Introduction
Artificial Intelligence (AI) holds enormous potential for businesses, enhancing productivity and competitiveness. However, adopting AI technology can be challenging. To support the adoption of AI, we need to ensure that technical and non-technical employees and decision-makers understand the opportunities, limitations and ethics of using AI in a business setting.
To address the skills barriers limiting AI adoption in businesses, the Department for Science, Innovation and Technology (DSIT) has been working with the Innovate UK BridgeAI programme (BridgeAI) to develop research on the high-level competencies that businesses need their employees to engage with to enable AI adoption, including for traditionally non-technical roles.
This project aims to facilitate an increase in the number and diversity of employees across the UK workforce with access to relevant, high-quality AI training, ultimately addressing the skills barriers limiting AI adoption.
About the AI Skills for Business Competency Framework
The framework identifies the knowledge, skills and personal aptitudes and behaviours required to navigate practical challenges and exhibit competency within life and their profession. The Framework targets the following audiences:
- AI Citizens: members of the public who may be customers to organisations making use of artificial intelligence. The framework defines the level of understanding of AI, with respect to its capabilities, opportunities and risks. In doing so it aims to provide AI Citizens with a pragmatic outlook on the use of artificial intelligence.
- AI Workers: employees not working primarily in ‘data’ or ‘AI’, but whose roles may be impacted by these technologies. The framework supports AI workers to identify the opportunities AI provides in terms of efficiency and productivity in their roles.
- AI Professionals: employees whose core responsibilities concern the use of ‘data’ and ‘AI’. These include data analysts, Machine Learning engineers, and data ethicists. The framework defines the cross-cutting competencies required to work effectively in multidisciplinary teams, and to collaborate effectively across their organisation.
- AI Leaders: those holding senior responsibility for the procurement and/or governance of artificial intelligence solutions. The framework will support them to foresight the implication of emerging technologies, including impacts on their workforce, and to oversee the responsible and safe introduction of AI in settings of organisational complexity and uncertainty.
The framework comprises five dimensions, representing a cluster of competencies and behaviours across five areas.
- Dimension A: Privacy and Stewardship. This area concerns the security and protection of data, including the design, creation, storage, distribution and associated risks. This dems practical data controls will articulate fully with legal, regulatory and ethical considerations.
- Dimension B: Specification, acquisition, engineering, architecture, storage and curation. This area concerns the collection, secure storage, manipulation, and curation of data. Competencies in this area also relate to the application of data management and analytical techniques. For example, this includes competencies around handling situations arising from the (mis)use of sensitive data.
- Dimension C: Problem definition and communication. This area concerns the ability to identify and clearly define a problem, to understand the role artificial intelligence can play in potential solutions, and to be able to communicate this knowledge effectively to a variety of audiences.
- Dimension D: Problem solving, analysis, modelling, visualisation. This area concerns the knowledge of and ability to apply a range of mathematical, statistical and computing tools and methods to define and analyse a problem and present solutions.
- Dimension E: Evaluation and Reflection. It is important that all professionals working within the field of data science and artificial intelligence have a clear understanding of the ethics that underpin their work, and take responsibility for the assurance of the models they build.
How to contribute
We welcome all feedback and contributions to this project. In the first instance, please contact the team at [email protected].
The Framework is published open source under the CC-BY4.0 license, and is maintained in a Zenodo community.
Funding
This project is supported by the Department for Science, Innovation and Technology (DSIT). It begins to fulfil the National AI Strategy commitment to Publish research into what skills are needed to enable employees to use AI in a business setting.
This project is funded by the Innovate UK BridgeAI programme (BridgeAI), which empowers UK businesses in high-growth sectors, driving productivity and economic growth through the adoption of Artificial Intelligence. This work is supported by a consortium including Innovate UK, Digital Catapult, The Alan Turing Institute, STFC Hartree Centre and BSI.
The framework was developed by The Alan Turing Institute, the UK’s national institute for Data Science and Artificial Intelligence. This work is led by Dr Matt Forshaw, Senior Advisor for Skills and the Skills Team at The Alan Turing Institute.
The Alliance for Data Science Professionals (AfDSP) brings together organisations and individuals to ensure professional, ethical and well-governed best practice. The Alliance for Data Science Professionals (AfDSP) comprises BCS, The Chartered Institute for IT, the Royal Statistical Society, the Operational Research Society, the Institute of Mathematics and its Applications, the Alan Turing Institute, and the National Physical Laboratory (NPL) and is supported by the Royal Academy of Engineering and the Royal Society.