Your company has AI agents answering customer emails. You’ve deployed machine learning to optimize ad spend. Your CRM practically predicts what prospects want before they know it themselves.
And yet… your sales team still Slack-begs Marketing for slide updates.
The future is unevenly distributed, especially in your collateral workflow.
Here’s the uncomfortable truth: While enterprises pour billions into AI transformation, the most basic go-to-market need (getting the right collateral in front of prospects) remains stuck in 2015.
Let’s break down why this sales collateral bottleneck exists, what it’s costing you, and how to fix it.
1. The Investment Doesn’t Match the Impact
The numbers are staggering. According to Menlo Ventures’ 2025 State of Generative AI report, departmental AI spending hit $7.3 billion in 2025, up 4.1x year over year. Gartner forecasts global AI spending approaching $1.5 trillion. Meanwhile, big tech companies are on track to invest an aggregate of $400 billion into AI initiatives this year alone.
Yet here’s what that investment bought: coding assistants, customer support bots, and marketing automation tools.
What it didn’t buy? A way to get customized pitch decks out the door without a three-day turnaround.
According to G2’s 2025 AI Agents Insights report, 57% of companies already have AI agents running in production. But when it comes to sales collateral (the documents that actually close deals) most organizations are still operating on request tickets and email chains.
The AI transformation happened everywhere except the last mile of your sales process—leaving behind a stubborn sales collateral bottleneck.
2. The Hidden Cost of “My Meeting Is Tomorrow!”
The collateral problem isn’t just annoying. It’s expensive.
Docurated’s State of Sales Productivity study found that sales reps spend just 32% of their time actually selling. The rest? 31% goes to searching for or creating content, and 20% to administrative tasks and CRM management.
Meanwhile, SiriusDecisions reported at their 2013 Summit that 60 to 70 percent of content produced by B2B marketing departments goes unused. Not because it’s bad content, but because reps can’t find it, can’t customize it, or can’t get it fast enough.
Think about what that means: Your marketing team creates assets. Your sales team can’t use them in time. So they build their own. Off-brand. Outdated data. No version control.
Then multiply that across every rep, every deal, every quarter.
3. AI Agents Don’t Fix Plumbing Problems
Here’s where the AI transformation narrative falls apart.
McKinsey’s latest research shows that while nearly nine out of ten organizations now regularly use AI, less than 20% have successfully scaled beyond pilot projects.
Why? Because AI is great at pattern recognition, content generation, and data analysis. What it’s not great at? Integrating with your specific brand guidelines. Pulling live data from your CRM into slide templates. Maintaining version control across 2,500 different assets.
As one analysis put it: “It’s a plumbing problem, not an intelligence problem. And plumbing takes time.”
Your AI agent can draft a brilliant follow-up email. But can it generate a compliant, on-brand pitch deck with accurate pricing for a specific prospect in three minutes?
That requires infrastructure, not just intelligence.
4. The “AI-Forward” Companies Feel This Pain Most
Counter-intuitively, the organizations investing most heavily in AI transformation are often the ones experiencing the worst sales collateral bottleneck.
Consider the pattern: A company deploys sophisticated AI for deal intelligence, pipeline forecasting, and buyer intent signals. Their reps now know exactly who to target and what to say. The AI even suggests optimal meeting times and talking points.
Then the rep needs a custom deck for that perfectly-timed meeting.
And they wait. Three days for creative to build it. Another round of revisions. By the time the deck is ready, the buying window has shifted.
According to Highspot’s 2025 State of Sales Enablement Report, companies with well-integrated enablement tech stacks are 42% more likely to increase sales productivity. But most organizations aren’t there yet. 55% still struggle with either sales training or coaching, and even fewer have solved the collateral automation challenge.
5. Infrastructure Beats Features Every Time
The solution isn’t another AI tool bolted onto your existing workflow. It’s infrastructure that makes your existing AI investments actually work.
Here’s what that looks like in practice:
One healthcare enterprise using Clatter saved 600+ hours annually on a single initiative by moving from request-based collateral creation to self-serve generation. Their marketers gained back 150+ hours in Q1 alone. What used to take three days now takes three minutes.
The transformation wasn’t about AI replacing humans. It was about eliminating the bottleneck between AI-powered insights and real-world execution.
As one operations lead who helped build a system with over 2,500 PowerPoint slides described it: “Before, when something changed, we had to track down every file and update it manually. With automation, the team gets hundreds of hours back and never has to worry about outdated materials.”
That’s not a feature. That’s infrastructure.
The Bottom Line
You can have the most sophisticated AI stack in your industry. But if your sales team still spends three days waiting for a deck, you’ve automated everything except what matters most.
The companies pulling ahead in 2026 aren’t just the ones with the best AI models. They’re the ones who’ve solved the plumbing problem, connecting AI-powered insights to production-ready assets in minutes instead of days.
The question isn’t whether you can afford to automate your collateral workflow.
It’s whether you can afford not to.
Ready to close the gap between AI strategy and practical execution? Schedule a demo to see how Clatter transforms collateral creation from a three-day bottleneck into a three-minute workflow.
