AI ACT

🇪🇺

Official Regulation 2024/1689 · EU AI Act

7-Day Content
Calendar — AI Act
& AI Agents

A week of high-impact posts on the EU AI Act clauses that matter most to AI agents running in production — and touching critical data.

127

Days Remaining

Days of Content

€35M

Max Fine (or 7% revenue)

Aug '25

Full Enforcement

The EU AI Act entered into force on 1 August 2024. Full enforcement for high-risk AI systems applies from 2 August 2026 — but obligations for GPAI models, prohibited practices, and governance frameworks kicked in earlier. If you have AI agents in production touching sensitive, financial, or personal data — you are already in scope.

127 DAYS TO FULL SCOPE

REF Key Clauses Referenced This Week REGULATION 2024/1689

CRITICAL

ARTICLE 6 + ANNEX III

High-Risk AI Classification

Defines which AI systems are "high-risk." Agents operating in employment, credit, biometrics, critical infrastructure, and legal/judicial contexts fall here automatically.

HIGH

ARTICLE 9

Risk Management System

Continuous risk management lifecycle required for high-risk systems — identification, estimation, evaluation, and mitigation of residual risks throughout the AI lifecycle.

HIGH

ARTICLE 10

Data Governance

Training, validation, and testing data practices must meet quality criteria. Relevance, representativeness, and freedom from errors required. Critical for agents trained on or accessing sensitive data.

HIGH

ARTICLE 13

Transparency & Explainability

High-risk AI must be transparent enough that deployers can interpret outputs correctly. Agents must surface how decisions are reached — not just what the decision is.

HIGH

ARTICLE 14

Human Oversight

Adequate human oversight measures must be technically built-in. Humans must be able to intervene, override, and halt AI agent actions — not just monitor them after the fact.

MEDIUM

ARTICLE 17

Quality Management System

Providers must implement a QMS covering design controls, testing, monitoring, and documentation — analogous to ISO 9001 but AI-specific. Required for all high-risk system providers.

HIGH

ARTICLE 26

Obligations of Deployers

Deployers (not just providers) have direct obligations: use AI only for intended purpose, monitor operation, ensure human oversight capability, and conduct data protection impact assessments.

HIGH

ARTICLES 52–53

GPAI Model Obligations

General-purpose AI models (GPT-class, Claude, Gemini) powering agents face transparency, copyright compliance, and systemic risk reporting obligations when used in production workflows.

CRITICAL

ARTICLE 71

Penalties

Prohibited AI practices: up to €35M or 7% global revenue. High-risk violations: up to €15M or 3% revenue. Incorrect information to authorities: up to €7.5M or 1% revenue.

⚠️

AI agents are not explicitly defined as a separate category in the Act — but they are captured under the broad definition of "AI system" (Article 3(1)). Any autonomous system that "generates outputs such as predictions, recommendations, decisions, or content that influence real or virtual environments" is in scope. An agent making credit decisions, processing employee data, or operating in critical infrastructure is almost certainly classified as high-risk under Annex III.

01 7-Day Content Calendar LIVE · 127 DAYS OUT

Day 1

ARTICLE 6 + ANNEX III · High-Risk Classification

Is Your AI Agent Already Classified as High-Risk?

HOOK POST THREAD

Hook / Opening Post

"127 days until the EU AI Act applies to your production AI agents. If your agent touches any of these 8 categories — you're already classified as high-risk. Here's what that means. 🧵"

Follow with a thread listing Annex III categories: biometrics, critical infrastructure, education, employment, essential services, law enforcement, migration, justice. For each: one sentence on how an AI agent might fall in.

Key Clause Angle

Article 6 + Annex III creates the classification trigger. The list is not exhaustive of use-cases — it's categorical. An agent that automates hiring screening, credit scoring, or patient triage is high-risk by definition, regardless of how small or "assistive" it is.

Art. 6(1)Annex IIIArt. 3(1)

Agent-Specific Angle + CTAs

Agent angle: "Most teams shipping AI agents think the Act is about chatbots. It's not. An agent that reads employee performance data to generate a review draft is processing employment data — that's Annex III, point 4."

CTA: "Which Annex III categories could your agent touch? Drop it in the replies."

#EUAIAct#AIAgents#AICompliance#AIGovernance#HighRiskAI

Day 2

ARTICLE 10 · Data Governance

Your Agent's Data Diet Is Now a Legal Document

DATA POST EXPLAINER

Hook / Opening Post

"Under the EU AI Act, the data your AI agent was trained on — and the data it accesses at runtime — must meet documented quality standards. Your RAG pipeline is now compliance infrastructure."

Open with the statistic: Article 10 requires training data to be "relevant, representative, free of errors and complete to the best extent possible." Ask: can you prove that today?

Key Clause Angle

Article 10(3) mandates data governance practices covering collection, processing, and preparation. Article 10(5) allows processing of special category data (health, biometrics) only where "strictly necessary" — AI agents querying such data must justify it.

Art. 10(2)Art. 10(3)Art. 10(5)

Agent-Specific Angle + CTAs

Agent angle: "Agentic RAG systems retrieving financial records, health summaries, or HR files at query time are performing real-time data access over potentially special-category data. That access must be purposeful, logged, and justified — not just technically possible."

CTA: "Does your team have a documented data governance policy for your agent's retrieval layer? Honest answers only."

#DataGovernance#AIAct#RAG#AIAgents#GDPR

Day 3

ARTICLE 14 · Human Oversight

"Human-in-the-Loop" Is Not Optional. It's Article 14.

POLL THREAD

Hook / Opening Post

"The EU AI Act doesn't just say 'have a human available.' It requires that humans can understand, monitor, and STOP your AI agent — by design, not by accident. Is your agentic system actually built for that?"

Lead with the poll: "What's your current human oversight model for AI agents in production?" Options: Full automation / Human reviews outputs / Human approves before action / No agents yet.

Key Clause Angle

Article 14(1)–(4): High-risk AI must allow natural persons to fully understand the system's capacities, correctly interpret outputs, and decide not to use it or override its output. This means your agent needs interpretable output, an audit trail, and a hard stop mechanism.

Art. 14(1)Art. 14(4)(a)Art. 14(4)(e)

Agent-Specific Angle + CTAs

Agent angle: "Multi-step agents are the hardest case. If your agent autonomously chains tool calls — search → query DB → draft email → send — at what point does a human actually see what's happening? Article 14 requires that oversight is built into the architecture, not bolted on post-deployment."

CTA: "Share your HITL architecture — what does 'pause for human review' actually look like in your agent stack?"

#HITL#AIGovernance#EUAIAct#AgenticAI#ResponsibleAI

Day 4

ARTICLE 13 · Transparency + ARTICLES 52–53 · GPAI

When Your Agent Uses GPT-4 or Claude — Both Layers Are Regulated

EXPLAINER CASE STUDY

Hook / Opening Post

"You're not just deploying an AI agent. You're deploying a stack: your orchestration layer + a GPAI model (GPT-4, Claude, Gemini). Under the EU AI Act, BOTH layers have obligations. Most teams are only thinking about one."

Frame as the "double obligation" problem — model provider obligations (Art. 52–53) AND deployer obligations (Art. 13, 26) stack on top of each other.

Key Clause Angle

Article 52: AI systems interacting with humans must disclose they are AI. Article 53: GPAI model providers must publish training data summaries and maintain model cards. Article 13: Deployers must ensure outputs are interpretable. When your agent takes action on behalf of a user, transparency must exist at both the model and application layer.

Art. 52(1)Art. 53(1)(b)Art. 13(1)

Agent-Specific Angle + CTAs

Agent angle: "A financial services agent using Claude to summarise client portfolios and generate advice drafts is: (1) subject to Art. 13 — output must be explainable to the deployer; (2) reliant on Anthropic's Art. 53 obligations for model-level transparency; and (3) possibly violating Art. 52 if the client doesn't know they're interacting with AI."

CTA: "Does your agent disclose its AI nature at every user-facing touchpoint? Where does transparency break down in your stack?"

#GPAI#LLM#EUAIAct#AITransparency#AIAgents

Day 5

ARTICLE 9 · Risk Management + ARTICLE 17 · QMS

Your Agent Needs a Living Risk Register. Not a PDF. A Process.

THREAD FRAMEWORK

Hook / Opening Post

"Article 9 of the EU AI Act doesn't ask for a risk assessment. It asks for a risk management SYSTEM — continuous, documented, updated across the entire AI lifecycle. One-time audits won't cut it."

Thread format: "Here are the 5 components of an Article 9-compliant risk management system for an AI agent in production" — identification, estimation, evaluation, mitigation, residual risk documentation.

Key Clause Angle

Article 9(1): Risk management must be "a continuous iterative process." Article 9(4): Risk mitigation measures must consider foreseeable misuse. Article 17: Quality management system must cover design, testing, monitoring, and post-market surveillance. Together: compliance is an ongoing engineering discipline, not a legal checkbox.

Art. 9(1)Art. 9(4)Art. 17(1)(e)

Agent-Specific Angle + CTAs

Agent angle: "AI agents in production drift. Prompts change, tools are added, data sources expand. Article 9 requires that your risk register reflects the system as it runs — not as it was designed. Every new tool call your agent can make is a new risk surface that must be evaluated."

CTA: "Is your agent's risk management process manual or automated? What triggers a risk re-evaluation in your team?"

#AIRisk#EUAIAct#MLOps#AIGovernance#QMS

Day 6

ARTICLE 26 · Deployer Obligations

If You Deploy the Agent, You Own the Compliance. Not Just the Vendor.

MYTH BUST HIGH URGENCY

Hook / Opening Post

"Big misconception: 'our AI vendor is responsible for EU AI Act compliance.' Wrong. Article 26 gives deployers direct, non-delegable obligations. If you're running the agent in production — you are on the hook."

Open with a myth vs. reality format. Myth: "Anthropic / OpenAI handles this." Reality: Model provider handles GPAI obligations. YOU handle deployment obligations.

Key Clause Angle

Article 26(1): Deployers must use AI only as intended. Article 26(5): Deployers must conduct Data Protection Impact Assessments (DPIA) where Art. 35 GDPR is triggered. Article 26(6): Deployers must inform providers of any serious incidents. The Act creates a shared but distinct responsibility chain — providers and deployers both have independent obligations.

Art. 26(1)Art. 26(5)Art. 26(6)

Agent-Specific Angle + CTAs

Agent angle: "An enterprise deploying a third-party AI agent (built on LangChain + Claude) to process customer support data cannot point to Anthropic when the regulator asks about human oversight mechanisms, data access logs, or incident reporting. Article 26 is your problem."

CTA: "Have you mapped where your obligations end and your AI provider's begin? Most teams haven't. What does your vendor contract actually say about compliance responsibilities?"

#EUAIAct#AICompliance#DeployerObligations#EnterpiseAI#AILaw

Day 7

ARTICLE 71 · Penalties + Week Summary

127 Days Left. Here's Your Compliance Checklist for AI Agents.

CALL TO ACTION THREAD

Hook / Opening Post

"We spent a week unpacking the EU AI Act for AI agents in production. Day 7: the checklist. 7 questions every team deploying AI agents touching critical data needs to answer before August. 🧵"

Thread format — one question per article covered this week. Each question is binary: "Can you answer YES to this right now? If not, that's your compliance gap."

The 7-Question Checklist

1. Have you classified your agent under Annex III? (Art. 6)
2. Can you document your agent's data governance? (Art. 10)
3. Is human override technically built into your agent? (Art. 14)
4. Are all user-facing touchpoints disclosed as AI? (Art. 52)
5. Do you have a continuous risk management process? (Art. 9)
6. Have you mapped deployer vs. provider obligations? (Art. 26)
7. Do you have incident reporting and logging in place? (Art. 26(6))

Final CTA + Penalties Hook

Penalties hook: "Article 71 penalties for high-risk violations: up to €15M or 3% of global annual revenue. For prohibited practices: €35M or 7%. These aren't theoretical. National authorities are building enforcement capacity right now."

CTA: "Save this checklist. Share it with your compliance team. And if you're building tooling to automate any part of this audit trail — I'd genuinely love to talk."

#EUAIAct#AICompliance#AIAgents#AIGovernance#RegTech#CISA

02 Recommended Posting Schedule X.COM + LINKEDIN

Day	Best Post Time	X.com Format	LinkedIn Format	Engagement Tactic
Day 1 — High-Risk Classification	09:00 BST / 10:00 CET	Hook tweet + 8-part thread	Long-form post with Annex III list	End with: "Which category could your agent touch?" — drives replies
Day 2 — Data Governance	08:30 BST / 09:30 CET	Stat-led single tweet → thread	Document post: Data Governance Checklist	Ask if teams have a data governance policy for their retrieval layer
Day 3 — Human Oversight	12:00 BST / 13:00 CET	Poll first, then thread	Poll + explainer on Art. 14	Poll creates built-in engagement. Follow up on results next day.
Day 4 — GPAI Double Obligation	09:00 BST / 10:00 CET	Thread with model provider diagram	Case study format — fintech agent example	Tag model providers (OpenAI, Anthropic) in the post — expands reach
Day 5 — Risk Management	08:00 BST / 09:00 CET	Framework thread: 5-part risk system	Carousel-style numbered post	Ask what triggers a risk re-evaluation — operational question drives replies
Day 6 — Deployer Obligations	10:00 BST / 11:00 CET	Myth-bust format (short, punchy)	Long-form with myth vs. reality table	Ask about vendor contracts — controversial and specific = high engagement
Day 7 — Checklist + CTA	09:00 BST / 10:00 CET	Thread: 7 questions + penalties	Checklist document + DM CTA	Explicitly ask people to save/share. Week 1 CTA for your collaboration ask.

03 Execution Tips for Maximum Reach STRATEGY

Always Cite the Article Number

Saying "Article 14" instead of "the human oversight bit" signals you've read the regulation. IT auditors, compliance leads, and legal teams respond to precision. It also differentiates your content from generic "AI regulation is coming" posts.

Make It Operational, Not Theoretical

Every post should answer: "What does my team actually need to DO?" Abstract compliance commentary is low-engagement. "Here's what Article 10 means for your RAG pipeline" is actionable and shareable.

Use the 127-Day Urgency Every Day

Open every post with a countdown or deadline reference. Urgency is your primary engagement driver. "127 days" is more visceral than "enforcement begins August 2025."

End Every Post With a Question

Compliance content can feel one-directional. Each post should close with a specific operational question — not "thoughts?" but "What does human override look like in your architecture?" — to surface qualified leads in the replies.

Cross-Post to LinkedIn With More Depth

X threads work as punchy hooks. LinkedIn posts can be longer and more structured — use the same content but expand the clause analysis and add a practical checklist. Compliance leads and IT auditors skew LinkedIn.

Week 2: Pitch Your Tooling — Naturally

After 7 days of credibility-building, Day 8 is when you can post: "I'm building tools to automate the compliance audit trail that Articles 9, 13, and 17 require. If that's your problem too — DMs open." The audience is pre-qualified from the week.

7-Day ContentCalendar — AI Act& AI Agents

7-Day Content
Calendar — AI Act
& AI Agents