AIAdoptionFramework

Human capacity Human capabilities represent the fundamental pillar for ensuring the successful adoption of AI technol­ ogies and realizing their enterprise impact. Smart transformation requires specialized, technically quali­ fied talent capable of designing, developing, and operating intelligent models in alignment with national priorities and ethical and technological standards. This human enablement includes developing human capital through talent acquisition, upskilling existing competencies, fostering a supportive work environ­ ment, and building strategic academic partnerships that feed the AI ecosystem with renewed skills and specialized knowledge. Entities aim to achieve a balance between quantity and quality by ensuring a sufficient number of skilled individuals with diverse backgrounds and disciplines that support innovation. Establishing sustainable career development paths is also crucial to preparing the workforce for the rapid evolution of AI, covering both technological skills (e.g., machine learning, data engineering, and cloud computing) and soft skills (e.g., analytical thinking, AI ethics, and data-driven decision-making). Continuity and stability are critical factors in building enterprise knowledge, which requires effective incentive policies, a creative and innovative environment, and opportunities for employees to grow and actively contribute to AI projects. Collaboration with universities and research centers also helps enhance human readiness by providing joint training and research programs and pathways to prepare the next generation of local AI experts. AI Adoption Framework 4.3.2 Professional Development Developing human capabilities is a core pillar of AI adoption. No technology, regardless of how ad­ vanced, can create a lasting impact without talent capable of understanding, adapting, and continuously improving it. Leading entities aim to build training and professional development ecosystems that align with rapid technological transformation and foster a sustainable learning culture within the workplace. Entities adopting AI can build capable teams by taking the following steps: Creating a Career Development Plan: Defining clear professional growth paths based on role re­ quirements.The National Occupational Standards for Data and Artificial Intelligence outlines career tracks and progression requirements. Linking Training to Accredited Certifications: Establishing certified programs that enhance profes­ Establishing a Clearly Defined AI Team: Creating a dedicated AI unit within the organizational struc­ ture, either as a standalone entity or as part of a digital transformation center. Clearly Assigning Roles: Defining responsibilities precisely across model development, data analy­ sis, solution design, and governance management to ensure cohesive efforts. Aligning with the National Occupational Standards Framework (NOSF): Aligning job descriptions and roles with national standards to ensure professionalism and equity. Achieving Clear Team Diversity: Ensuring fair representation, including women and people with disabilities, to support innovation and inclusion. Planning for Annual Team Growth: Linking expansion plans to employment support initiatives to ensure structured and sustainable growth. Simplified Practical Example: The entity establishes an AI unit composed of 35 employees across 10 career tracks. Women make up 40% of the hires, and people with disabilities make up 5%. Job descriptions are updated annually in line with the National Occupational Standards for Data and Artificial Intelligence. ໟ ໟ ໟ ໟ AI Adoption Framework