It's designed for risk owners, IT/security teams, data and AI engineers, consultants, legal/ethical advisors, leaders overseeing AI deployments, and executives needing strategic oversight of AI risk.
The course is suited to professionals responsible for identifying and managing AI risks, including IT and security teams, data scientists and engineers, and AI developers working on design, deployment, and maintenance.
It also supports consultants and legal/ethical advisors focused on AI regulation and societal impact. Leaders overseeing AI implementations and executives benefit by gaining a structured approach to AI risk governance and compliance-aligned decision-making.
AI risk programs scale when legal, security, engineering, and business owners share a common workflow and vocabulary for risk decisions.
“Best results come when technical and governance stakeholders learn together.”
This ISO/IEC 42001 Lead Implementer course trains professionals to design and deploy an Artificial Intelligence Management System that stands up to regulatory, ethical, and operational scrutiny.
View courseThis training is designed for professionals who must structure, operate, and defend an information security risk management process aligned with ISO/IEC 27005:2022. Participants work through the full risk lifecycle, from context definition to treatment decisions and executive reporting.
View courseThis course prepares participants to manage, govern, and scale AI initiatives aligned with business objectives. It addresses growing pressure to control AI risks, ensure transparency, and deliver measurable value from AI investments. Participants evaluate AI opportunities, structure governance, design dashboards, and automate workflows using no-code tools. Abilene Academy teaches through real case execution, Power BI and n8n labs, and exam-focused coaching led by active consultants. It is designed for AI project managers, business leaders, compliance professionals, and transformation leads.
View courseIdentify AI risks through lifecycle analysis: data risks (bias, quality), model risks (drift, overfitting), deployment risks (adversarial attacks, misuse), and operational risks (feedback loops, unintended impacts).
The EU AI Act (Regulation (EU) 2024/1689) entered into force on 1 August 2024 and applies in phases. Bans on prohibited AI have applied since 2 February 2025; governance and general-purpose AI (GPAI) obligations since 2 August 2025; the transparency rules since 2 August 2026; and, since the Digital Omnibus on AI (Regulation (EU) 2026/1744), the Annex III high-risk rules apply from 2 December 2027. High-risk systems embedded in already-regulated products have until 2 August 2028.
AI risks are dynamic, probabilistic, and context-dependent. Unlike static IT systems, AI models degrade over time, produce unexpected outputs, and fail in ways difficult to predict or test comprehensively.
The exam is domain-based, covering AI risk concepts and regulations, governance, identification and analysis, evaluation/treatment/monitoring, and organizational learning and performance improvement.
ISO/IEC 42006 changed who can certify you, ISO 19011:2026 changed how the audit runs, and the Omnibus moved the AI Act deadlines. What an AIMS audit demands, evidence by evidence.
ISO 27001 gives you a head start on ISO 42001, not a free pass. Here is what carries over, what is new, and how to extend your ISMS to an AIMS, step by step.
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