Everywhere you turn, someone in your organization is asking the same questions in a slightly different way:
And then there’s you, the data leader. You know the promise of AI, but you also know the truth: most organizations aren’t ready. Gartner® warns¹ that more than 60% of AI projects will fail to deliver by 2026, often because the data isn’t trustworthy or the processes behind it aren’t repeatable or trustworthy.
That’s the squeeze. If you move too slowly, you’ll disappoint the business. If you move too fast without the right foundations, you’ll disappoint everyone.
For years, weak DataOps practices might have been good enough for analytics. A broken dashboard was embarrassing, but it was visible. People noticed, they complained, and you fixed it.
AI is different.
As our CTO, Guy Adams, often explains “With AI, the backstop is gone. A model retrained on bad data doesn’t break loudly. It keeps producing outputs that sound plausible, until they quietly steer your business decisions off course.”
That’s why “good enough” data is no longer safe. And why so many leaders are feeling that pit in their stomach: if they don’t act, they’ll miss the moment; if they act without trust, they could fail their organization.
The irony is, most organizations already know what’s required: automated delivery, continuous observability, embedded governance, and a data product operating model
But look under the hood.
A GitHub repo here. An Airflow job there. A third-party test harness. A governance process in spreadsheets. A Slack approval thread. All stitched together by their most expensive engineers.
That isn’t DataOps. That’s duct tape.
It works until the velocity and quality needed by AI rips it apart.
Momentum is the latest generation of the DataOps.live platform, the only Snowflake-native DataOps automation platform for trusted AI.
It was born from listening to customers and prospects who told us:
“Help us make our data AI-ready. We can’t keep up with brittle pipelines, invisible quality, and governance that lags behind innovation.”
Momentum answers by delivering all the key DataOps capabilities essential for AI readiness, not as a patchwork of tools, but as a single harmonious automated platform:
The arrival of the Data Engineering AI Agent changes the way data products are built.
Instead of months of backlogs, hand-offs, and brittle scripts, a data engineer or domain expert can simply describe what they need “a Customer 360 with demographics,” “a finance view that encodes how we calculate profit,” “a product telemetry data product.”
Our new agent, Metis, instantly assembles the first iteration: pulling the right sources, generating pipelines, wiring tests, and documenting the product in minutes. Then it stays with you in plain language as you refine.
What once required engineers stitching together YAML, SQL, JSON, and endless approvals is now automated. Metis handles:
The result is a direct conversation about intent and outcome, with engineering effort focused on innovation instead of mundane work.
More than acceleration, this is a paradigm shift: moving from human-led, AI-assisted work to AI-first processes with humans in the loop. It’s how data products go from a bottlenecked craft to a repeatable business capability.
If Metis accelerates how you build, AI-Ready Scoring transforms what you can prove. It continuously evaluates whether data products are fit for AI, rolling up 120+ indicators across six critical layers of readiness. More importantly, it turns those scores into actionable guidance, showing teams where to focus, when to enforce gates, and how to demonstrate readiness to the business, the board, and regulators.
AI-Ready Scoring covers:
This framework guides improvement, continuously highlighting gaps and enforcing policy gates so only AI-fit data products move forward. Rather than AI bolted onto yesterday’s processes, it’s processes redesigned to be AI-first, with humans in the loop for responsible design and management.
DataOps.live Momentum reflects a broader industry evolution. We’re moving from a world where data engineering was a manual process, to one where AI agents act as copilots, and soon to a future where AI-first processes empower even non-technical users, always with responsible human oversight.
For CDOs, CIOs, and AI leaders, this is a leadership mandate. Organizations that embed automation, observability, and governance into their operations today will deliver AI outcomes faster, safer, and at scale. Those who cling to duct-taped DIY approaches will be left behind.
With DataOps.live Momentum, you can finally say “yes” to both sides of the squeeze:
The result is confidence. Confidence that you can meet demand without creating chaos. Confidence that you can move quickly without sacrificing trust.
Because the real risk isn’t adopting new automation. The real risk is standing still while competitors turn AI-ready data into AI advantage.
Every organization is at this crossroads. Business demand for AI isn’t slowing down. Boards won’t accept excuses.
DataOps.live Momentum gives leaders a way to change the ending: transforming AI-ready from a slogan into evidence you can stand behind, embedding governance without slowing innovation, and uniting speed with trust
👉 Explore the DataOps.live platform and see how Momentum helps you answer the call for AI without failing the business. It’s free to get started and free 500 minutes every month – including production minutes!
GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.
¹Pivot Your Data Engineering Discipline to Efficiently Support AI Use Cases, Robert Thanaraj, Michael Gonzales, Yogesh Bhatt, Ehtisham Zaidi, Gartner, 27 May 2025, ID G00826564