
Why “let’s use AI” is the wrong start and “let’s break down the task” is the right one
Three types of HR tasks: one-off, repeating and process
Jobs-to-be-Done decomposition of an HR task into subtasks
Four AI-fit criteria: repeatability, data volume, input and output format, cost of error
Tools: AI-Fit Scorer and Task Decomposition Worksheet
Six AI capabilities: prompt, project, connector or MCP, computer use, scheduled action, vibe coding
Task-by-capability matrix: which capability fits which HR subtask
Recruiting from sourcing to offer mapped to the six capabilities
Common mistakes: a prompt where a project is needed, an agent where a prompt is enough
Tools: Capability Matching Matrix and Six Capabilities Reference
Three levels of AI autonomy: assistive, augmentative, autonomous
Four criteria for a human-in-the-loop checkpoint: risk, reversibility, audit, employee trust
The Human Agency Scale from Stanford research as a frame for autonomy decisions
Performance review: where AI prepares the summary and where HR makes the decision
Tools: AI HR Manager RACI Builder and Human Agency Decision Tree
Why uploading files into a chat breaks down for repeating HR tasks
Three types of HR data: static documents, periodic exports, live systems
Three connection patterns: project upload, connector or plugin, MCP server
Engagement survey analysis, privacy and data minimisation: what not to give AI
Tools: Data Flow Canvas, Connection Pattern Matrix and Data Connection Patterns
Four trigger types: manual, scheduled, event-driven, conversational
Event-driven HR: a new hire in the ATS starts the onboarding flow
Scheduled HR: a weekly pulse survey and a regular retention report
Scheduled or event-driven: choosing by frequency, reaction speed and workload
Tools: Trigger Chain Designer, Trigger Map Canvas and Trigger Selection Guide
Five AI risks in HR: bias, prompt injection, data leakage, hallucination, audit gap
GDPR, the EU AI Act and CCPA at awareness level: why many HR uses count as high-risk
Guardrail patterns: human approval gates, audit log, data masking, input and output checks
Compensation and background checks: where AI can help and where it should not decide
Tools: Compliance Readiness Gate, AI Risk Assessment Worksheet and Guardrails Checklist
One-page AI architecture in seven sections: task, capabilities, roles, data, triggers, guardrails, metrics
End-to-end recruiting case with all layers on one diagram
Fallback patterns for the moments when AI fails
Ten-criteria validation and a brief that IT, legal and the CEO can read
Tools: One-Page Architecture Builder, One-Page Architecture Template and Architecture ValidationChecklist
Five levels of AI maturity in HR: shadow, experimenting, structured, orchestrated, transformed
90-day roadmap: pilot in month one, measure in month two, scale in month three
Pilot metrics and a baseline that show results to leadership
Your own role in 12 months: from running processes to designing solutions
Tools: Maturity & Role Compass, 90-Day Roadmap Template and HR Maturity Self-Assessment
This course contains the use of artificial intelligence
88% of HR tech leaders say AI has not brought them significant ROI (CIO, March 2026). The tools are not theproblem. The problem is that every new HR task still starts from an empty chat window.
You already use AI. You paste a job description into a chat, copy the answer back and move on. Next week thesame task starts from zero again. You are not sure when a single prompt is enough, when you need a projectwith stable instructions, when AI should connect to your HR data and when it should start on a schedule.Meanwhile SHRM’s State of AI in HR 2026 shows that 62% of HR functions use AI somewhere in theorganization, but only 39% use it inside HR. Every month without a system is another month of one-off chatsthat nobody can repeat, measure or defend in front of leadership.
After this course you look at any HR task the way an architect looks at a building. You break it down, choosethe right AI capability for each part, decide where AI acts alone and where a person approves, connect thedata it needs, set the moment it starts, and build in the protection. The result is a one-page architecture youcan show to IT, legal and your CEO, and a 90-day roadmap with pilot metrics. The method does not depend onany product, so it keeps working when the tools change.
The course is built and taught by Mike Pritula:
#1 HR instructor on Udemy, with 2,000,000+ students on Udemy
20 years in HR at Wargaming, Preply, iDeals and Starlightmedia
PHRi, SHRM-CP and HCI sHRBP certified, HRCI representative in Eastern Europe
Founder of Pritula Academy, where 170,000+ students have trained
The course follows an eight-layer model called TARGET CRAFT, one layer per lesson, and each layer answersone plain question. First you learn to see the task: what exactly the work is and which of six AI capabilities fitseach piece of it. Then you design the parts around it: how much autonomy AI gets, which data it works with,and what starts it without anyone opening a chat. Next you add the guardrails that keep the solution fair,auditable and safe from prompt injection. Finally you assemble everything on one page and turn it into a 90-day rollout plan and a new role for yourself. Every lesson ends with one short assignment on your owncompany, so by the last lesson you have a real architecture, not notes.
What’s included:
Lifetime access to all materials
Active instructor support in Q&A
Udemy Certificate of Completion
A practical assignment on your own company in every lesson
22 ready-to-use tools: interactive builders, spreadsheet canvases and matrices, a document template andPDF checklists and guides
A section with additional courses, tools and resources
According to SHRM’s 2026 CHRO Priorities, 92% of CHROs expect AI in the workforce to grow in 2026. TheHR teams that design their AI now will decide how it is used. The rest will inherit tools and rules someone elsechose for them.
Enroll now and start your first lesson today.