At this summer’s Ai4 conference in Las Vegas, one thing became crystal clear: the buzz around AI is louder than ever, but many companies are still trying to figure out what they can actually do with it.
While the keynotes leaned toward “AI for everything,” hallway conversations told a different story. Most companies are still in the early innings of AI maturity. They’re not lacking ambition per se—they’re lacking clean, organized, and accessible data.
So let’s skip the hype and talk brass tacks. The following outlines what enterprise companies can do today to shore up their data readiness and place themselves on a direct path to AI maturity.
Adopting the ‘Path to AI Maturity’ Framework
The diagram below reflects a framework shaped by years of working with enterprise Tealium clients on their data and AI readiness journeys.
Across industries, we’ve seen organizations progress through similar stages of maturity, starting with clean, consented data, then layering in predictive capabilities, real-time activation, and ultimately agentic orchestration.
You don’t need a “moonshot AI project” to get started. You need a disciplined, connected data foundation. Here’s how many leading organizations are building toward a mature, scalable AI future—and how you can, too.
1. What You Can Do Right Now: Leverage Predictive Analytics
Many companies already have the foundational pieces in place to start experimenting with predictive analytics: customer events, attributes, and identity stitched together inside their data platforms. That’s enough to get started.
By applying predictive insights to existing visitor data, for instance, Tealium users can segment audiences more intelligently, triggering more relevant experiences today, not months from now. No need to build a model. No need to code. Just configure it and go.
2. What You Can Do Short-Term: Ingest External Model Outputs (30-Day Ramp)
Let’s say your data science team is already cranking out models in Snowflake, Databricks, or Python. The good news is that you don’t have to rebuild them elsewhere.
You can ingest those model outputs as attributes into your engagement layer. Whether it’s risk scores, customer clusters, or product affinity predictions, use them just like any other attribute to trigger experiences via platforms like Tealium. That’s real-time activation without data silos, and it keeps your internal ML investment intact.
3. What You Can Do Short-Term: PredictML (60-Day Ramp)
Want to move beyond out-of-the-box predictions? The right CDP can begin training and deploying custom models natively.
Once you’re live and collecting data for 60 days, Tealium’s PredictML, for example, starts unlocking the ability to train and deploy your own models inside the Tealium ecosystem. Whether you’re trying to predict lifetime value, engagement likelihood, or anything else tied to customer behavior, PredictML shortens the gap between ideation and implementation.
In a world where it can take six months just to get an API wired up for a new model, being able to move this fast is a massive differentiator.
4. What You Can Do Long-Term: Hosted Model Triggers via API
For companies with more advanced ML maturity, Tealium supports calling hosted models via API in real time.
Imagine a visitor landing on your site, and Tealium calling an API to your internally hosted model—think fraud detection or next-best-action engine—to instantly tailor the experience. That’s the future-ready model: combining first-party data, real-time orchestration, and intelligent decisions, all in the moment.
This level of flexibility is what enables your business to start building an agentic architecture.
5. And What’s Next: Tealium for Agentic AI
Agentic AI was everywhere at Ai4. The ability to let AI systems make decisions and take actions autonomously is no longer theory—it’s an emerging reality.
The coming years won’t just be about data fueling AI. It’ll be about data coordinating AI agents to act on behalf of your brand with precision, governance, and compliance.
As these multi-agent ecosystems mature, you’ll want to invest in providers that offer reliable APIs, such as Tealium’s Moments API, to coordinate their actions and decisions to remain contextual, compliant, and brand-safe.
Final Thought: AI Readiness Starts with Data Readiness
The biggest takeaway from Ai4—and from months of post-conference follow-up with enterprise leaders? Most companies aren’t behind on AI because they lack ambition—they’re behind because they lack organized, governed, first-party data.
Whether you’re starting with predictive audiences or preparing to launch autonomous agents, your data foundation determines your ceiling. And the ability of your CDP, whether Tealium or otherwise, to enrich and activate that foundation will determine the height of said ceiling.
