AI is everywhere in go-to-market conversations right now, and for good reason. But there’s a simple truth most teams are still grappling with:
If your data isn’t clean, connected, and reliable, AI won’t help you.
In our recent survey of senior sales and marketing leaders at software companies, preparing data for AI and machine learning was the number one pipeline-related priority for the year ahead. That’s a shift worth paying attention to.
What’s driving the shift?
Leaders are feeling the pressure to modernize their go-to-market strategies. Budgets are tighter, headcount is leaner, and everyone is being asked to do more with less. In theory, AI can help fill the gap.
But only if the data behind it is trustworthy.
When we asked which data-related initiatives matter most for pipeline growth, the top answers were:
- Prepare data for AI and ML activity (43% ranked this highest)
- Integrate data from across the business (36%)
- Enrich data to support marketing efforts (36%)
- Verify accuracy and actionability of contact data (32%)
These aren’t theoretical concerns. They’re day-to-day pain points that get in the way of executing effective campaigns, routing leads correctly, or surfacing the right insights at the right time.
Setting the foundation for AI
Large companies in our survey were especially focused on AI readiness. In fact, **over 40% of respondents from firms with 5,000+ employees cited it as a top priority. **
That makes sense. AI systems need structure. They need unified fields, consistent formats, and behavior signals that are actually meaningful. Without that foundation, AI can’t give you insights, just noise.
There’s also a risk of distraction. Some companies are chasing shiny tools before they’ve done the hard work of building a clean, usable dataset. That’s a recipe for frustration, wasted spend, and wasted team time.
How to get your data AI-ready
Here are a few practical steps we’re seeing successful teams take:
- **Run a data health check. **Understand where your contact and account data stands today. This includes what’s missing, what’s outdated, and what’s duplicated.
- Consolidate sources. The fewer systems and spreadsheets you rely on, the easier it is to create a single view of your buyer.
- Verify before enrichment. Don’t dump new data into your CRM until you’ve validated what’s already there.
- Create a feedback loop. Use performance data from campaigns and outreach to improve the quality of your inputs over time.
The bottom line
You can’t layer AI on top of a messy foundation and expect great results. The companies that win in 2025 will be the ones that take data hygiene seriously today.
Because AI is only as good as the data you feed it, and most teams still have work to do.
Download our full report for more insights.