Specialised Track · HR & People Function

Reinvent the people function with AI.

A three-day, hands-on programme for CHROs, HR leaders, talent and L&D teams. Redesign hiring, engagement, retention, and workforce planning with applied AI and agentic automation. Every delegate leaves with a working HR agent in Codespaces and a transformation roadmap for their function.

3 days 17 modules 60% hands-on Codespaces lab included STOA certified
Daniel Sto
Why this programme exists
"Hiring, engagement, retention, planning. Every HR motion is an agent waiting to be built."
Daniel Sto · Director of Faculty, STOA Institute
Duration
3 days
Format
Live online or on site
Next open date
Private cohorts
Fee
$2,997 per delegate
includes Codespaces lab & all materials
For teams
Private cohort from 8 delegates
Schedule a TNA call
Programme overview

Built around the four pillars of the people function.

This three-day programme is built for CHROs, HR leaders and the talent, learning and people analytics teams who have to decide where AI belongs in the people function. HR holds sensitive personal data and a high volume of repetitive document work: job descriptions, policies, candidate pipelines, engagement surveys, performance reviews, attrition data and learning plans. Generative AI drafts, classifies and summarises that work well, and an AI agent goes one step further: given a goal, it reads the policy, applies the rules, records a decision and hands the exceptions to a person. The programme follows the four pillars of the people function, Hire, Engage, Grow and Plan, with responsible use built into every module.

Day one builds operator-level fluency: how large language models work, an HR digital maturity and AI readiness audit, prompt engineering with the C.L.E.A.R. framework on participants' own HR documents, AI-assisted sourcing and rubric-first screening, custom assistants for recruiting and HR administration, and an introduction to AI agents. Day two applies AI across compliance, engagement and retention: the Blueberry Test for bias, benefits and pay-equity guardrails, NLP and sentiment analysis on engagement surveys and employee relations tickets, predictive retention and attrition analytics, and performance calibration with HR analytics. Day three is strategic: workforce planning and personalised learning, then the agent build, where every participant builds a leave request triage agent against a written policy in a pre-configured Codespaces environment and instruments it to read its traces, before ethics, governance, Shadow AI and the capstone roadmap close the programme.

Participants work on realistic recruiting, engagement, attrition, performance and L&D scenarios throughout. They leave with a prioritised AI use-case roadmap for their function, an HR prompt library, working custom assistants, a working HR agent with its evidence pack of traces and metrics, a Shadow-AI governance policy draft, and a capstone HR AI transformation roadmap with a ninety-day plan they can hand to their executive committee. The programme finishes on where the field is heading: agentic AI, where an HR agent is given a goal and plans and executes the work under human supervision, with context engineering, agentic retrieval-augmented generation and the Model Context Protocol.

Who should attend

This programme is designed for the leaders and specialists of the HR and people function across all industries:

  • CHROs and HR Directors
  • HR Managers and HR Business Partners
  • Talent acquisition and recruitment leads
  • Learning and development (L&D) and people analytics teams
  • Digital transformation officers in HR
  • Workforce strategists and OD specialists
  • Employee relations, HR compliance and DEI leads
  • Reward, compensation and benefits specialists
  • People operations and HR shared services managers

Learning outcomes

By the end of this programme, participants will be able to:

  • Explain how generative AI works and where its output needs verification in people decisions
  • Audit HR digital and AI readiness maturity
  • Apply the C.L.E.A.R. framework and K-shot prompting to HR documents and communications
  • Reinvent recruiting, engagement, retention and L&D workflows with AI
  • Build custom assistants and HR-specific agents
  • Run the Blueberry Test for bias on job descriptions, prompts and outputs
  • Apply NLP and sentiment analysis on people data
  • Build attrition and performance dashboards with AI
  • Produce an AI-assisted workforce plan and personalised learning paths
  • Evaluate an HR agent's traces, metrics, costs and failure modes
  • Prevent and govern Shadow AI in HR
  • Leave with an HR AI transformation roadmap and a ninety-day plan
Hire

Talent Acquisition

AI-assisted sourcing, screening, JD generation, structured interviews, candidate experience agents.

Engage

Voice of Employee

NLP on surveys, sentiment analysis, predictive retention, exit-interview automation, ER triage.

Grow

L&D & Performance

Personalised learning paths, skills inference, performance summaries, career-growth recommendations.

Plan

Workforce Strategy

Strategic workforce planning, scenario modelling, ROI prioritisation, AI roadmap and governance.

Programme outline

Seventeen modules. Three days. One working HR agent.

A progressive structure from operator-level fluency, through compliance, engagement and retention, to strategic workforce planning, governance and a capstone HR AI roadmap.

Day 1: The Intelligent HR Operator

01
Day 1 · Module

AI in HR Today

  • What is generative AI?
  • Large language models and chat assistants (ChatGPT, Claude, Microsoft Copilot, Gemini)
  • Tokens, context windows and memory
  • Hallucination and non-determinism
  • Verification of AI output in people decisions
  • The HR AI landscape and vendor claims
  • AI across the employee lifecycle (attract, hire, onboard, engage, develop, reward, retain, exit)
Live walkthrough the calculator test
02
Day 1 · Module

HR Digital Maturity and AI Readiness

  • HR digital maturity models
  • The AI readiness audit (data, systems, skills, governance, culture)
  • HRIS, ATS and LMS data as AI inputs
  • Use-case mapping across the employee lifecycle
  • Data, pain and impact scoring
  • Quick wins and transformation projects
  • The future of talent acquisition and autonomous HR administration
Diagnostic tool the HR AI Readiness Assessment Toolkit applied to participants' own HR workflows
03
Day 1 · Module

Prompt Engineering for HR Work

  • The C.L.E.A.R. prompt engineering framework
  • K-shot prompting (zero-shot, one-shot, few-shot, multi-shot)
  • Chain-of-thought prompts
  • Persona, tone and house-style instructions
  • Structured outputs (tables, summaries, decision memos)
  • HR documents (job descriptions, policies, employee communications, interview guides)
  • Sensitive data and what never goes into a prompt
  • The HR prompt library and reusable agent skills
Hands-on exercise rebuilding three HR documents with C.L.E.A.R.
04
Day 1 · Module

AI in Talent Acquisition

  • Boolean and X-ray sourcing with AI
  • Deep research and candidate longlists
  • Job description generation and inclusive language
  • Rubric-first screening (criteria, weights, evidence)
  • Ranking, shortlisting and outreach drafting
  • Structured interviews and question banks
  • Interview scheduling automation
  • Candidate experience and correspondence at scale
Hands-on exercise an AI candidate longlist and rubric-scored shortlist
05
Day 1 · Module

Custom Assistants for HR

  • Custom assistants (custom GPTs, Claude Projects, Copilot agents, Gemini Gems)
  • System-instruction design for HR assistants
  • Knowledge upload and policy-aware responses
  • Guardrails, refusals and escalation rules
  • The recruiter copilot and the HR admin assistant
  • The onboarding assistant and the employee handbook
  • Pre-engineered prompt templates from the STOA HR library
  • Testing against known questions (answer, refuse, escalate)
Individual and pair work building an onboarding assistant with an escalation policy and testing it against supplied questions
06
Day 1 · Module

AI Agents and Autonomous HR Administration

  • What is an AI agent?
  • Agents, assistants and workflow automation
  • The agent loop (goal, observe, reason, act, evaluate, repeat)
  • Levels of autonomy and human-in-the-loop
  • HR administration processes for agents (leave and absence, letters and contracts, onboarding tasks, policy questions, HRIS updates, case notes)
  • The build spectrum (no-code, low-code, full-code)
  • Visual agent builders and coding agents (n8n, LangFlow, Claude Code)
  • AI features inside HR platforms (Workday, SAP SuccessFactors, Oracle HCM)
  • The agent design brief (goal, inputs, tools, outputs, guardrails, success criteria)
Live demonstration an agent completing a multi-step HR task end to end

Day 2: AI in Compliance, Employee Engagement and Retention

07
Day 2 · Module

AI in HR Compliance and the Blueberry Test

  • AI in HR compliance (policy checks, contract and letter review, documentation checks)
  • Bias in AI-assisted people decisions (sourcing, screening, performance, reward)
  • The Blueberry Test for bias in prompts and outputs
  • Protected characteristics and proxy variables
  • Human review of AI-assisted decisions
  • Auditability, explainability and regulatory considerations
  • Record keeping and the audit trail
Hands-on exercise running the Blueberry Test on participants' own job descriptions and interview prompts
08
Day 2 · Module

Intelligent Benefits, Total Rewards and Pay Equity

  • Benefits and total-rewards personalisation
  • Benefits enquiries and policy question assistants
  • Compensation benchmarking with AI-assisted research
  • Pay-equity analysis and workforce composition views
  • Policy-aligned AI guardrails for reward data
  • Sensitive data, anonymisation and synthetic datasets
Controlled group discussion guardrails for AI in reward and pay-equity decisions
09
Day 2 · Module

Engagement, Retention and Voice of the Employee

  • Voice of the employee sources (engagement surveys, pulse surveys, ER tickets, exit interviews, employer reviews)
  • Survey design and generation with AI
  • NLP and sentiment analysis on survey comments and ER tickets
  • Theme extraction at scale
  • Exit-interview automation
  • ER case triage and summaries
  • Manager action plans from survey themes
Hands-on exercise a live engagement survey built with AI, then theme and sentiment analysis of the responses
10
Day 2 · Module

Predictive Retention and Attrition Analytics

  • Attrition patterns, costs and flight-risk indicators
  • Predictive retention models and their limits
  • Attrition risk scoring and intervention design
  • Manager nudges and retention conversations
  • Fairness and explainability in risk scores
  • HR analytics in the AI era (dashboards, decision support)
Hands-on exercise building an attrition dashboard from a 220-employee dataset
11
Day 2 · Module

Performance Management and HR Analytics

  • Performance cycles, calibration and rating inflation
  • AI-assisted performance summaries and feedback drafting
  • Calibration gaps between departments and managers
  • Talent concentration and blocked-talent signals
  • Data quality faults in HR exports (duplicates, incomplete records)
  • Structured requests for dashboards and charts
  • Executive narratives and management summaries from HR data
Individual and pair work a four-chart performance dashboard from an annual review export with planted data faults

Day 3: Strategic Planning and the Future of AI in HR

12
Day 3 · Module

Strategic Workforce Planning

  • Strategic workforce planning (hire, develop, transition)
  • Skills-based scenario modelling
  • Skills taxonomies
  • Demand and supply forecasting for roles
  • Role redesign and task reallocation
  • Workforce composition and cost scenarios
  • The 18-month workforce plan
Hands-on exercise an 18-month workforce plan built with AI on participants' own organisation
13
Day 3 · Module

L&D and Talent Development

  • AI-assisted training needs analysis from performance data
  • Personalised learning paths on the 70:20:10 model
  • Skills inference and career-growth recommendations
  • Content and assessment generation with quality control
  • AI tutors and learning assistants
  • Learning analytics and the Kirkpatrick model
Hands-on exercise personalised learning paths for three employee personas
14
Day 3 · Module

Building the HR Agent

  • The lab environment (GitHub Codespaces, browser-based, pre-configured)
  • The leave request triage case (policy, requests, decisions)
  • Decision rules (APPROVE, DECLINE, NEEDS_INFO) and policy citation
  • Document-grounded answers and abstention
  • The two build tracks (visual canvas, coding agent)
  • Planted edge cases (insufficient notice, missing evidence, out-of-policy requests)
  • Acceptance criteria and automated checking of results
  • The decline email to the employee
Lab building the leave request triage agent end to end
15
Day 3 · Module

Evaluating and Monitoring the HR Agent

  • Observability for AI agents (LangSmith)
  • Traces and their contents (context, prompt, model response, tokens, latency, cost)
  • The metrics baseline
  • Failure-mode probes and abstention on missing information
  • Optimisation levers (instructions, context size, model choice)
  • The Agent Health Check measures:
    • Groundedness and policy citation
    • Escalation and abstention behaviour
    • Hallucination and omission rates
    • Sensitive-data leakage
    • Cost, latency and reliability
  • Human approval points for people decisions
Lab instrumenting the triage agent, recording the baseline and running a failure-mode probe
16
Day 3 · Module

Ethics, Governance, Shadow AI and Emerging Methods

  • Ethics in decisions about people (fairness, transparency, accountability, human review)
  • Data sovereignty, residency and the data controls on consumer AI tools
  • What is Shadow AI?
  • Preventing and managing Shadow AI in HR (approved tools, acceptable use, monitoring)
  • The minimum viable AI policy for the HR function
  • The regulatory and standards direction (EU AI Act, ISO/IEC 42001, NIST AI Risk Management Framework, data protection law)
  • Emerging methods:
    • Context engineering
    • Agentic retrieval-augmented generation (RAG)
    • Model Context Protocol (MCP)
    • Computer use and browser agents
    • Multi-agent patterns in HR operations
Controlled group discussion the Shadow-AI governance policy draft for participants' organisations
17
Day 3 · Module

Capstone, Your HR AI Transformation Roadmap

  • The HR AI use-case portfolio across the four pillars (Hire, Engage, Grow, Plan)
  • ROI and the AI use-case prioritisation matrix (value, feasibility, risk, data readiness)
  • The pilot portfolio and the pilot definition (scope, owner, success criteria, review points)
  • The capstone agent brief for participants' own HR use case
  • Team readiness and capability building
  • Showcase and peer review
  • The ninety-day plan (next steps, priority use case, timeline, owners)
Personal action planning each participant's HR AI transformation roadmap and ninety-day plan
Day 3 · Course closing

Course closing

  • Course debrief and key takeaways
  • Final Q&A
  • Official closing ceremony and award of certificates
  • Group photo
Three-day path

Diagnose. Apply. Build.

Each day moves further from theory and closer to a working agent in your own environment. Everyone, regardless of technical background, can follow along.

Day 1
Operate
Foundations & custom GPTs

AI foundations for HR, readiness audit, prompt engineering lab, recruitment redesign, and a hands-on custom GPT workshop.

Day 2
Engage
Compliance, sentiment & retention

Bias and the Blueberry Test, NLP on engagement surveys, predictive retention, exit-interview automation, and HR analytics.

Day 3
Lead
Strategy, governance & capstone

Workforce planning, Shadow-AI governance, ROI prioritisation, future-of-work trends, and your HR AI transformation roadmap.

Inside the programme

A live Codespaces lab. No setup. No friction.

Every delegate gets access to a pre-configured GitHub Codespaces environment with HR datasets, working notebooks, and reference agents already wired up. You see agentic AI applied to real people-data, then build your own.

  • Pre-loaded recruiting, engagement, attrition and L&D datasets
  • Working starter agents you fork and modify
  • Custom GPT system-instruction library for HR
  • Shadow-AI & governance policy templates
  • Lab access remains active for 30 days post-programme
Download brochure
Built for HR

Designed for the people who lead the people function.

A practitioner-led programme, calibrated for the pace and language of HR. Not a generic AI course wrapped in HR examples.

For HR leadership

CHROs, HR Directors, and digital transformation officers who need a clear AI roadmap, governance posture, and ROI thesis for the next 12 months.

For talent & L&D

Recruiters, talent partners, learning and people-analytics teams who want to redesign sourcing, hiring, engagement and learning around AI.

For ER & compliance

Employee relations, HR compliance and DEI leaders who need to evaluate bias, governance, Shadow AI, and ethics in people workflows.

Our training methodology

Three frameworks behind every programme.

Whatever programme you choose, it follows three proven instructional frameworks, from design to delivery to evaluation.

Delivery

TEA™ Delivery Framework

  • T Theory, core concepts & frameworks
  • E Examples, live demos & case studies
  • A Application, hands-on exercises & practice

Our signature approach structures every module into three phases for maximum retention and practical application.

Design

ADDIE Instructional Design

  • A Analyse, assess learner needs
  • D Design, structure the learning path
  • D Develop, build materials & activities
  • I Implement, deliver the programme
  • E Evaluate, measure outcomes & refine

The industry-standard model for course design and learning alignment.

Evaluation

Kirkpatrick Model

  • L1 Reaction, participant satisfaction
  • L2 Learning, knowledge & skills gained
  • L3 Behaviour, on-the-job application
  • L4 Results, business impact & ROI

The globally recognised four-level framework for measuring training effectiveness, from initial reaction to long-lasting post-training effects.

Upcoming sessions

Choose your date.

Open-enrolment dates below. Need a private session for your HR team? Schedule a TNA call, custom proposal within 48 hours, delivery in as little as three weeks.

Date
Format
Duration
Price
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What every participant gets

You keep everything.

No vendor lock-in. No paywalled materials. Every delegate leaves with the working files, the templates, the lab access, and the post-programme support to actually use them.

Working HR agent

A live, deployable custom GPT or agent built on your own recruiting, engagement, retention or L&D use case.

Codespaces lab access

Pre-configured GitHub Codespaces environment with HR datasets, starter agents, and notebooks.

Readiness toolkit & roadmap

HR AI Readiness Assessment plus a prioritised HR Transformation Roadmap mapping pilots, ROI and timelines.

HR prompt & policy library

Custom GPT system-instruction library, the Blueberry Test dataset, and a Shadow-AI governance policy template.

STOA certificate

Certificate of Completion plus a guided pathway to the Google AI certificate as an additional credential.

30-day support

Post-programme Q&A, lab access, and implementation guidance for your HR use case.

Delivery options

Choose how your HR team learns.

In-Person

Instructor-led on-site

Delivered at your offices or venue. Maximum engagement for HR teams of 8 – 20 participants. All exercises use your team's actual hiring, engagement, retention and L&D scenarios.

Live Online

Virtual instructor-led

Real-time delivery via Zoom, Teams, or Meet. Interactive breakout rooms, the same Codespaces lab, same depth as in-person. Ideal for distributed people organisations.

Hybrid

Blended approach

Combine in-person and virtual sessions. Flexible scheduling across time zones. Pre-work, capstone reviews and follow-up resources included.

Training catalogue

104 courses in nine families, overview level, methodology up front.

Download the catalogue
Ready to build

Stop talking about AI in HR. Start running it.

Join the next open session, or book a private programme for your HR team. Custom proposal within 48 hours. Delivery in as little as three weeks.