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About Kasp

Task-based analysis,
with its foundations in view.

Kasp helps assess how AI assistance, partial automation and substitution potential change individual tasks · so decisions rest on verifiable foundations, not sweeping predictions about jobs.

01 Mission

What Kasp is built on

Kasp supports analyses of work, education, organizations, products, countries and public systems. Each area has its own result structure. For work, occupation, role, task, workflow and workflow step are recorded separately; ESCO, O*NET and ISCO-08 are among the possible source families. The result comprises eight separate impact dimensions · not a universal overall score.

02 Principles

Four rules behind every assessment

  • 01Task-basedFor work, Kasp separates the occupation or role from the specific tasks and described workflow. Other analysis areas follow their own subjects and result structures.
  • 02Evidence-ledStored sources can show their origin, date, scope and source status. User context and Kasp assessments remain distinguishable from them.
  • 03Visible limitsWhere required context, robust evidence or review is missing, a statement remains unknown or withheld. Missing information is not filled with substitute values.
  • 04Versioned and verifiableSupported dossiers can document stored sources, data currency and versions. Public impact values require the designated subject-matter and technical checks.

03 Methodology

How an assessment is developed

An analysis begins with the described subject, baseline and planned AI deployment. For work, relevant occupation and task sources can add context. Kasp keeps supplied user context, stored sources and its own assessment separate.

For work, the result structure examines technical capability, workflow states, human working time, review burden, quality change, augmentation impact, task substitution potential and residual risk separately. A public value requires appropriate context, robust evidence, calibration and reproducible review.

Source status, evidence grade, uncertainty or coverage are shown only where the specific result actually contains that information. They describe the evidence, not the future. If the required foundation is missing, no substitute value is shown.

Explore the methodology

04 Limits

What Kasp is not

Kasp does not provide individual career, HR, legal, tax, medical or financial advice, and does not predict the future of any individual job. Assessments combine versioned data, documented sources and automated processing. They may be incomplete, outdated or incorrect and must be reviewed by a qualified person before important decisions.

Orbit organizes related analyses, files, scenarios and versioned results in authorized workspaces. Kasp must not be used to evaluate identified employees or as the sole basis for hiring, performance, promotion or dismissal decisions.

AI transparencyExplore the occupation catalog