Georgia PE Continuing Education Requirements
Georgia professional engineer registrations renew on an annual cycle. Georgia Code § 43-15-17 states that certificates of registration or licenses are renewable annually, and the Georgia Professional Engineers and Land Surveyors Board describes renewal as a yearly online process. The Board’s current public page states that individual license renewals begin October 22, 2025. The statute requires the executive director to give each licensee notice of the expiration date and renewal fee at least one month before expiration, so Georgia PEs should verify the exact expiration date shown in the Board renewal portal or official renewal notice.
Georgia professional engineers must complete 15 PDH during each 12-month annual renewal period. Georgia Board Rule 180-11-.03 states that every professional engineer is required to obtain 15 PDH each annual renewal period. Georgia Code § 43-15-6(b) authorizes the Board to require continuing education of not more than 15 hours annually for professional engineers and professional structural engineers.
Specific topic PDH Requirements
Georgia’s PE continuing education rule does not state a separate professional-engineering requirement for ethics, Georgia laws and rules, health-safety-welfare, accessibility, building codes, life safety, or sustainability. Qualifying activities must have a clear purpose and objective and must maintain, improve, or expand skills and knowledge relevant to the registrant’s practice. The Board’s continuing education page states that activities may include technical, ethical, or managerial content, but it does not make ethics a separate mandatory PE hour category.
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Qualifying PDH activities
Qualifying PDH activities for Georgia professional engineers include:
Successful completion of college courses.
Successful completion of continuing education courses.
Correspondence, televised, videotaped, audiotaped, and other short courses or tutorials relevant to the professional engineer’s practice.
Presenting or attending seminars, in-house courses, workshops, or professional or technical presentations at meetings, conventions, or conferences relevant to the professional engineer’s practice.
Teaching or instructing in an area relevant to the professional engineer’s practice.
Authoring published papers, articles, or books relevant to the professional engineer’s practice.
Active participation in professional or technical societies, for professional engineers only.
Receiving patents relevant to the professional engineer’s practice.
Georgia allows online and other distance-format learning when the activity otherwise qualifies. Board Rule 180-11-.03 expressly includes correspondence, televised, videotaped, audiotaped, and other short courses or tutorials taken to maintain, improve, or expand skills and knowledge relevant to the professional engineer’s practice. The Board’s continuing education page also refers to online courses, video courses, evening courses, and weekend courses, and states that a PDH credit is roughly equivalent to one clock hour of instruction, rounded to the nearest half hour.
The Georgia Board states that it does not pre-approve courses for PDH credit and that it is the registrant’s responsibility to assure that the activities meet the requirements. Board Rule 180-11-.05 states that the Board has final authority regarding approval of courses, classes, seminars, meetings, and other methods of satisfying the chapter, and the number of PDH allocated to each.
Georgia technical course options
Carry-Forward & Recondkeeping Rules
Georgia permits carryover of a maximum of 7.5 PDH into the subsequent annual renewal period when a professional engineer exceeds the 15 PDH requirement in an annual renewal period. The official rule does not state a separate PE subject-specific carryover limitation because it does not establish a separate PE ethics or laws-and-rules hour requirement.
Georgia registrants are responsible for maintaining continuing education records. Required records include a log showing the activity type, sponsoring organization, location, duration, instructor’s or speaker’s name, and PDH earned, plus attendance verification records such as completion certificates or other documents supporting attendance. The log and supporting records must be maintained for 4 years, and copies may be requested by the Board for audit verification.
Renewal & Exemptions
Georgia uses renewal certification and audit rather than routine submission of all CE documents with every renewal. The Board’s continuing education page states that a registrant will not be renewed unless the registrant certifies on the renewal application that the PDH requirements have been met. Board Rule 180-11-.06 states that the Board randomly audits registrants. A registrant found not to have satisfied continuing education requirements is subject, after notice and hearing, to an initial $500 fine, and continued deficiency after 6 months may result in suspension until the registrant satisfies the Board that the registrant has become compliant.
Georgia exemptions include first-renewal exemption for registrants licensed by examination or comity, certain military service exceeding 120 consecutive days, physical disability, illness, or other extenuating circumstances approved by the Board with supporting documentation, inactive status for qualifying registrants over age 65 who are retired or inactive, and an exemption for registrants over age 65 who are actively practicing and have held a valid Georgia license for the previous 25 consecutive years. Inactive registrants may not practice professional engineering or land surveying in Georgia.
Meet Your General Technical PE Hour Requirements
Frequently Asked Questions
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Georgia professional engineers must complete 15 PDH during each 12-month annual renewal period.
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Georgia certificates of registration are renewable annually. The Board page describes yearly online renewal and states that individual license renewals begin October 22, 2025; the statute requires the executive director to give each licensee notice of the expiration date and fee at least one month before expiration. Licensees should verify their exact expiration date in the Board renewal portal or official notice.
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No. The Georgia Professional Engineers and Land Surveyors Board states that it does not pre-approve courses for PDH credit and that the registrant is responsible for assuring that activities meet the requirements. The Board has final authority on credit during review.
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Georgia registrants must maintain the required log and supporting attendance or completion records for 4 years, and copies may be requested by the Board for audit verification purposes.
Course Syllabus
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Combines six courses covering AI fundamentals, engineering ethics, prompting and documentation, cybersecurity and confidentiality, automation and licensure, and practical AI implementation. Learners examine engineering applications, hallucinations, verification, responsible charge, data protection, recordkeeping, tool selection, workflow design, professional accountability, and the use of platforms such as ChatGPT, Claude, Gemini, and Microsoft Copilot. Includes applied scenarios, exercises, companion videos, and a final assessment for each course.
Bundle includes the following courses:
US-PE-AI-101 Artificial Intelligence in Engineering Practice
US-PE-AI-102 Engineering Ethics in the Age of AI US-PE-AI-103 Prompting, Documentation, and Recordkeeping for AI-Assisted Engineering Work
US-PE-AI-104 Cybersecurity and Confidentiality Risks of AI Tools in Engineering US-PE-AI-105 AI, Automation, and the Future of Engineering Licensure
US-PE-AI-106 Leveraging Artificial Intelligence in Professional Engineering Practice
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This course helps professional engineers understand how generative AI is changing engineering work and how they can adapt without surrendering professional judgment, technical accountability, or responsibility for public safety. Learners review practical workflows using ChatGPT, Claude, Gemini, and Microsoft Copilot for research, document analysis, technical communication, calculation support, project administration, quality control, and professional development.
The course is designed as a practical guide for evaluating, selecting, and applying AI tools in professional engineering workflows. It emphasizes appropriate use cases, productivity gains, effective prompting, verification of AI-assisted outputs, confidentiality protection, and continued professional accountability.
Will AI Replace Engineers? Understanding the Real Career Risk
This module examines the realistic career implications of AI for professional engineers. It distinguishes between tasks, roles, and professions, emphasizing that AI is more likely to change routine production tasks than eliminate professional accountability. Learners assess where AI can accelerate work and where human judgment, field awareness, stakeholder communication, and responsible decision-making remain essential.
Choosing the Right AI Tool for the Engineering Task
This module reviews tool selection as an engineering decision. Learners compare platforms such as ChatGPT, Claude, Gemini, and Microsoft Copilot based on task fit, source grounding, confidentiality controls, workflow integration, traceability, and cost. The module emphasizes matching the tool to the task, data classification, source requirements, and organizational controls rather than selecting a platform by brand preference.
Prompting and Workflow Design for Professional Engineers
This module treats prompting as a form of lightweight technical specification writing. Learners review how to define objectives, context, constraints, sources, output format, uncertainty, and verification requirements. The module emphasizes source-bounded prompting, staged workflows, verification architecture, context management, revision control, and reusable prompt design for engineering tasks.
High-Value AI Applications Across Engineering Disciplines
This module identifies practical AI use cases across engineering disciplines, including research and requirements analysis, drafting and technical communication, calculation support, code review, technical automation, design-option development, trade studies, reports, specifications, quality control, and project administration. The module emphasizes that AI may improve speed and organization, but engineering conclusions still require discipline-specific competence, verification, and accountability.
Using AI Without Jeopardizing Your License, Employer, or Client
This module focuses on professional risk management when using AI. Topics include competence, responsible charge, confidentiality, privacy, security, intellectual property, source integrity, documentation, defensibility, organizational governance, incident response, correction, and adoption planning. The module reinforces that AI does not hold a license, owe a duty to the public, or accept disciplinary consequences; professional duties remain with the engineer.
Ten Key Points and Practical AI Use Checklist
The course closes with a practical review emphasizing that AI changes workflows but not professional accountability. Key points include choosing tools based on task and controls, using prompts as technical specifications, verifying AI-generated technical output, protecting confidential information, documenting material AI use, and retaining responsibility for competence, public protection, responsible charge, truthful communication, and final approval.
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This course examines how artificial intelligence, automation, and digital engineering tools may affect professional engineering practice, licensure expectations, responsible charge, supervision, documentation, and professional accountability. The course focuses on practical issues that licensed engineers are likely to encounter as AI-assisted workflows become more common in research, design support, drafting, analysis, communication, quality control, and project administration.
Learners review the difference between task automation and professional responsibility, the limits of automated outputs, the continuing role of engineering judgment, and the importance of verification, documentation, confidentiality, and final professional review. The course treats AI as a support tool, not as a replacement for professional competence or the licensed engineer’s responsibility for final engineering work.
Course Modules
AI, Automation, and the Changing Engineering Workflow
Introduces how AI and automation are being used to support engineering tasks such as research, drafting, code assistance, calculation checks, data analysis, report preparation, and project communication. The module emphasizes that efficiency gains do not transfer professional responsibility away from the engineer.
Licensure, Competence, and Responsible Charge in an Automated Environment
Reviews how traditional licensure concepts apply when AI tools assist with engineering work. Topics include competence, supervision, responsible charge, review of work prepared by others, and the need for meaningful control over professional decisions.
Human Judgment, Verification, and Quality Control
Focuses on the engineer’s duty to verify AI-assisted or automated outputs before relying on them. Topics include hallucinations, hidden assumptions, incomplete context, outdated information, calculation errors, code errors, and the need to validate conclusions against authoritative sources and engineering principles.
Documentation, Records, and Defensible Use of AI Tools
Explains how engineers can document AI-assisted workflows in a practical and reviewable manner. Topics include prompts, assumptions, source checks, version history, calculation validation, review notes, limitations, and records that support final professional decisions.
Confidentiality, Data Governance, Cybersecurity, and Intellectual Property
Reviews risks associated with entering project information into AI systems, including client confidentiality, proprietary designs, public infrastructure information, personally identifiable information, platform data retention, access controls, and internal AI-use policies.
Supervision, Delegation, and Organizational Use of AI
Examines how AI may affect delegation of work to staff, review of subordinate work, firm-level procedures, software governance, and quality management. The module emphasizes that AI tools may assist teams but do not eliminate the engineer’s obligation to supervise, review, and exercise independent judgment.
Future Practice, Board-Risk Scenarios, and Professional Adaptation
Considers how AI and automation may influence future expectations for engineering practice, licensure, documentation, and professional conduct. Learners review practical scenarios involving overreliance, insufficient review, unclear records, confidentiality failures, and pressure to approve AI-assisted work without adequate verification.
Course Review and Practical Implementation Framework
Provides a final framework for responsible AI use in engineering practice. Learners review when AI use may be appropriate, what must be verified, what should be documented, what information should be protected, and when the engineer should slow down, escalate, or decline to rely on AI-assisted output.
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This course provides professional engineers with a practical overview of how artificial intelligence can support engineering practice while preserving professional judgment, technical accountability, and responsible decision-making. The course covers common AI-assisted uses, including research, drafting, calculation support, code review, design-option development, report preparation, and workflow efficiency. It emphasizes that AI tools may assist with productivity and organization, but engineers remain responsible for verifying technical content, protecting confidential information, applying relevant standards, and exercising independent professional judgment.
Introduction to Artificial Intelligence in Engineering Practice
Introduces what AI means in an engineering setting, the difference between AI-supported work and AI-delegated work, and common engineering tasks where AI may assist. The module establishes the core principle that AI can support engineering tasks, but the engineer remains responsible for judgment and final work products.
Practical AI Capabilities and Limitations
Reviews common AI capabilities such as summarizing documents, drafting outlines, generating checklists, comparing alternatives, supporting code, and organizing workflows. It also addresses limitations, including incorrect output, invented references, misstated requirements, missing assumptions, outdated information, and context errors.
AI for Engineering Research and Technical Information Review
Covers how AI can support research orientation, issue spotting, technical summaries, and review of codes, standards, regulations, and technical information. The module emphasizes that AI-generated research must be verified against controlling sources, applicable editions, jurisdictions, project facts, and authoritative references.
AI for Drafting, Editing, and Technical Communication
Explains appropriate uses of AI for drafting emails, reports, summaries, action items, and technical explanations. The module emphasizes objectivity, accuracy, scope control, and the need to prevent AI-generated wording from inventing facts, overstating certainty, omitting limitations, or changing technical meaning.
AI as Calculation Support
Reviews how AI can assist with calculation planning, variable identification, formula organization, spreadsheet support, unit checks, and reasonableness prompts. The module stresses that AI-assisted calculations require independent verification of inputs, formulas, assumptions, units, intermediate steps, and project applicability.
AI for Code Review and Technical Automation
Addresses AI support for reviewing scripts, spreadsheets, macros, data-processing routines, control logic, and technical automation. Topics include syntax review, test-case generation, documentation, version control, validation, engineering logic, and peer review where code affects technical conclusions or deliverables.
AI for Design Options and Engineering Judgment
Explains how AI can help brainstorm alternatives, organize constraints, compare conceptual options, and prepare preliminary decision matrices. The module emphasizes that AI-generated design options are prompts for professional evaluation, not final engineering decisions.
AI for Reports, Specifications, and Deliverables
Reviews AI use in organizing reports, drafting executive summaries, improving consistency, checking scope alignment, and supporting specification development. The module emphasizes final deliverable review for accuracy, completeness, assumptions, limitations, coordination with drawings and specifications, and avoidance of unsupported claims.
Workflow Efficiency and Quality-Control Applications
Covers AI-assisted workflow improvements such as agendas, meeting summaries, action-item lists, review logs, document consistency checks, lessons learned, and quality-control prompts. The module distinguishes efficiency from accountability and reinforces that AI may support QC but does not replace qualified technical review.
Risk Management, Confidentiality, and Data Governance
Reviews risks involving confidential client information, proprietary designs, nonpublic facility data, security-sensitive information, personal data, trade secrets, bid information, and internal business records. The module also covers approved tools, access controls, retention practices, AI-use policies, and intellectual-property concerns.
Professional Responsibility When Using AI
Connects AI use to professional duties involving competence, responsible charge, accountability, public protection, truthful communication, and objective reporting. The module emphasizes that AI tools do not hold a license, assume responsible charge, sign or seal documents, or accept professional responsibility.
Practical AI-Use Framework for Engineers
Provides a structured framework for responsible AI use: define the task, control the input, review the output, verify technical content, document when appropriate, and take responsibility for the final work product. The module closes with practical decision prompts for engineers using AI in professional workflows.
Training multiple engineers? Ask about group enrollment.