Research finds 68.1% deploy database changes weekly or faster, while only 28.1% report standardized, consistently enforced database change governance.

AUSTIN, Texas: #AI--Liquibase, the leader in Database Change Governance, today released the 2026 State of Database Change Governance Report, new research on how enterprises are managing database change as AI becomes embedded across production systems, analytics, and delivery pipelines. The report finds that AI interaction with enterprise databases is now widespread, while governance automation and consistent enforcement have not kept pace with the speed and scale of change.

Methodology: Survey findings are based on a 2026 Liquibase survey of 426 respondents across its global community, reported in aggregate. The report also includes anonymized product telemetry observations from tens of thousands of database and data platform installations across Liquibase Secure customers and Liquibase Community users.

For CIOs, the issue is not that AI touches production data. The issue is whether the organization can prove control at the database layer when change is frequent, environments are heterogeneous, and AI introduces new pathways for change and access. At AI scale, manual governance struggles to keep up. That is where risk compounds and then surfaces as data quality failures, audit friction, and outcomes leaders cannot explain.

“AI raises the standard for control. It adds new automation and new actors, and it does it right where trust is won or lost: the database,” said Pete Pickerill, Co founder, Liquibase. “If governance isn’t enforced and measurable, you’re operating with an unmanaged risk surface. The result is data quality issues, audit friction, and outcomes leaders can’t explain. This report maps the gap and the practical path teams are taking to close it.”

Key findings from the 2026 survey

AI interaction: 96.5% of respondents report at least one AI or LLM interaction with their production databases, including analytics and reporting, training pipelines, internal copilots, and AI-generated SQL.

Change velocity: 68.1% deploy database changes weekly or faster, including 10.8% deploying multiple times per day and 18.8% deploying daily.

AI-era risk: 64.3% cite data quality issues as a top AI-related risk, and 46.5% cite ungoverned AI-generated SQL as a key concern.

Estate complexity: Organizations report an average of five database and data platform types, and 29.1% manage ten or more database types.

Governance gap: Only 28.1% report database change governance that is standardized and consistently enforced, while 42.3% remain at Ad hoc or Emerging. Only 7.7% report fully automated governance using policy as code with real-time enforcement.

Why this matters now

The report highlights a widening operating gap. Enterprises are shipping database change continuously across diverse platforms, while governance often depends on documentation, manual review, and fragmented evidence. In an AI era, those approaches do not scale. As AI automations and AI-generated changes increase, the cost of inconsistent enforcement rises, and the blast radius of a single unmanaged change expands across downstream analytics and AI systems.

Audit pressure compounds the challenge. The report finds 95.3% of respondents undergo multiple compliance or database audits per year, with more than one in five facing seven or more audits annually.

What Liquibase Secure customer behavior shows at AI scale

(Based on anonymized Liquibase Secure product telemetry, separate from the survey results.)

Governance is the default: 99.25% of Liquibase Secure sessions run with governance enabled, a necessary baseline as AI increases the volume of proposed change.

Standardization enables automation: Nearly 86% of observed changelog activity is in XML and YAML, supporting machine-readable change definitions that AI-scale delivery can validate and enforce.

Controls must exist before CI: About 90% of sessions run outside CI, reinforcing that as AI accelerates change, governance has to shift left into the developer workflow.

Adoption starts with proof: Reporting is among the most exercised capabilities, reflecting early demand for audit-ready traceability as AI makes decisions harder to defend without evidence.

A practical roadmap and scorecard for CIOs

Beyond the survey findings, the report provides a staged operating model for moving from ad hoc database change to standardized, enforced, and observable governance, without slowing delivery. It also introduces a CIO-ready scorecard that pairs reliability metrics (MTTD and MTTR) with coverage metrics for automated controls, audit evidence, and AI-governed change, so leaders can measure progress and risk reduction over time.

Availability

The 2026 State of Database Change Governance Report is available now.

About Liquibase

Liquibase empowers teams to deliver mission-critical applications, data products, and AI initiatives by automating and governing database change. We are the company behind Liquibase Community, a project with deep open-source roots that has been downloaded more than 100 million times and is trusted by thousands of teams worldwide.

Liquibase Secure, built on that proven community foundation, is the only enterprise platform that unifies DevOps, security, and compliance at the database layer. It enables organizations to deliver applications and data products with velocity, safety, and confidence. Trusted by the world’s most innovative and highly regulated enterprises, Liquibase Secure powers the last mile of application and data delivery.

Learn more at www.liquibase.com. Follow us on LinkedIn and X.

Fonte: Business Wire