Give every employee AI that has the context to be useful

We’re introducing new capabilities in Rippling AI: plugins, skills, and automations*. Together, they help employees use AI with tailored context about their role, team, and policies, turn proven instructions into reusable prompts, and automate recurring work. They’re all governed by the policies and permissions already in Rippling.

General-purpose AI tools are powerful. But at work, AI is only useful when it understands the context around the task: who is doing the work, where they sit in the org, what systems they work in, who they work with, and what information they’re allowed to access. Without that context built-in to their AI tooling, employees are left with the hassle of copying data from other systems into their prompts, figuring out which MCPs to connect, and unknowingly rebuilding workflows their colleagues have already created. 

The context that makes AI powerful varies by person and changes constantly. A manager may need access to their team’s staffing, performance, or approval data, but an individual contributor shouldn’t see the same information. What's useful for HR may not be relevant or appropriate for Finance. And as employees join, change roles, or leave, access and workflows need to change with them.

Rippling AI brings those pieces together. Plugins connect approved third-party business systems, skills package repeatable instructions, and automations* run AI prompts under the right conditions and permissions.

What we’re launching

Plugins

Plugins connect Rippling AI to third-party MCPs, giving employees a way to complete work across their tech stack from within Rippling. AI becomes more powerful because it can access data and take actions across the business systems employees already use. For example, an HR manager preparing for performance calibration can use Rippling AI to identify the right managers to include, check Google Calendar for their availability and send invites, and draft emails in Gmail – all from Rippling.

Combined with Rippling’s MCP Gateway, companies can control which business systems each employee can connect to and what actions they’re allowed to take. That means employees can use AI with context around their role, team, and work, without exposing data they shouldn’t see or forcing companies to manage a separate permission layer.

Skills 

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Skills are reusable instructions for Rippling AI to package and share best practices. Written in natural language, they describe how work should get done, including rules to follow, files to reference, systems to check, approved plugin actions, and the format the output should follow. For example, managers and recruiters can use an Offer Deck skill to create compelling offers for their top candidates, incorporating information about their roles, teams, feedback themes, and more.

Skills can be shared with employees based on role, team, reporting line, or other workforce attributes. As employees change roles or teams, access will adjust automatically. Skills can also be automatically enabled for all or a subset of employees, so Rippling AI follows company-approved processes every time.

Automations

Automations* let teams prompt Rippling AI on a recurring basis, without manual prompts. Like traditional workflows, automations can run on a schedule, when Rippling data changes, or when an event in Rippling occurs. They can also be triggered by an email or Slack message, and when events occur in third party systems. 

In Rippling AI, employees can describe processes they want to automate using natural language, and it will generate the workflows with the steps, prompts, and triggers needed. Automations are governed by Rippling permissions, so employees will only access the data and actions they’re allowed to use. For example, executives can create an automation to monitor key Slack channels and flag any issues that need their attention.

How it works in practice 

Consider a frontline manager preparing for the week ahead: the manager needs to know what could disrupt operations before it becomes a problem. That work usually entails checking multiple systems to reconcile workers’ hourly schedules, staffing changes, time off, training status and deadlines, access issues, timecard exceptions, and pending approvals.

With Rippling AI, that weekly brief can be generated automatically.

Before the week starts, an automation runs a company-approved skill for frontline planning. Rippling AI starts with the workforce context already in Rippling, then uses plugins to pull in additional context from connected systems like Outlook, Google Calendar, Slack, Teams, Atlassian, and other tools employees use every day. Because it is built on Rippling’s workforce context, it understands which employees report to the manager, which locations or teams they oversee, and what information the manager is allowed to see.

The brief is delivered to the manager in Slack every Monday morning, with the issues most likely to disrupt the week: an uncovered shift, a new employee missing required training before their shift, a timecard exception that needs approval, or an equipment issue that could keep someone from starting work on time. Rippling AI also recommends next steps and identifies owners. The manager starts the week with a prioritized plan, instead of searching across systems or getting blindsided by escalations throughout the week.

Built on Rippling’s workforce context

Rippling’s advantage is the workforce context behind these capabilities: employee identity, team, manager, permissions, and policies. That context makes Rippling AI more useful because it understands the business around every request. It also makes AI safer to scale because access follows the employee as the organization changes.

A frontline manager can get a week-ahead brief with updates about their team, not every team or their team from last quarter. Employees can use a performance review coach with the right guidance for their specific roles. A support manager can investigate a low CSAT score with approved customer and team context. 

The companies that get the most from AI won’t be the ones with the most one-off prompts. They’ll be the ones that turn useful AI work into governed, reusable workflows that stay current as the business changes.

Rippling AI is built for that shift. See it in action.

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