To address the skills barriers limiting AI adoption in businesses, the AI Skills for Business Competency Framework presents guidance, including the high-level skills and competencies employees need to support AI adoption. This is the first of a series of products designed to enable businesses to understand their AI upskilling needs and training providers to develop relevant training solutions.
Name in original language
AI Skills for Business Competency Framework
Initiative overview
The framework outlines the essential knowledge, skills, personal attributes, and behaviors necessary to effectively address practical challenges and demonstrate competence in both personal and professional contexts. It is designed for the following groups:1) **AI Citizens**: Individuals in the public who may engage with organizations utilizing artificial intelligence. The framework clarifies the understanding of AI, focusing on its capabilities, opportunities, and risks, thereby equipping AI Citizens with a realistic perspective on AI usage.2) **AI Workers**: Employees whose roles are not primarily centered on data but may still be influenced by these technologies. The framework aids AI workers in recognizing the efficiency and productivity enhancements that AI can offer in their jobs.3) **AI Professionals**: Individuals whose main responsibilities involve data and AI, such as data analysts, machine learning engineers, and data ethicists. The framework delineates the essential cross-disciplinary competencies needed to collaborate effectively within teams and across their organizations.4) **AI Leaders**: Senior personnel responsible for the acquisition and governance of AI solutions. The framework assists them in anticipating the implications of emerging technologies, including their effects on the workforce, and in overseeing the responsible and safe implementation of AI in complex organizational environments.The framework consists of five dimensions, each representing a set of competencies and behaviors across five key areas.**Dimension A: Privacy & Stewardship**. This dimension focuses on data security and protection, encompassing the design, creation, storage, distribution, and associated risks.**Dimension B: Specification, acquisition, engineering, architecture, storage, and curation**. This area addresses the collection, secure storage, manipulation, and curation of data, along with competencies related to data management and analytical techniques, including handling issues arising from the (mis)use of sensitive data.**Dimension C: Problem definition & communication**. This dimension emphasizes the ability to identify and articulate a problem clearly, understand how artificial intelligence can contribute to potential solutions, and effectively communicate this knowledge to diverse audiences.**Dimension D: Problem solving, analysis, modeling, visualization**. This area involves the knowledge and application of various mathematical, statistical, and computing tools and methods to define and analyze problems and present solutions.**Dimension E: Evaluation and Reflection**. It is crucial for all professionals in data science and AI to have a solid grasp of the ethical principles guiding their work and to take responsibility for the integrity of the models they develop.
Name of responsible organisation (in English)
Department for Science, Innovation and Technology (DSIT)
