Lexonis

Unleashing AI’s Power to Enhance SFIA-based NICE Cyber Security Work Roles

Judith Clark

For those working in the ever-evolving field of cyber security, the recent work carried out by NIST (National Institute for Standards and Technology) are likely on your radar. Their Workforce Framework for Security, known as the NICE framework, introduced 52 cyber security work roles. In June 2023, the SFIA Foundation undertook to map crucial skills from the SFIA framework (Skills Framework for the Information Age) to these 52 NICE cyber security work roles.

At Lexonis, we saw an opportunity to take this a little further. Our plan was to transform these work roles into well-crafted job profiles, seamlessly integrating them into our extensive library of SFIA-based job profiles to support our clients’ Talent Management applications. To make it even more interesting, we decided to leverage the power of generative AI!

With AI at our fingertips, we accelerated the development process of these job profiles, enriching them with additional attributes that we include in our comprehensive job profile library. Here are the goals we set out to achieve:

  1. Enhancing NICE Work Roles with added depth: we imported the NICE work role names and descriptions into our Lexonis Essentials software platform. Through careful organization and alignment within job family guidance provided by SFIA, we ensured a seamless integration. We also fine-tuned the descriptions, aligning them with Lexonis’ best practices to ensure consistency in the use of action verbs and overall clarity. Additionally, we assigned an appropriate job band/grade and job focus to each job to align them with the attributes in the Lexonis job profiles.
  2. Leveraging AI for Job Responsibilities: At Lexonis, we firmly believe in harnessing AI’s potential to optimize efficiency. Thanks to our integrated GPT technology in the Lexonis Essentials platform, we made significant strides in generating six key responsibility statements for each job. AI proved its capabilities by suggesting relevant responsibility statements for cyber security roles. Through a collaborative “human-in-the-loop” approach, we reviewed and fine-tuned the AI-generated suggestions to ensure they accurately reflected the specific requirements of each role. The combination of our SFIA expertise and AI’s capabilities allowed us to quickly define responsibility statements for all 52 roles with great effect.
  3. Identifying Proficiency Levels: Once we established the job responsibility statements, we circled back to the SFIA Foundation’s skill mappings for each job. Drawing on our deep expertise and extensive knowledge of the SFIA framework, coupled with insights gained from our collaboration with clients, we carefully selected the most suitable proficiency levels for each skill mapped. This comprehensive approach allowed us to create well-rounded job definitions that aligned with our objectives.

Conclusions

AI has proven to be an invaluable tool in our journey to leverage the potential of SFIA and the NICE work roles. By transforming them into refined job profiles and seamlessly integrating them into our extensive library has been a very satisfying piece of work. However, it is crucial to note that human validation remains an essential component in the process. At Lexonis, we have developed intuitive interfaces that facilitate organizations in capturing and reviewing feedback from subject matter experts, ensuring the results meet their exacting standards.

Today, we proudly offer a comprehensive library of job profile templates that encapsulate the essential SFIA skills and proficiency levels for NICE cyber security roles. These seamlessly integrate with our extensive library of SFIA-based job profile templates, empowering our clients to maximize the potential of their workforce.

If you’re curious to witness the impressive results and learn more about utilizing the Lexonis job profile library, the AI-enabled Lexonis Essentials platform, and the SFIA 8 framework, please feel free to contact the Lexonis team!

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