The LICQual Level 3 Diploma in AI Risk Management and Incident Response is a comprehensive, advanced-level qualification designed for professionals looking to take their expertise in AI risk management and incident response to the next level. As AI continues to revolutionize industries, the risks associated with these technologies grow more complex.
This diploma equips you with the advanced skills and knowledge required to manage AI-related risks effectively, respond to incidents swiftly, and ensure organizational resilience. With a focus on real-world applications, this course will enable you to protect AI systems and navigate the challenges of AI governance, ensuring compliance with legal and regulatory standards.
The LICQual Level 3 Diploma in AI Risk Management and Incident Response delves deep into the intricacies of managing and responding to AI-related risks. Over six in-depth units, you’ll gain expertise in advanced risk assessment techniques, AI incident detection, and recovery strategies.
You’ll also explore the legal, ethical, and regulatory aspects of AI risk, learning how to ensure your organization stays compliant and aligned with industry standards. This course emphasizes the creation and implementation of robust AI risk management frameworks, effective communication strategies for risk reporting, and building incident response teams capable of handling AI-related crises.
Designed for professionals in IT, cybersecurity, and AI governance, this diploma will prepare you to take on leadership roles in AI risk management. Whether you’re an experienced practitioner or an aspiring expert, the LICQual Level 3 Diploma provides you with the tools and knowledge needed to mitigate risks and safeguard AI systems in an ever-evolving digital landscape. This qualification will not only boost your career but also ensure that you remain at the forefront of AI risk management and incident response.
Course Overview
Qualification Title
LICQual Level 3 Diploma in AI Risk Management and Incident Response
Total Units
6
Total Credits
36
GLH
120
Qualification #
LICQ2200312
Qualification Specification
To enrol in the LICQual Level 3 Diploma in AI Risk Management and Incident Response, candidates must meet the following entry requirements:
- Educational Requirements: Applicants should have a minimum of a high school diploma or equivalent. It is recommended that participants have a basic understanding of AI, technology, or risk management. Prior education in IT, business, or a related field will provide a solid foundation for the course.
- Experience: While prior professional experience in AI, cybersecurity, or risk management is not mandatory, it is highly recommended. The course is best suited for individuals with a foundational understanding of AI technologies or risk management principles. Those with experience in managing or overseeing IT systems, AI projects, or business operations will benefit most.
- English Language Proficiency: Participants should have a sufficient level of English proficiency to understand course materials, engage in discussions, and complete assessments. A general understanding of written and spoken English is necessary for successful participation in the course.
- Age Requirement: Candidates must be at least 18 years of age at the time of enrolment.
|
Qualification# |
Unit Title |
Credits |
GLH |
|---|---|---|---|
|
LICQ2200312-1 |
Strategic AI Risk Management |
10 |
40 |
|
LICQ2200312-2 |
Developing AI Incident Response Plans |
10 |
40 |
|
LICQ2200312-3 |
Ethical and Legal Implications in AI Risk |
10 |
40 |
|
LICQ2200312-4 |
AI Risk Mitigation & Prevention Strategies |
10 |
40 |
|
LICQ2200312-5 |
Building & Leading an AI Risk Management Team |
10 |
40 |
|
LICQ2200312-6 |
Continuous Improvement in AI Risk Management |
10 |
40 |
By the end of this course, learners will be able to:
Strategic AI Risk Management:
- Develop and implement strategic AI risk management frameworks tailored to organizational needs.
- Identify key AI risks and assess their potential impact on business operations, ensuring that proactive measures are in place.
- Evaluate and prioritize AI risks based on business goals and technological landscapes to align risk management strategies effectively.
Developing AI Incident Response Plans:
- Create comprehensive AI incident response plans to address a wide range of potential AI-related incidents.
- Design step-by-step procedures for AI incident detection, containment, eradication, and recovery, ensuring minimal business disruption.
- Customize incident response plans to specific organizational structures and AI systems, improving responsiveness and recovery efficiency.
Ethical and Legal Implications in AI Risk:
- Analyze the ethical implications of AI technologies and implement strategies to ensure compliance with relevant legal and regulatory frameworks.
- Address legal and compliance challenges, ensuring that AI risk management practices align with industry standards and government regulations.
- Implement governance strategies that prioritize ethical AI development and reduce the risk of legal liabilities.
AI Risk Mitigation & Prevention Strategies:
- Develop and implement advanced AI risk mitigation and prevention techniques to safeguard systems from potential threats.
- Identify emerging risks within AI technologies and apply innovative strategies to reduce the likelihood of AI system failures and security breaches.
- Promote a culture of proactive risk management through the integration of AI risk prevention practices across the organization.
Building & Leading an AI Risk Management Team:
- Build, lead, and manage a high-performing AI risk management team capable of handling complex AI-related risks and incidents.
- Develop team structures and roles, ensuring effective collaboration and coordination across different departments.
- Foster a culture of continuous learning and adaptability within the AI risk management team to keep pace with evolving AI technologies.
Continuous Improvement in AI Risk Management:
- Implement continuous improvement processes for AI risk management, ensuring that strategies evolve in line with technological advancements and business changes.
- Regularly evaluate and refine AI risk management practices based on feedback, incident reports, and evolving industry trends.
- Establish mechanisms for monitoring, reporting, and refining AI risk management efforts to achieve long-term success and resilience.
This diploma is ideal for:
- Senior professionals in IT, cybersecurity, or risk management seeking to deepen their expertise in AI risk management and incident response.
- AI specialists, engineers, and data scientists looking to enhance their understanding of managing risks and responding to incidents within AI systems.
- Managers and team leaders responsible for overseeing AI projects, who need to develop and implement effective risk management strategies.
- Compliance officers, legal advisors, or professionals involved in ensuring AI systems meet regulatory and ethical standards.
- Professionals interested in building and leading high-performing AI risk management teams to safeguard AI-driven technologies.
- Business executives and decision-makers responsible for implementing strategic risk management frameworks to address AI-related challenges.
- Consultants or advisors in technology, cybersecurity, or risk management who want to specialize in AI-related risks and incidents.
- Those who are aiming to pursue leadership roles in AI risk management, incident response, or corporate governance.
- Individuals with a foundational understanding of AI and risk management who want to take their skills to an advanced level for career growth.
Assessment and Verification
All units within this qualification are subject to internal assessment by the approved centre and external verification by LICQual. The qualification follows a criterion-referenced assessment approach, ensuring that learners meet all specified learning outcomes.
To achieve a ‘Pass’ in any unit, learners must provide valid, sufficient, and authentic evidence demonstrating their attainment of all learning outcomes and compliance with the prescribed assessment criteria. The Assessor is responsible for evaluating the evidence and determining whether the learner has successfully met the required standards.
Assessors must maintain a clear and comprehensive audit trail, documenting the basis for their assessment decisions to ensure transparency, consistency, and compliance with quality assurance requirements.