most of the early ROI lives. Reps experience less friction. Managers see fewer interruptions. Confidence rises fast.

A 30-60-90 plan to launch JIT enablement

Here’s a pragmatic plan any enablement leader can adapt.

Days 1 to 30: Foundations and focus

• Map the work. Sit with five reps. Shadow real calls or emails. Note exactly where they pause to look for help.
• Choose two journeys. For example, stage progression from discovery to evaluation, and the top support issue by volume.
• Deconstruct content. Split long docs into small, named cards with clear owners and review dates.
• Pilot delivery. Surface the relevant cards inside your CRM and email. Add a simple “Was this helpful?” control.

Days 31 to 60: AI answers and reinforcement

• Ground the assistant. Connect your clean corpus so natural-language questions return precise, source-linked answers.
• Seed recommendations. Use signals like opportunity stage, product, and persona to push the right content at the right time.
• Instrument the loop. Track time-to-answer, questions deflected, and content usage by moment.
• Reinforce changes. Ship alerts and “save for later” summaries that respect attention.
  

Days 61 to 90: Scale and tie to outcomes

• Automate micro-workflows: Auto-create a buyer room from a stage change. Draft a follow-up that cites the exact asset a buyer viewed.
• Connect to pipeline: Attribute content and buyer engagement to stage progression and influenced revenue.
• Retire and promote: Archive stale cards. Promote the short list that consistently moves deals.
• Share the wins. Roll up time saved, deflection, and revenue signal. Give leaders the one-page summary they can repeat.

Your first goal is not feature breadth. It is fewer obstacles in the moments that matter.

Real-world snapshots from the field

Q4 Inc.
A 300+ person public company platform in finance, Q4 started with skepticism born from painful legacy enablement systems. Richard Thibault, Head of Revenue Enablement and Training, initially preferred an internal site over “another CMS.” That changed when the team centralized content in Spekit, delivered guidance in the flow of work, and turned on AI Sidekick, a contextual just-in-time sales assistant. 

The results speak clearly:

• 3× ROI driven by usage gains and self-serve answers
• 23× usage growth, with 46,000+ content views in the last 12 months
• 30% fewer ad-hoc “what’s this?” questions to managers and SMEs

“Enablement tools were so clunky and heavy that I didn’t like any of them. Spekit changed how we work and how we think about learning. It’s about finding what you need when you need it.” — Richard Thibault, Head of Revenue Enablement and Training

“The ability to search using AI is groundbreaking in our space. All that legacy content is now instantly queryable. It’s a force multiplier for enablement.” — Chris Allen, VP of Marketing

Impact beyond sales: marketing now pipes every launch asset back into Spekit as the single source of truth. Teams use short certifications and Gong checks to lock messaging. As usage spread to support, product, and marketing, Spekit became a company-wide knowledge hub. The model is simple: less scavenger hunt, more execution. AI Sidekick carries the repetitive load so people can coach, decide, and ship faster.

InMoment
Speed matters when you are modernizing go-to-market. InMoment connected systems quickly, moved from kickoff to integrated rollout fast, and saw high usage early. The team packaged complex information into short, current, and findable guidance that appears where reps work. The lesson is simple. If the experience is easy, adoption follows. If adoption follows, impact compounds.

These aren’t one-off stories. They’re predictable outcomes when you remove friction and focus on delivery over destination.

Final word

Just-in-time enablement isn’t about teaching more. It is about teaching less at the exact right time. It’s not about adding another portal. It’s about making the workflow smarter. AI is a force multiplier here, but only when it is grounded in your up-to-date content and connected to your processes.

If you lead enablement or revenue, ask three questions this quarter:

• Where do our reps pause, switch tools, or ask for help, and how often
• What is the smallest useful unit of guidance we can place at those moments
• How will we measure the effect on speed, quality, and revenue

Answer those with a simple plan. Start with one journey. Deliver inside the tools people already use. Reinforce in small bites. Measure what moves. Retire what does not. Then repeat.

The teams that win in the next year won’t be the ones with the most training hours or the largest repositories. They’ll be the ones who turn knowledge into action with the least friction. That’s what just-in-time enablement delivers. And with AI, it’s finally practical at scale.

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About the author:

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Elle Morgan, Director of Content & Enablement Expert, helps fast-growing SaaS teams turn knowledge into execution. At Spekit, she builds content and enablement strategies that drive adoption, performance, and growth through storytelling, strategy, and soul.