The global skills and competency framework for the digital world

SFIA 9 - a framework for AI skills - BETA

AI & data literacy | Build AI/ML models | Develop and operationalise AI/ML applications | ML Ops | Impact on jobs

The SFIA Foundation's approach to integrating AI-related skills into SFIA 9 is driven by practical considerations and a focus on the enduring professional skills and competencies for the workplace.

This is in beta alongside the development of the SFIA 9 framework. Contributions and ideas are welcome.

Challenges in defining AI Skills

There are several challenges in defining AI-related skills due to the rapidly evolving nature of AI technologies. These challenges include:

  1. Pace of change: AI technologies are advancing rapidly, making it difficult to create a static framework that remains relevant over time. New tools, platforms, and methodologies are constantly emerging.

  2. Breadth and depth: SFIA is a broadly used framework. AI encompasses a wide range of subfields, from machine learning and natural language processing to robotics and ethical considerations. Balancing the depth of coverage without becoming overly specific is a challenge.

  3. Integration with existing skills: AI skills need to be integrated with existing professional skills in a way that complements and enhances them, rather than creating siloed specialisations. Employers may need to localise the SFIA skills to their specific tools, platforms, and methodologies as these are constantly emerging.

  4. Industry variation: Different industries adopt and apply AI in various ways. Employers may need to localise the SFIA skills to their specific tools, platforms, and methodologies are constantly emerging.

  5. Ethical and legal considerations: As AI technologies raise significant ethical and legal issues, the framework must address these aspects comprehensively.

  6. SFIA User needs: Ensuring that the framework remains practical and useful for current SFIA users, while also being adaptable for future advancements in AI.

Recognising that predicting the future is challenging, the framework is designed to be useful and reflective of current practices rather than speculative predictions. Emphasis is placed on professional skills that adapt to new technologies and working practices, without delving into the intricate details of AI platforms and tools, which can be found elsewhere. The framework maintains a focus on the needs of current SFIA users, ensuring it remains relevant and beneficial.

There is a risk that many of the current opinions on AI skills for SFIA are not yet mature enough for the core of SFIA and may be better suited as add-ons to SFIA to allow for proper maturation.

Over the years, from SFIA v1 to SFIA v8, the lifecycle of new technologies and working practices has been observed. SFIA’s regular updates have allowed for niche skills to evolve from specialist areas to more generic skills, eventually breaking down into more granular and focused activities within broader skill areas. This evolution underscores the importance of a structured yet adaptable framework to support industry, employers, and individuals in navigating the complexities of AI integration.

Overview of AI Skills in SFIA 9

AI and data literacy: Covers the basic concepts and knowledge necessary for professionals to interact with AI technologies, with significant overlap with data literacy.

AI Skills to Automate, Assist, Augment: Skills required to implement AI tools that automate processes, assist in decision-making, and augment human capabilities.

Skills focused on developing and operationalising AI/ML applications: Essential for IT and data science professionals, these skills involve the design, development, deployment and operationalisation of AI/ML-driven systems. This section details the skills needed to build and operate robust, data-intensive applications leveraging AI/ML technologies.

Skills focused on building the AI/ML Models: Targeted at specialist roles such as data scientists and AI researchers. 

Using AI to make individuals more productive: AI tools can enhance individual productivity by acting as digital assistants or copilots. This section explores how AI can support personal productivity and streamline tasks.

Using AI to make teams more productive: AI can improve team dynamics by enhancing work flows, tasks and collaboration.

New AI-Related skills in SFIA: SFIA 9 introduces new and changed skills specifically tailored to AI technologies, including AI ethics, machine learning engineering, and natural language processing. Each new skill addresses the growing demands of AI integration in the workplace.

Changes to SFIA Skills to Incorporate AI: Existing SFIA skills have been updated to include AI components where relevant. This ensures professionals can apply their current expertise in new, AI-driven contexts, with guidance notes clarifying these updates.

Organisation and job design incorporating AI: Effective AI integration requires strategic organisational and job design. This section provides insights into designing roles and structures that leverage AI capabilities, ensuring organisations remain agile and innovative.