Alation automates governance with latest AI-powered suite

Governance agents

With incomplete and inconsistent metadata among the reasons so many AI initiatives never make it past the pilot stage, Alation is attempting to remove one of the barriers to successful AI development with the launch of Curation Automation.

I like the notion of declarative data governance -- humans define the intention, policies and business outcomes, then oversee agents as they build and enforce the rules to achieve them. That is the future of data and AI governance, although it will take a while to get there.

Using the feature, administrators can use natural language that reflects their organization's business and regulatory intent to define metadata requirements. Once those requirements are specified, agents automatically enforce them to make data complete and consistent so it can be discovered and used to inform AI and analytics tools.

Meanwhile, when packaged with CDE Manager and Data Quality to form the outcome-based governance system, Curation Automation helps enable Alation customers to automate data governance in a move that was inspired by customer feedback, according to GT Volpe, Alation's senior director, product management.

CDE Manager, introduced in November 2025, is an agentic AI-fueled feature set aimed at identifying critical data elements  -- data related to integral operations such as reporting and regulatory compliance -- and prioritizing governance of those CDEs. Data Quality is Alation's suite for assessing, monitoring and improving the quality of an enterprise's data and is powered by the vendor's Data Quality agents.

"What we kept hearing from customers was that governance wasn't actually working in practice," Volpe said. "They had policies, but turning those policies into consistent, day-to-day enforcement was manual, hard to scale, and nearly impossible to prove. The goal for outcome-based governance was to change all that for our customers."

Before enabling Alation users to declare their standard for data and then using AI agents to automate the process of getting data to meet that standard, data governance required months of manual work, Volpe continued.

"That work … can now happen in days or weeks -- with far greater consistency -- while still keeping people in the loop for nuance, review and exceptions as the data and needs evolve," he continued.

Beyond metadata management, outcome-based governance includes the following:

• Transparent automation with all changes available for preview before being executed to ensure they meet organizational standards.
• Continuous enforcement so that standards are consistently applied and data remains complete and consistent as requirements evolve.
• Measurable impact through built-in reporting that demonstrates provable outcomes based on pre-declared standards.

AI-powered metadata enrichment and transparency are perhaps the most significant capabilities of outcome-based governance , according to Petrie.

"I like how Alation uses agents to generate and enrich metadata, especially to understand user intentions, guide their governance actions and support context engineering," he said. "Data engineers, stewards, and consumers will also appreciate the transparency so they can inspect and approve actions before anything takes effect."

Meanwhile, Stewart Bond, an analyst at IDC, noted that Curation Automation and outcome-based governance demonstrate that Alation is delivering on its investments in developing AI capabilities that make use of the knowledge the vendor has gained regarding customers' data.

In particular -- just as BI vendors develop tools that deliver analytics outcomes desired by users such as customer retention or operational efficiency -- they show that Alation is tailoring AI outcomes to meet the needs of its users, he continued.

"The new automation features show that Alation is leveraging its investments in agentic AI and the wealth of intelligence about data that Alation manages," he said. "For Alation, one of the primary outcomes of the platform is governance, and the more it can be automated, the more the platform will be adopted and demonstrate its value in the organization."

Looking ahead

With outcome-based governance now generally available, part of Alation's product development roadmap is focused on expanding the suite to make governance even more autonomous, as well as make agentic AI-generated outcomes more transparent and trustworthy, according to Volpe.

Informa TechTarget

"That means continued investment in agentic automation -- not just identifying gaps, but resolving them and proving they were resolved across broader sections of the data management world," he said.

In addition, Alation plans to both make declaring desired outcomes even easier and empower agents to suggest and implement the path toward reaching those outcomes, Volpe continued

Petrie, meanwhile, suggested that with most enterprises using more than one data catalog to manage data, Alation would be wise to make its data catalog capabilities more flexible to support AI initiatives that span different organizational domains.

"Most enterprises have two to four catalogs in their environments, and they're getting very proactive about sharing metadata across these platforms to build context for AI initiatives," he said. "I'd like to hear more from Alation about how it can federate metadata management across catalogs to support these initiatives."

Eric Avidon is a senior news writer for Informa TechTarget and a journalist with more than three decades of experience. He covers analytics and data management.