Assessment - AMP HR

How AI-Ready Is Your HR Team?

HR isn’t just a support function anymore — it’s a strategic driver of organizational agility, innovation, and culture. But as AI transforms the workplace, where does your HR team stand?

This quick, 2-minute assessment will assess your maturity across five essential pillars of AI readiness:

Governance & Ethics
Strategy & Vision
Skills & Adoption
Data & Integration
Tools & Infrastructure

What to expect:

You’ll rate your current state in each area and at the end, you’ll receive your custom maturity profile:

Category	What It Means
🧊 Explorer	Just starting — AI feels new or distant. Let’s build the foundation.
🌱 Experimenter	You’re exploring with intent, but need structure and alignment.
🚧 Builder	You’ve got traction. Now it’s time to formalize and scale.
🚀 Advancer	You’re leading with purpose. Focus on expanding reach and capability.
🔥 AI Leader	You’re a model of maturity—strategic, ethical, and scalable.

1 / 9

Category: Governance and Ethics

Who owns AI oversight in HR?

NO ONE:
There’s no clear ownership or awareness around AI governance in HR.
AI decisions are ad hoc and risky, with no accountability for ethical or legal implications.

IT OR LEGAL ONLY:
AI oversight is delegated outside of HR, usually to IT or compliance teams.
This may cover basic risks, but misses the people impact and HR-specific needs.

SHARED BUT UNDEFINED:
Oversight is loosely shared across departments, but roles and processes aren't clearly defined.
Important questions fall through the cracks — slowing progress and increasing risk.

HR INVOLVED:
HR is actively involved in AI oversight, with input from legal and tech teams.
A growing structure is forming, but consistency and documentation may still be lacking.

DEFINED HR-LED GOVERNANCE:
A clear, documented AI governance model is in place — HR leads responsibly with cross-functional support.
You’re leading with intention, mitigating risk, and modeling trustworthy AI adoption.

2 / 9

Category: Governance and Ethics

How do you address ethical risks like bias, privacy, and transparency?

NOT AT ALL:
No one is currently considering ethical or legal risks around AI in HR.
This leaves the organization exposed to unintended bias, reputational damage, or legal consequences.

TALKED ABOUT:
The topic has come up, but no specific steps have been taken.
Awareness is growing, but without action, risk remains unmanaged.

IN DEVELOPMENT:
We’re exploring or drafting an ethical AI policy with HR involvement.
There’s momentum, but clarity and accountability still need to mature.

SOME POLICY EXISTS:
Guidelines exist but aren’t consistently applied across tools or teams.
You’re ahead of most, but gaps could lead to inconsistent outcomes.

FORMAL, ONGOING OVERSIGHT:
We have a formal AI ethics framework, with regular reviews and clear ownership.
Your team is leading responsibly and modeling AI governance best practices.

3 / 9

Category: Governance and Ethics

Are internal AI audits conducted for fairness and compliance?

NEVER:
No reviews or safeguards exist for fairness, accuracy, or bias in AI-related tools.
This creates significant organizational risk, especially with sensitive HR data.

SOMETIMES, IF ISSUES ARISE:
We occasionally review tools reactively, but there’s no standard process.
This puts your team in firefighting mode rather than proactive control.

WE'VE DONE ONE OR TWO:
We’ve completed limited reviews, often with external input or one-time initiatives.
It’s a good start — but not yet scalable or reliable.

REVIEWED AS NEEDED:
We review tools based on risk level or quarterly business reviews.
There’s a pattern emerging — but more rigor could increase confidence.

STANDARDIZED AUDIT PROCESS:
Regular, documented AI audits are part of our HR risk and compliance strategy.
This sets a high bar for accountability and trust in AI decisions.

4 / 9

Category: Strategy & Mindset

How does leadership view AI?

DISMISSIVE:
AI is seen as hype or irrelevant to HR’s mission.
This mindset risks falling behind as the talent landscape shifts.

MILDLY CURIOUS:
Leadership is aware of AI, but unsure what role HR should play.
Interest is there — but it hasn’t yet translated into vision or action.

OPEN TO EXPLORING:
AI is discussed in planning sessions, but with limited commitment.
You’re in the early stages of making it part of strategic conversations.

STRATEGIC PRIORITY:
AI is actively considered as a tool to improve HR outcomes.
Leadership understands the opportunity and is investing in discovery.

TRANSFORMATIVE LEVER:
AI is viewed as a core part of future HR strategy and competitive advantage.
You’re aligning people strategy with innovation at the leadership level.

5 / 9

Category: Strategy & Mindset

How clearly is success defined for AI in HR?

NO DEFINITION:
There’s no defined goal or metric for AI efforts in HR.
This makes it hard to measure progress or justify investment.

EFFICIENCY ONLY:
Success is framed purely in terms of time saved or automation.
This underplays the broader impact AI can have on strategy and trust.

EXPERIENCE & TIME:
We look at efficiency and some improvement in HR user experience.
A good starting point — now expand into strategic value and culture impact.

STRATEGIC GOALS INCLUDED:
Success includes talent outcomes, process fairness, and adoption.
You’re tying results to business and people outcomes — keep going.

STRATEGIC + ETHICAL SUCCESS:
We define success through strategic impact, employee trust, and ethical guardrails.
You’re setting the bar for responsible, people-first innovation.

6 / 9

Category: Capabilities & Adoption

How confident is your HR team in using AI tools?

NO EXPOSURE:
The team has not used any HR tools with AI capabilities.
This limits your ability to experiment or assess potential use cases.

BASIC AWARENESS:
Some team members are aware of AI in tools but haven’t used it.
There’s curiosity, but little hands-on experience or understanding.

LIMITED USAGE:
We’ve used AI-powered tools in narrow ways (e.g., resume filters).
You’re experimenting — now deepen understanding and governance.

COMPETENT USE:
Our team understands how to use and evaluate AI features responsibly.
You’re developing capability and managing the human-AI handoff well.

FLUENT & CRITICAL:
We use AI tools strategically and evaluate their limitations and risks.
Your team knows how to use AI — and when not to — with confidence.

7 / 9

Category: Capabilities & Adoption

How does your team learn about AI in HR?

NO EXPOSURE:
We haven’t explored AI in HR at all.
This limits your ability to prepare for future disruption and puts your team at a knowledge disadvantage.

BASIC AWARENESS:
Some team members have heard about AI trends or features, but learning is ad hoc.
There’s curiosity, but no structured effort to understand or evaluate the tech.

LIMITED USAGE:
We’ve done some self-guided exploration (e.g., articles, webinars, tool demos).
You’re taking first steps — now it’s time to connect learning to real use cases.

COMPETENT USE:
Our team is engaging in courses, shared learning sessions, or guided workshops.
You’re building shared understanding and growing capability.

FLUENT & CRITICAL:
AI learning is embedded in our team’s growth plans and internal discussions.
Your team not only learns — they apply, question, and improve on what they know.

8 / 9

Category: Data & Infrastructure

How AI-compatible is your HR tech stack?

MANUAL OR LEGACY TOOLS:
Our systems are outdated or heavily reliant on manual processes.
This blocks any meaningful AI adoption or integration.

CLOUD-BASED, NO AI:
We’ve moved to the cloud, but current tools don’t offer AI features.
You’re modernizing — but not yet leveraging what’s possible.

BASIC AI FEATURES:
We use some AI features in existing HR tools (e.g., auto-scheduling, insights).
You’re gaining exposure — now it’s time to assess value and fit.

AI-READY PLATFORMS:
We’ve adopted platforms designed with AI in mind, even if features aren’t fully activated.
You’re positioned to scale your AI usage responsibly.

FULLY INTEGRATED & CUSTOMIZABLE:
Our HR tech stack supports AI with integrations, APIs, and governance layers.
You’ve built a future-ready system aligned with innovation and compliance.

9 / 9

Category: Data & Infrastructure

How accessible and clean is your HR data?

COMPLETELY SILOED:
Data is scattered across tools and spreadsheets with no clear structure.
This makes it nearly impossible to leverage AI or even basic insights.

PARTIALLY CENTRALIZED:
We’ve digitized some processes but lack clean, consistent datasets.
AI potential is limited without quality inputs.

MOSTLY CLEANED:
Key datasets are in place, though some areas still need work.
You’re almost ready to plug into smarter tools — just tighten alignment.

WELL STRUCTURED:
Data is centralized, standardized, and used for analytics.
You’ve got the foundation — now put it to work with predictive insights.

AI-READY:
Clean, trustworthy data is integrated across HR systems and ready for AI applications.
You’ve built the infrastructure for strategic, data-driven HR.

Very exciting! We're about to compile your assessment results...

Where can we share your report?

NameEmail