Gearset adds AI-powered automated UI testing for Salesforce

Gearset has launched Automated Testing, adding AI-driven, no-code user interface testing to its DevOps platform for Salesforce teams.

Gearset is positioning the release as a response to growing Salesforce complexity and pressure to deliver changes faster without increasing operational risk. The company cited research showing that 65% of Salesforce development teams feel the systems they work with are too complex.

Quality assurance remains a persistent constraint for teams building and maintaining large business applications. Manual testing is time-consuming and can produce inconsistent results. While automation can reduce repetitive work, many organisations still face skills gaps and tooling challenges.

Gearset's research found that 43% of Salesforce development teams reported bugs or issues in more than 10% of deployments. It also found that 30% of businesses cited a lack of automation tools as the main reason for deployment delays, while 44% said integrating automation into existing deployment infrastructure is a major challenge.

Testing in pipelines

Automated Testing runs UI tests inside Gearset pipelines rather than as a separate activity. This puts testing alongside other release steps and is intended to surface feedback earlier in the development cycle.

The product focuses on Salesforce user journeys and repeatable checks that teams can run as changes move through environments. Gearset says the tests require minimal maintenance compared with traditional UI test suites.

Test creation is no-code, according to Gearset. Admins and developers can create tests by clicking through an expected workflow or by using natural language, which the system then translates into an executable test.

AI also supports ongoing maintenance. Gearset says tests can "self-heal" when Salesforce UI elements change, reducing the brittleness common in many UI testing tools.

Salesforce programmes often combine configuration changes, metadata, validation rules, and process automation. These elements can introduce regressions that are hard to detect when teams rely on a small set of end-of-sprint checks. Gearset says its approach mirrors how users interact with Salesforce and accounts for Salesforce-specific complexity.

Market context

Salesforce remains a central operational system for many enterprises, and most deployments include customisations and integrations. That complexity increases the burden on release teams, particularly where organisations use governance controls and phased rollouts.

The market for DevOps tools aimed at Salesforce teams has expanded in recent years, as organisations seek to standardise release management in the same way they do for other software products. This has driven greater use of CI/CD patterns, version control, and automated checks.

In a research summary, Gearset says it has more than 3,000 customers globally. In its corporate description, it says it supports 3,500 organisations worldwide and has processed 39 million successful deployments.

Automated Testing is available to Gearset customers as part of the Gearset platform. It sits alongside products for deployment, CI/CD, testing, backup, and monitoring. Gearset has also expanded its use of AI across areas it calls Org Intelligence and Observability.

Executive comments

Gearset linked the launch to ongoing debates about speed and control in software delivery, and framed the feature as a way to broaden participation in QA beyond specialist automation engineers.

"Salesforce teams shouldn't have to choose between speed and quality," said Matt Dickens, Chief Product Officer at Gearset.

"Automated Testing is yet another example of Gearset solving a well-defined problem with AI," said Kevin Boyle, CEO of Gearset.

Gearset says it plans further work on AI agents across its platform.