Learning and planning.
In one workspace.

PlanAI brings role-based learning, strategic initiative planning, financial analysis, and team review into one workspace. Teams can move from research and guided learning to practical work such as an initiative proposal, forecast, or scenario analysis.

For example, a manager preparing a growth proposal can study the relevant concepts, develop the plan, test its financial assumptions, and bring the work to colleagues for review. This gives learning a concrete application and gives reviewers a proposal they can examine in detail.

CFOs can use the workspace to help teams build financial acumen and prepare proposals with explicit assumptions, forecasts, and alternative scenarios. CHROs and learning leaders can connect development priorities to practical assignments and review how employees apply their knowledge.

A shared initiative might ask managers to develop a business case for their function. Finance can define the analytical expectations, while HR shapes the learning path and review process. Both teams can discuss the resulting work against agreed criteria.

Use learning progress alongside practical submissions, such as plans, models, and scenario analyses. These provide material for reviewers to assess the clarity of the business question, the quality of evidence, and the reasoning behind a recommendation.

Define assessment criteria before the assignment begins. Comparing an initial submission with a revised version can help reviewers identify development needs and discuss improvements. Evidence of stronger work should be considered alongside any longer-term business outcomes you choose to track.

Scope PlanAI around the learning and planning workflow you want to support, then identify which information needs to come from your existing learning, finance, and productivity systems. Establish which system remains the authoritative source for each type of record.

During the technical review, confirm the availability of required connectors, their data scope and permissions, and who will administer them. Connection capabilities and configuration depend on your deployment and should be validated against the pilot’s requirements.

AI workflows can use prompts, business information, and selected document content as context. The provider and information included depend on the workflow and deployment. Agree on permitted sources, applicable provider terms, and data-handling requirements before introducing sensitive material.

Assign people to review AI-assisted work before it informs a business decision. Reviewers should check source material, financial assumptions, calculations, and recommendations. Our security and architecture page outlines the data and oversight topics to address with IT.

Enterprise sign-in can connect to your organization’s identity provider, including Microsoft Entra ID. Directory provisioning and workspace role assignments are configured as part of the deployment, with access determined by membership and applicable permissions.

Involve your identity and IT administrators early to define who can join, contribute, review, and administer the workspace. Validate onboarding, role changes, and access removal before expanding the rollout, and confirm that the configuration meets your organization’s requirements.

Choose one participating team, an executive sponsor, and a defined business task, such as preparing a growth proposal or evaluating an investment scenario. Agree on the learning path, expected deliverables, review criteria, and responsibilities before work begins.

The pilot plan should cover workspace setup, any required connections, working sessions, and a review date. Scope and timing depend on the use case and deployment requirements. At the review, assess the work produced, participant feedback, and operational fit to decide what to refine or expand.

Establish a baseline and a small set of measures tied to the business need. These might include participation, the quality of submitted business cases, time spent preparing and revising plans, or the ability to explain and test financial assumptions. Agree on who will collect and review the evidence.

Consider the findings alongside licensing, implementation, administration, and employee time. A wider investment decision should reflect observed benefits and the cost of adoption, with a clear distinction between results demonstrated during the pilot and benefits that still need validation.