EU AI Act Readiness Playbook: Keep Verbatim Coding Fast and Compliant

The EU AI Act is now live, and its phased obligations begin biting over the next 24 months. Prohibited use cases are banned first, but the heavier lift arrives in 2025–2026 when high-risk systems must prove governance, documentation, and human oversight. For market and polling researchers, that covers any AI verbatim coding workflow feeding client decisions—exactly the domain Rundux accelerates.

Yet only a sliver of organisations feel prepared. F5’s 2025 State of Application Strategy study found just 2% of leaders say their company is fully ready for the EU AI Act, while VinciWorks reports that policy knowledge among UK compliance professionals remains low. The gap is not technology—it is process, evidence, and shared language between insights teams and regulators.

Know the EU AI Act milestones that affect verbatim coding

• December 2024: the Regulation enters into force; six months later (June 2025) bans on prohibited AI practices apply. Use this window to audit data intake and disclosure statements.
• December 2025: general-purpose AI (GPAI) providers must deliver technical documentation and comply with transparency duties—critical if your workflow relies on frontier models.
• June 2026: core obligations for high-risk systems apply, including risk management, human oversight, data governance, logging, and post-market monitoring. Most automated thematic analysis in insights programmes falls here.

Treat these dates like you would a brand tracker launch. Build a mini roadmap where each milestone forces a decision: do we have the evidence the Act requests, and can we surface it within two clicks inside Rundux?

Audit your AI verbatims workflow against high-risk criteria

Annex III of the Act classifies AI that profiles individuals for access to services or influences democratic processes as high risk. Verbatim coding used in customer experience, election polling, or employment research almost always feeds decisions that regulators will scrutinise. Keep a single inventory of every Rundux project, its purpose, and the data sources involved.

• Document provenance: store consent terms, sampling notes, and import logs alongside each upload so you can prove lawful data collection.
• Define oversight roles: record who approves coding maps, how often human QA happens, and the thresholds (5% sampling or higher) you enforce.
• Log interventions: capture when analysts merge or retire themes, and generate exports that show the before/after taxonomy so auditors see governance in action.

Rundux already helps here: every project inherits OpenAI’s non-training policy, our audit logs timestamp code edits, and multilingual translations stay inside the same secure workspace. The job now is to package that evidence into a policy deck your legal team endorses.

Keep speed while proving trustworthy AI

The European Commission’s 2025 pro-innovation strategy emphasises both trust and rapid deployment. You do not need to slow your thematic analysis AI experiments—just align safeguards with the Act. Start with the controls you already have: data-layer analytics events that show human-in-the-loop checks, and configurable access controls that restrict who can publish exports.

• Build a runbook: combine Rundux screenshots, GTM event logs, and your QA sampling policy in a short guide. Share it with procurement and compliance before the next RFP.
• Automate alerts: set up pushDataLayer events for every approval step so you maintain a near-real-time governance feed without extra admin.
• Rehearse incident response: simulate a taxonomy rollback or data deletion request and time how long it takes to restore stakeholder confidence.

Upskill the humans driving AI verbatims

Regulation is only as strong as the people applying it. VinciWorks tracked a surge in compliance hires because boards need practitioners who “get” AI risk. Pair your analysts with compliance specialists for quarterly drills—it deepens trust while reinforcing Rundux best practice.

1. Run joint workshops: walk legal, compliance, and research leads through a live Rundux project, highlighting where governance artefacts live.
2. Refresh taxonomy standards: adopt UK spelling, plain-language code names, and cross-team tagging rules so reviewers capture nuance across languages.
3. Track capability metrics: log how many team members can run the full workflow end-to-end and report readiness to executives every quarter.

Being “regulator ready” does not mean reverting to manual coding. It means pairing Rundux speed with visible controls so stakeholders trust both the insight and the process. Start now, build muscle memory, and let the EU AI Act deadline be the moment you prove modern AI verbatim coding can be safer than the old manual queue.