AI Risk Assessment Process
Understanding exposure before it becomes a problem. An AI risk assessment is not about predicting every outcome. It's about knowing where AI touches people decisions and whether leadership has control.
In HR, that clarity matters.
What an AI Risk Assessment Is
and what it is not
What It Is
An AI risk assessment answers a simple question: Where could AI materially affect people, and are those decisions defensible?
It is a leadership review of how decisions are actually made. It focuses on impact, accountability, and control.
What It Is Not
- A technical audit
- A vendor certification exercise
- A legal memo
- A one-time event
It goes beyond compliance checklists. It examines real decision-making processes.
Why HR Needs Its Own AI Risk Assessment
Personal Impact
HR decisions affect jobs, income, and opportunity. The stakes are high for individuals.
Hidden Risk
Risk scales quickly. Bias can hide. Documentation gaps matter. Accountability can blur.
Impact Focus
An HR-focused assessment looks at impact, not just technology. People outcomes drive the analysis.
Step 1: Identify Where AI Shows Up
The first step is visibility. Many teams discover AI in places they did not expect.
1
Recruiting & Hiring
Resume screening tools, chatbots, applicant tracking systems, interview scheduling platforms.
2
Assessments & Screening
Skills tests, personality assessments, video interview analysis, background check automation.
3
Performance & Engagement
Performance analytics, engagement surveys, feedback tools, sentiment analysis platforms.
4
Workforce Planning
Predictive analytics, headcount modeling, succession planning, attrition forecasting tools.
5
Operations & Monitoring
Scheduling systems, productivity tracking, time monitoring, workflow optimization tools.
Step 2: Understand How Decisions Are Influenced
Not all AI use carries the same risk. The assessment looks at the level of influence.
Informational Use Only
AI provides data or insights. Humans make decisions independently. Risk is lower.
Decision-Support Use
AI recommends options. Humans evaluate and choose. Risk is moderate.
Decision-Influencing Use
AI shapes or determines outcomes. Human review may be limited. Risk is higher.
The closer a tool gets to determining outcomes, the higher the risk. This distinction matters for oversight.
Step 3: Classify Risk Level
Each use case is evaluated based on key factors. This step separates noise from real exposure.
Impact on Individuals
Does it affect employment, compensation, or opportunity?
Decision Type
Is it hiring, performance, discipline, or termination?
Review Capability
Can outputs be reviewed or overridden easily?
Volume & Scale
How many people are affected? How often?
Step 4: Review Human Oversight
This is where most gaps appear
AI can inform decisions. Humans must own them.
Where humans review AI outputs
Is review meaningful or perfunctory? Does it happen before decisions are finalized?
Who makes final decisions
Is authority clear? Do decision-makers understand the AI's role?
How overrides are handled
Can AI recommendations be rejected? Is override authority documented?
Whether judgment is documented
Are decisions recorded? Can the rationale be explained later?
Step 5: Review Documentation and Practices
Risk is not just about what happens. It's about what can be shown later.
Internal descriptions
How tools are described internally to managers and staff
Decision documentation
How decisions are recorded and maintained over time
Concern escalation
How concerns are raised, tracked, and resolved
Change tracking
How updates to tools or processes are documented
You don't document everything. You document what matters. Focus on decisions that affect people outcomes.
Step 6: Evaluate Vendor Risk
Vendors are part of the assessment. Using a vendor does not remove employer accountability.
What vendors disclose
Do they explain how their AI works? What data is used? What factors influence outputs?
What remains opaque
Are there black boxes? Proprietary algorithms? Limited visibility into decision logic?
Where responsibility sits
Who is accountable for outcomes? What does the contract say? What are the limitations?
How updates are communicated
Are you notified of changes? Do updates affect risk? Is there a review process?
Step 7: Define Practical Mitigation
The output of an assessment is not a report. It's decisions. The goal is control, not perfection.
Increase oversight
Where human review needs to be strengthened or formalized
Change processes
Where workflows should be redesigned for better control
Add documentation
Where records are needed to support decisions
Accept risk
What risk is acceptable given business needs
Phase implementation
What can be addressed later without material exposure
How This Fits Into Fractional CHRO Work
AI risk assessment is not a standalone exercise. It integrates into ongoing HR leadership.
As a fractional CHRO, I:
- Conduct assessments as part of HR leadership
- Integrate findings into daily practice
- Support leaders through changes
- Revisit assessments as tools evolve
This keeps risk management practical and current. It becomes part of how HR operates, not a separate initiative.
Connection to the Colorado AI Act
For Colorado employers, this process supports compliance. The law has clear expectations.
Identification
Identify high-risk AI systems affecting employment decisions
Human Oversight
Ensure meaningful human review of AI-influenced decisions
Risk Mitigation
Implement reasonable measures to reduce identified risks
Documentation
Maintain appropriate records of processes and decisions
A structured assessment makes those expectations manageable. It provides the foundation for ongoing compliance.
When an Assessment Is Most Useful
Waiting increases exposure. An AI risk assessment is especially useful at key moments.
1
New HR Tools
Before or during implementation of new technology
2
Hiring Acceleration
When recruiting volume increases significantly
3
System Changes
When performance or evaluation systems are modified
4
Restructures
Before layoffs or organizational changes are planned
5
Proactive Clarity
When leadership wants clarity before regulators do
The Outcome
A good assessment turns AI from an unknown into a managed input.
Visibility
Clear understanding of where AI influences decisions and how
Control
Established processes for oversight and meaningful human review
Defensible Decisions
Documentation and practices that support accountability
Confidence
Leadership readiness for regulatory scrutiny and stakeholder questions
Let's Talk
If AI influences your HR decisions, an assessment is a logical starting point.
The first conversation focuses on practical next steps:
Where AI shows up today
Current tools and systems affecting people decisions
What decisions it affects
Impact on hiring, performance, and other HR outcomes
Where oversight exists
Current review processes and accountability structures
What needs attention now
Priority areas for mitigation and control