Rule 505-3-.114. [Effective 7/1/2026] Artificial Intelligence for Educators Endorsement

1. (1) Purpose. This rule states field-specific content standards for approving endorsement programs that prepare certified educators and individuals employed in education adjacent settings to understand, use, and model Artificial Intelligence in the field and at the grade level of their base certification and supplements requirements in Rule 505-3-.01, REQUIREMENTS AND STANDARDS FOR APPROVING EDUCATOR PREPARATION PROVIDERS AND EDUCATOR PREPARATION PROGRAMS.
2. (2) In-Field Statement. Completers of the Artificial Intelligence for Educators Endorsement program have strengthened and enhanced competency in the Foundations of Artificial Intelligence in Education, Classroom Application for Using Artificial Intelligence in Education, and Leadership of Artificial Intelligence in Education. Completers of the Artificial Intelligence for Educators Endorsement program are qualified to provide direct instruction to students in the grade levels and/or field(s) of their base teaching certificate(s), or to serve as a resource for schools, districts, and other education settings.

3. (3) Definitions.

   1. (a) Artificial Intelligence (AI) is defined as the capability of machines to perform tasks that typically require human intelligence, such as learning, reasoning, and problem-solving.
   2. (b) AI Literacy refers to the knowledge and skills necessary for students and educators to effectively understand, evaluate, and use artificial intelligence technologies in a responsible and ethical manner.
   3. (c) AI System is defined as a software application that uses generative models to produce new content such as text, images, audio, or video based on input data, supporting teaching and learning while requiring human oversight for accuracy, ethics, and alignment with educational goals.
   4. (d) AI Tools are software applications that utilize artificial intelligence techniques to perform tasks that typically require human intelligence, enhancing productivity and creativity across fields.
   5. (e) Iterative Prompting is the process of refining and improving AI responses through successive rounds of prompts, using each output to inform and adjust the next prompt until you achieve the desired result.
   6. (f) Micro-Endorsement is a credential indicating a candidate has successfully demonstrated competence in a defined portion of endorsement program content standards.
   7. (g) Prompt Engineering is defined as the practice of crafting and refining input instructions (prompts) to get AI systems to produce desired outputs.
   8. (h) Prompting is the act of providing instructions, questions, or context to an AI system to guide it toward generating a specific response or completing a particular task.

4. (4) Requirements.

   1. (a) A GaPSC-approved educator preparation provider may seek state approval to offer this field as either a stand-alone endorsement program or as an endorsement program embedded in a GaPSC-approved initial preparation program or an advanced (degree-only) preparation program. In addition to meeting all applicable approval requirements and standards, embedded endorsement programs must meet requirements specified in paragraph (3) (e) 4. (ix) of GaPSC educator preparation rule 505-3-.01, REQUIREMENTS AND STANDARDS FOR APPROVING EDUCATOR PREPARATION PROVIDERS AND EDUCATOR PREPARATION PROGRAMS.
   2. (b) Approval to offer the Artificial Intelligence for Educators Endorsement qualifies the EPP to recommend for the micro-endorsement: Foundations of Artificial Intelligence in Education Micro-Endorsement, candidates who are actively enrolled in the program and who demonstrate mastery of standards 1-4.

   3. (c) Program Admission Requirements.

      1. 1. Stand-alone Programs.

         1. (i) Candidates admitted to a stand-alone Artificial Intelligence for Educators Endorsement must hold a valid, level 4 or higher Professional, Advanced Professional, or Lead Professional teaching certificate, Life certificate, Induction, or Provisional certificate. Candidates holding a Provisional certificate at program completion will not earn the Endorsement until their certificate is converted to a Renewable Professional certificate or a 5-Year Induction certificate at level 4 or higher.
         2. (ii) Prospective candidates who are currently employed in an education or education adjacent setting, yet who are not certified, may be admitted to a stand-alone Artificial Intelligence for Educators Endorsement at the discretion of the EPP. For such candidates, completion of the program will not earn the endorsement until a 5-Year Induction Certificate at level 4 or higher or a Renewable Professional Certificate is obtained.

      2. 2. Embedded Programs.

         1. (i) Candidates admitted to an Artificial Intelligence for Endorsement embedded in an initial preparation program must hold the Pre-Service certificate or Provisional certificate. Candidates holding a Pre-Service certificate at program completion will not earn the endorsement until their certificate is converted to the 5-Year Induction certificate at level 4 or higher. Candidates holding a Provisional certificate at program completion will not earn the endorsement until their certificate is converted to a Renewable Professional certificate.
         2. (ii) Candidates admitted to an Artificial Intelligence for Educators Endorsement embedded in an advanced (degree only) preparation program must hold a valid, level 4 or higher Professional, Advanced Professional, or Lead Professional teaching certificate, Life certificate, or 5-Year Induction certificate at level 4 or higher to obtain the endorsement.

   4. (d) To receive approval, a GaPSC-approved educator preparation provider shall offer a preparation program described in program planning forms, catalogs, and syllabi addressing the following standards:

      1. 1. AI Foundational Concepts and Systems Thinking. The candidate demonstrates how AI systems work, their capabilities and limitations, and implications for educational practice.
      2. 2. Implementation and Sustained Use of AI. The candidate evaluates, selects, and implements AI tools using evidence-based criteria that prioritize pedagogy, privacy, and long-term viability.

      3. 3. Responsible and Ethical Use of AI. The candidate understands responsible and ethical use of Artificial Intelligence in education:

         1. (i) Candidates understand and critically apply fair, ethical, and legal principles in all uses of AI in education.
         2. (ii) Candidates identify and address bias and potential harm when using AI in education.
         3. (iii) Candidates understand how to protect student privacy and data when using AI tools for education.
         4. (iv) Candidates ensure informed consent is acquired when necessary while using AI tools for education, aligned with local, state, and federal guidelines.
         5. (v) Candidates select and use AI tools that meet accessibility requirements for all learners.
         6. (vi) Candidates maintain transparency with students, families, colleagues, and administrators when using AI for educational purposes.

      4. 4. Assessing AI Performance and Ensuring Quality. The candidate recognizes and responds to the evaluation and quality assurance of Artificial Intelligence output in education:

         1. (i) Candidates critically evaluate AI systems and outputs for transparency, reliability, bias, accuracy, fairness, and appropriateness.
         2. (ii) Candidates demonstrate accountability for the use of AI tools and their impacts.
         3. (iii) Candidates make informed decisions about when and how to use AI to support student learning.
         4. (iv) Candidates demonstrate prompt engineering as a skill, using iterative prompts to increase the usability of differentiated outputs.

      5. 5. AI for Planning and Differentiation. The candidate demonstrates the ability to use Artificial Intelligence for informed planning and differentiation of instruction aligned to Georgia Standards for Excellence.

         1. (i) Candidates use AI to plan and differentiate instruction ensuring accessibility and human oversight to meet learner needs.
         2. (ii) Candidates leverage AI to create varied, accessible, and engaging learning materials across text, image, audio, and video formats while maintaining instructional quality and accessibility standards.
         3. (iii) Candidates apply AI in ways that honor disciplinary thinking (i.e. scientific inquiry, mathematical reasoning, historical analysis, writing process, etc.), practices, and standards specific to their content area(s) to prepare students for field-specific AI uses.

      6. 6. Using AI for Assessment Design. The candidate applies academic integrity when evaluating assessment practices using Artificial Intelligence:

         1. (i) Candidates design authentic assessments that account for student access to AI and protect academic integrity.
         2. (ii) Candidates demonstrate how to use AI responsibly for feedback and rubric design, clearly distinguishing AI-generated feedback from teacher-generated feedback.

      7. 7. AI and Data Literacy. The candidate applies data literacy and ethical decision-making when using Artificial Intelligence to interpret data responsibly:

         1. (i) Candidates demonstrate how to use AI to generate insights that guide differentiated and effective instruction while protecting student privacy and data.
         2. (ii) Candidates understand the statistical limitations of AI including when it is inappropriate to use AI for data analysis while protecting student privacy and data.

      8. 8. Digital Citizenship and Learner Use of AI. The candidate implements age-appropriate use of AI (P-5, 6-8, and 9-12) when using Artificial Intelligence:

         1. (i) Candidates teach students to protect their personal data and how to recognize and avoid unsafe AI practices.
         2. (ii) Candidates teach students to question AI outputs for accuracy, bias, and fairness.
         3. (iii) Candidates teach students to use AI as a learning partner rather than a replacement for personal understanding and communication.
         4. (iv) Candidates teach students the importance of adhering to copyright and intellectual property concerns related to AI-generated content.

      9. 9. Advocate and Model Ethical AI Practices. The candidate applies knowledge of collaboration, communication, and policy alignment when using Artificial Intelligence in Education:

         1. (i) Candidates engage colleagues, families, and stakeholders in transparent and informed AI use aligned with ethical and legal policies.
         2. (ii) Candidates demonstrate the ability to model transparency while leading and/or supporting professional learning related to AI uses.
         3. (iii) Candidates demonstrate the ability to communicate and collaborate with colleagues, families, and stakeholders about ethical and effective AI uses aligned with local, state, and federal guidelines.
         4. (iv) Candidates demonstrate the ability to advocate for policies and practices that promote ethical, equitable, and effective AI uses in educational settings.

      10. 10. Professional Practice in AI Innovation. The candidate sustains professional growth by staying informed about emerging AI tools, research, limitations, and instructional implications, and by evaluating how these developments may enhance or challenge existing practices.

          1. (i) Candidates thoughtfully reflect on how AI tools support or influence their work while maintaining professional integrity in the field of education.

Authority: O.C.G.A. § 20-2-200.

History. Original Rule entitled "Artificial Intelligence for Educators Endorsement" adopted. F. June 10, 2026; eff. July 1, 2026, as specified by the Agency.