AI Act Readiness Programme

AI Act Readiness Programme / September 25, 2026

From Obligations to Audit-Ready Value

How can we transform AI Act requirements into practical governance processes that support innovation, reduce risk, and withstand regulatory scrutiny?

The AI Act Readiness Programme was designed to answer exactly that.

Led by experts in AI governance, trustworthy AI, and regulatory compliance, this hands-on workshop helps organizations move beyond uncertainty and build a clear, actionable path towards AI Act readiness.

Whether you are an executive, legal professional, DPO, engineer, product owner, procurement specialist, or innovation leader, this workshop provides the structure, tools, and cross-functional alignment needed to operationalize compliance efficiently and confidently.

This workshop is not about compliance checklists.

It is about creating a repeatable governance system that allows your organization to innovate with confidence while meeting the requirements of the AI Act.

What You Will Achieve

Translate Regulation into Action - Move beyond legal interpretation and learn how to convert AI Act requirements into concrete organizational processes, responsibilities, and workflows.
Build Your AI Governance Framework - Develop a structured inventory of AI systems, establish defensible risk classifications, and understand the obligations that apply to your organization as a provider, deployer, importer, or distributor.
Become Audit-Ready - Learn how to create and maintain the evidence, documentation, and governance controls required to demonstrate compliance and respond confidently to regulatory assessments.
Align Teams Around a Common Goal - Bring together legal, technical, business, procurement, and compliance stakeholders under a shared understanding of responsibilities, risks, and next steps.
Leave with a Practical 90-Day Roadmap - Walk away with a prioritized action plan, governance milestones, and implementation guidance to accelerate your organization's readiness journey.

Why Attend?

Organizations that start preparing early will be better positioned to:

Reduce regulatory and operational risk
Avoid costly compliance gaps
Strengthen internal governance practices
Build trust with customers, partners, and regulators
Enable responsible and sustainable AI adoption

Who Should Attend?

Executive Leaders and Decision Makers
Legal and Compliance Teams
Data Protection Officers (DPOs)
AI, Data and Engineering Teams
Product Managers and Innovation Leads
Procurement and Risk Management Professionals

Secure Your Spot

Places are limited to ensure an interactive and highly practical experience.

Event details

Program

TIME	SESSION
09:30	Opening & The AI Act Clock
10:00	AI Act Essentials & Literacy
11:15	Coffee Break
11:30	Risk Classification Lab
12:45	Lunch
13:45	Obligations into Controls
15:00	Evidence Sprint
16:15	Coffee Break
16:30	90-Day Operational Roadmap
17:30	Closing remarks

Costs

1280,00 euros for one person.

Contact

Please drop us an email - communication@fraunhofer.pt - in case you have any doubts or questions.

Location

TBD, Lisboa

Date

September 25, 2026

Organization

André Carreiro is a Senior Researcher and the Innovation Lead for the "Auditing and Governing AI systems" Innovation Path at Fraunhofer Portugal AICOS. He holds a Ph.D. in Biomedical Engineering from Técnico Lisboa and has worked with machine learning in healthcare and industrial settings since 2010. André is the coordinator of the Horizon Europe project ACHILLES and has been the technical lead for aiceblock™ since 2021. Through his work on aiceblock™, he has spent years developing the technical mechanisms for privacy, robustness, and transparency that are now central to AI Act compliance. His current focus is on helping organizations translate these legal requirements into practical, everyday engineering workflows.

Mariana Pinto is an AI Researcher with a background in Biomedical Engineering. She completed her master's thesis on the discovery and mitigation of algorithmic bias, laying the foundation for her work in trustworthy AI. Her research evolved into the technical implementation of AI auditing dimensions, including bias, robustness, privacy, and transparency, to support compliance in AI-driven systems. As a key contribution, she collaborated on the design of an operationalization framework that bridges regulatory and technical requirements with practical AI audits. The framework was successfully validated in a public-sector AI system, tailored to domain- and use-case-specific requirements.