The LICQual Level 2 Diploma in AI Risk Management and Incident Response is a comprehensive qualification for professionals who want to take their AI risk management skills to the next level. As Artificial Intelligence (AI) becomes increasingly integral to business operations, understanding how to manage AI-related risks and respond to potential incidents is essential.
This diploma is designed to help you gain a deeper understanding of the risks associated with AI technologies, including cybersecurity threats, data breaches, and system failures, and provide you with the skills to develop effective incident response strategies. Whether you’re working in AI, cybersecurity, or IT risk management, this course will give you the tools you need to protect your organization from the evolving threats in the AI landscape.
The LICQual Level 2 Diploma in AI Risk Management and Incident Response offers a detailed exploration of AI risk management, designed for those seeking a more in-depth understanding of the complexities involved in safeguarding AI systems. The course covers key topics, such as identifying and assessing AI risks, including privacy concerns, data protection, and security vulnerabilities. You will also learn how to implement risk mitigation strategies to prevent or minimize the impact of potential incidents.
This diploma goes beyond theory, focusing on practical incident response techniques, enabling you to create and execute response plans that mitigate damage from AI-related disruptions. Additionally, you’ll explore how to recover quickly from AI incidents, ensuring minimal downtime and business continuity.
By the end of this course, you’ll be equipped to handle AI risks and incidents with confidence, making you a vital asset to any organization utilizing AI technologies. Whether you’re aiming to enhance your current role or shift into a more specialized AI risk management position, this diploma provides the essential knowledge and skills for success.
Course Overview
Qualification Title
LICQual Level 2 Diploma in AI Risk Management and Incident Response
Total Units
6
Total Credits
36
GLH
120
Qualification #
LICQ2200311
Qualification Specification
To enrol in the LICQual Level 2 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. A basic understanding of AI, technology, or risk management is recommended, though not mandatory. Prior knowledge of IT or business concepts will be beneficial for understanding the course material.
- Experience: While no specific professional experience is required, individuals with a background in technology, cybersecurity, AI, or risk management will find the course more accessible. This diploma is ideal for those looking to advance their skills in AI risk management and incident response.
- English Language Proficiency: Participants should have a basic 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 effective 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 |
|---|---|---|---|
|
LICQ2200311-1 |
Advanced AI Risk Assessment Methods |
6 |
20 |
|
LICQ2200311-2 |
Legal, Ethical, and Regulatory AI Risks |
6 |
20 |
|
LICQ2200311-3 |
Advanced Incident Response & Recovery for AI |
6 |
20 |
|
LICQ2200311-4 |
AI Risk Management Tools and Techniques |
6 |
20 |
|
LICQ2200311-5 |
Organizational Governance for AI Risk |
6 |
20 |
|
LICQ2200311-6 |
AI Risk Communication in a Corporate Environment |
6 |
20 |
By the end of this course, learners will be able to:
Advanced AI Risk Assessment Methods:
- Gain expertise in advanced risk assessment methodologies tailored to AI systems.
- Apply various risk assessment frameworks to evaluate complex AI technologies, identifying potential threats and vulnerabilities.
- Prioritize AI risks based on their impact and likelihood, and develop strategies to mitigate these risks effectively.
Legal, Ethical, and Regulatory AI Risks:
- Understand and apply legal and ethical considerations in AI risk management, ensuring compliance with relevant laws and regulations.
- Analyze the regulatory landscape for AI systems and develop strategies for managing legal and compliance risks.
- Assess the ethical implications of AI technologies and create governance policies that align with ethical standards.
Advanced Incident Response & Recovery for AI:
- Develop advanced incident response strategies specifically designed for AI-related incidents, ensuring minimal disruption.
- Create comprehensive recovery plans for AI systems, focusing on business continuity and the restoration of AI-driven processes after a major incident.
- Conduct post-incident analysis to identify improvements in response protocols and recovery methods.
AI Risk Management Tools and Techniques:
- Explore and apply a range of AI risk management tools and techniques to effectively assess, monitor, and mitigate AI risks.
- Utilize advanced software and frameworks to proactively identify potential risks in AI systems and implement effective mitigation strategies.
- Integrate risk management tools into the daily operations of AI-driven processes, ensuring continuous monitoring and risk reduction.
Organizational Governance for AI Risk:
- Understand the role of organizational governance in managing AI-related risks.
- Develop and implement organizational policies and frameworks for overseeing AI risk management efforts across departments.
- Promote a risk-aware culture within the organization to ensure a unified approach to AI risk management at all levels.
AI Risk Communication in a Corporate Environment:
- Develop clear communication strategies to report and discuss AI risks within the corporate environment.
- Tailor risk communication to different stakeholders, ensuring that technical and non-technical audiences understand the potential impacts of AI risks.
- Create comprehensive reports that document AI risks, mitigation strategies, and incident responses, fostering transparency and informed decision-making.
This diploma is ideal for:
- Professionals with a background in IT, cybersecurity, or risk management who want to specialize in AI risk management and incident response.
- AI developers, data scientists, and engineers seeking to enhance their understanding of AI risks and how to manage them effectively.
- Business leaders and managers overseeing AI projects and initiatives, ensuring proper risk management and compliance strategies are in place.
- Compliance officers and legal advisors responsible for navigating the complex legal, ethical, and regulatory challenges associated with AI technologies.
- Incident response professionals looking to broaden their knowledge of handling AI-related incidents and developing recovery plans for AI systems.
- Consultants and advisors in technology or risk management, aiming to gain expertise in AI risk and incident management for client projects.
- Individuals in governance roles who want to develop comprehensive frameworks for overseeing AI risk management within their organizations.
- Those seeking to advance their career in AI risk management and incident response by obtaining a recognized qualification in the field.
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.
