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SHRM-CPFrequently TestedTechnology Domain
AI in HR is new for the 2026 BASK, expect questions

Technology Management in HR

4

Analytics Levels

Descriptive diagnostic predictive prescriptive

3

System Types

HRIS HRMS HCM

1

New for 2026

AI content expanded across competencies

System Types

three acronyms, each a bigger circle
HRISHuman Resource Information System

Core record-keeping. Employee data, payroll, benefits administration, compliance reporting. The foundation every other system builds on.

HRMSHuman Resource Management System

Everything in HRIS plus talent management capabilities. Recruiting, onboarding, performance management, and learning management.

HCMHuman Capital Management

The full suite. HRMS plus workforce planning, analytics, succession planning, and strategic workforce management. Treats people as a strategic asset.

HR Analytics Levels

DescriptiveDiagnosticPredictivePrescriptive

Descriptive = What happened? (reports, dashboards)

Diagnostic = Why did it happen? (root cause analysis)

Predictive = What will happen? (forecasting models)

Prescriptive = What should we do? (recommended actions)

AI in HR

Expect questions about algorithmic bias in hiring tools and the need for human oversight of AI decisions

Where AI Helps

  • Resume screening at scale
  • Chatbots for candidate questions
  • Predictive turnover models
  • Skills gap analysis

Where AI Risks

  • Algorithmic bias from historical data
  • Lack of transparency in decisions
  • Privacy and data protection concerns
  • Over-reliance without human review

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Exam Traps

2026 BASK Expanded AI Content

The 2026 Body of Applied Skills and Knowledge significantly expanded coverage of AI and technology across multiple competencies. Expect more questions about AI in recruiting, bias mitigation, and the role of human oversight.

Analytics Levels Follow a Sequence

Descriptive (what happened) comes first. Then diagnostic (why). Then predictive (what will happen). Then prescriptive (what should we do). The exam tests whether you can place a scenario at the correct level.

Algorithmic Bias in Hiring

AI tools trained on biased historical data will reproduce that bias. If past hiring favored one group, the AI will continue that pattern. Human oversight is required to catch and correct algorithmic discrimination.

AI Needs Oversight

AI in HR is a tool, not a decision-maker. Human review is required to prevent bias from scaling unchecked.

Analytics Sequence

What happened, then why, then what will, then what should. Each level builds on the previous one.

1
Descriptive (Current Speed)

The speedometer shows 65 mph. That is descriptive analytics. It tells you what is happening right now or what happened in the past. Turnover was 18% last year. That is a descriptive metric.

2
Diagnostic (Why Slowing Down)

You notice the car is slowing. You check and find a tire is low. That is diagnostic analytics. You investigate why turnover spiked in Q3 and find it correlated with a policy change.

3
Predictive (When You Will Arrive)

The GPS estimates arrival at 3 PM based on current speed and traffic patterns. That is predictive analytics. A model forecasts which employees are at highest risk of leaving within six months.

4
Prescriptive (Best Route)

The GPS says take the highway to save 20 minutes. That is prescriptive analytics. The model recommends specific retention interventions for high-risk employees and estimates their impact.

What happened, then why, then what will, then what should.
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Reviewed by Sarah L., PrepSolution Content Editor, HR
Sources verified against SHRM 2026 standards
Updated May 2026