New Roles · AI Operators & Cross-Functional Roles

Responsible AI Officer. The role, the market signal, and how to build it in your org.

Sets AI governance policy and coordinates risk review across the organization. Works with business, legal, security and technical owners on decision authority, evidence, escalation and accountability.

In a workforce of people and AI agents, this role takes shape around the workflows it supports. Define its responsibilities and handoffs, then prepare people to perform that work.

Source snapshot 2026-07-17. Postings do not confirm that a vacancy is still open.

58 postings · 50 distinct titles · from 264,613 real job postings · see the source snapshot →

What the market calls it
Chief Responsible AI OfficerAI Ethics OfficerAI Impact OfficerHead of AI SafetyOffice of Responsible AI
Employers in this source snapshot
Accenture 13Bmo 5PwC 4Bosch 3Mastercard 3

What the postings ask this role to do

1,168 tasks extracted from real Responsible AI Officer job descriptions, classified Automate / Augment / Human-only. In this source classification, 2.3% of task statements are automation candidates. The share does not measure working time or demonstrated agent performance.

Automate
  • Set up a job alert
  • Join the talent network
  • Prepare governance summaries.
  • Track defects within azure devops.
  • Collect audit evidence for sox it compliance.
Augment
  • Perform reperformance testing, sampling, and evidence validation to assess control execution.
  • Develop strategies to ensure the ethical and responsible use of artificial intelligence technologies.
  • Draft clear, risk-based issue descriptions and contribute to discussions on risk severity and impact.
  • Document process flows, control descriptions, and key risks based on walkthroughs and artifact reviews.
  • Develop and document test steps and test scripts aligned to approved testing methodologies and risk frameworks.
Human-only
  • Facilitate training sessions to enhance team understanding of responsible ai practices.
  • Contribute to continuous improvement of data & ai governance testing and advisory practices.
  • Support ongoing governance forums, working groups, or risk discussions related to data and ai governance.
  • Assist stakeholders in understanding risk and control expectations, governance standards, and testing outcomes.
  • Apply professional judgment to determine control effectiveness, identify control gaps, and assess residual risk.
How we build it in your org

From the market's version of this role to your version of it

1. Define workflow responsibilities
Start with the actual work this role must improve and the output your enterprise needs. Define how people and agents share the decisions, exceptions and handoffs. Task Intelligence examines the tasks within that work.
2. Define your version
Your team defines the role around its own systems, data, rules and responsibilities. Agree what the person configures, builds, reviews or supervises and what technical support is needed.
3. Practise and assess readiness
Build on the domain and technical expertise your people already bring. Shape a practical project around your enterprise context, then use relevant Simulations, GenAI Sandboxes and Skill Validation Assessments to review the work and capability demonstrated.

Start with the work, not the org chart.

Define what this role will build, configure, decide and check. Connect that work to an enterprise-specific project and agreed assessment evidence.