AI Regulator Engagement Plan and Position Paper Template

Engaging regulators and standards bodies before rules are final. An engagement map, a comment process from flagging to filing, a position-paper template, and an engagement log.

Who this is for: The policy or government-affairs owner who wants the organization's experience to inform AI rulemaking.

Download the kit (Markdown) ↓4 artifacts. Every table also copies as CSV.

1. Regulatory engagement map

Spreadsheet

The bodies worth engaging, the current relationship, upcoming opportunities, and the internal owner.

Template

Body	Relevance to us	Current engagement level	Upcoming opportunities	Internal owner
<regulator / standards body / working group>		none / responsive / active / member	consultations, workshops, drafts open	<name>

Worked example

Body	Relevance	Engagement level	Upcoming opportunities	Owner
EU AI Office	sets guidance we must follow	responsive (we answer consultations)	Art. 6(3) guidance consultation Q1; code of practice workshops	Head of Policy
NIST (AI RMF / GenAI profile)	our control framework aligns to it	active (we submit comments)	profile revision comment window	AI Gov Lead
ISO/IEC JTC 1/SC 42	AI standards we adopt	member (one delegate)	WG meetings quarterly	AI Gov Lead
State AG (CO)	enforces SB205	none	rule implementation feedback	US Counsel

Acceptance criteria

✓The map covers regulators, standards bodies, and working groups relevant to the business.
✓Each has an internal owner and a realistic engagement level, not an aspirational one.
✓Upcoming consultation and comment windows are tracked with dates.

2. Comment process document

Document

How a consultation goes from noticed to filed, with review and approval built in.

Template

The workflow for responding to a consultation or request for comment.

Flag: monitoring surfaces an open consultation; the engagement owner logs it with the deadline
Decide: go / no-go on responding, based on relevance and capacity; recorded
Assign: a drafter and contributing subject-matter experts
Draft: against the relevant position paper; note where we deviate and why
Review: Legal for legal exposure; Comms for messaging; the executive sponsor for sign-off
File: submit before the deadline; capture the confirmation
Log: record in the engagement log; note any follow-up (meeting requests, hearings)

Worked example

EU AI Office Art. 6(3) guidance consultation:

Flagged 2026-11-02, deadline 2027-01-15.
Go decision: yes (directly affects our Resume Screener classification).
Drafter: Head of Policy; SMEs: AI Gov Lead, Employment Counsel.
Draft built on position paper PP-2 (high-risk scoping).
Review: Legal (2 rounds), Comms, GC sign-off 2027-01-08.
Filed 2027-01-10; confirmation archived.
Follow-up: requested a bilateral meeting; pending.

Acceptance criteria

✓Every response goes through a recorded go/no-go decision.
✓Legal and executive sign-off happen before filing.
✓Filed responses and their confirmations are archived.

3. Position paper template

Document

Internal reference documents stating the organization's view on key AI governance questions, reused across engagements.

Template

One per major policy question. Kept current. The source for consultation responses and meetings.

Question: the specific policy issue
Our position: stated in two or three sentences
Rationale: the reasoning, grounded in our operational experience
Evidence: data or examples from our own systems that support the position
What we are asking for: the concrete outcome (a definition, a threshold, a safe harbour, a timeline)
Counter-arguments and our response:
Approved by and date:

Worked example

Question: How should the Article 6(3) derogation for non-high-risk Annex III systems be scoped?
Our position: The derogation should turn on whether the system materially determines the outcome, not on the use-case label alone. A tool that ranks but does not filter, with mandatory human review of every case, should be able to qualify.
Rationale: Our screening tool influences recruiter attention order; recruiters review every application regardless. Treating it identically to an auto-reject system misallocates compliance effort.
Evidence: override rate 12%; 100% of applications are human-reviewed; adverse-impact ratio 0.88 under monitoring.
What we ask for: guidance that lists "does not replace or materially determine the human decision" as a qualifying factor, with documentation requirements.
Counter-arguments: "ranking still shapes outcomes" is fair, which is why we propose documentation and monitoring conditions, not a blanket exemption.
Approved by: GC + Head of Policy, 2026-11-20.

Acceptance criteria

✓Each position is backed by evidence from the organization's own systems, not generic argument.
✓It states a concrete ask, not just a concern.
✓It is approved by Legal and the policy owner and kept current.

4. Engagement log

Spreadsheet

A record of what was filed, attended, and submitted, for continuity and for demonstrating good-faith engagement.

Template

Date	Body	Activity	Reference / topic	Position paper used	Outcome / follow-up	Owner
YYYY-MM-DD		comment filed / meeting / hearing / standard vote

Worked example

Date	Body	Activity	Topic	Position paper	Outcome / follow-up	Owner
2026-09-30	NIST	comment filed	GenAI profile revision	PP-4 (evaluation)	acknowledged; some language adopted in the next draft	AI Gov Lead
2026-10-15	ISO SC 42 WG	meeting attended	AI management system standard	PP-1	volunteered as an editor for one clause	AI Gov Lead
2027-01-10	EU AI Office	comment filed	Art. 6(3) guidance	PP-2	meeting requested, pending	Head of Policy

Acceptance criteria

✓Every engagement activity is logged with the topic and the position paper used.
✓Outcomes and follow-ups are captured, not just the submission.
✓The log is available to Legal and leadership as evidence of engagement.

Governance controls this kit produces evidence for

Completing the artifacts above gives you a head start on the evidence requirements for these controls.

CMP-005

The whole kit is the regulatory engagement process for AI standards development.

CMP-002

The engagement map and its opportunity tracking extend standards and regulatory monitoring into participation.

BRD-004

Position papers and the engagement log support ESG and investor disclosure on responsible AI leadership.

CMP-003

Engagement with voluntary frameworks and standards bodies is tracked alongside binding-rule monitoring.

This kit backs one playbook. Read the full guidance for the reasoning behind each artifact.

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