Critical HR work lives across files, emails and systems.
Monthly MIS, recruitment trackers, policies, LMS records and employee feedback require repeated consolidation before HR can act.
AI FOR HR
A hands-on, business-first AI programme that helps HR teams improve recruitment, employee service, workforce reporting, payroll review, learning effectiveness and people decisions through governed AI workflows.
PREVIOUS PROGRAM HIGHLIGHTS
Hands-on enterprise sessions built around facilitator demonstrations, governed HR workflows and collaborative use-case design.
WHY THIS PROGRAMME
The programme begins with workflow evidence, data boundaries and review ownership. Tool instruction follows the business problem.
Monthly MIS, recruitment trackers, policies, LMS records and employee feedback require repeated consolidation before HR can act.
Duplicates, stale regulations, inconsistent definitions and unsupported causal claims can enter management packs without deliberate checks.
Teams need role-based practice, reusable templates, agents, dashboards and a 30-day implementation owner for each selected use case.
Measured through role-relevant pre- and post-assessment.
Participants finish the core case output during the programme.
Selected teams begin using or piloting an approved HR workflow.
Validated against a baseline for suitable reporting and operations tasks.
Measurement note: These are illustrative targets for programme design. Replace them with agreed baselines and verified post-program results before publishing as client outcomes.
15 HR AI USE CASES
Each use case has a defined problem, input set, output, owner, implementation wave and human validation requirement. Eight are positioned as quick wins, five as Phase 1 priorities and two as strategic builds.
Consolidate HRMS, payroll, attendance, hiring, attrition and L&D inputs into an evidence-led leadership pack.
HRBP / HR Analytics 2–3 monthsFind duplicates, missing fields and inconsistent department, grade, location, manager and cost-centre values.
HR Operations 1–2 monthsCompare pay movements against attendance, leave, increments, incentives and deductions before sign-off.
Payroll / HR Ops 2–3 monthsReconcile rosters, attendance, overtime, leave and compensatory off to surface staffing and policy exceptions.
Workforce Operations 3–4 monthsDecompose budget variance across units, grades and locations with drivers, forecasts and management commentary.
C&B / HR Finance 4–6 monthsIdentify cohort concentrations while keeping patterns separate from confirmed causes and individual decisions.
HR Analytics / HRBP 3–4 monthsTurn hiring inputs into a structured JD, role scorecard, sourcing brief and bias-aware manager checklist.
Talent Acquisition 1–2 monthsCompare CV evidence against weighted role criteria and record information gaps without unsupported rejection.
Talent Acquisition 1–2 monthsGenerate structured questions, role-specific probes, evidence guides and consistent panel evaluation formats.
TA / Interview Panel 1–2 monthsTrack communications, documents, background checks, approvals and ageing risks between selection and joining.
TA / HR Operations 2–3 monthsImprove evidence quality, flag incomplete statements and prepare rating-distribution review packs.
Performance / HRBP 3–4 monthsCombine enrolment, completion, assessment and feedback data to identify cohorts and programmes needing action.
Learning & Development 2–3 monthsAnonymise and categorise survey and exit feedback with traceable themes, sample controls and action priorities.
Engagement / Analytics 2–3 monthsAnswer from approved documents with citations, version control, exception routing and an unresolved-query log.
HR Ops / EX / IT 4–6 monthsAdapt approved HR messages across email, WhatsApp, intranet, posters and professional social channels.
Engagement / Corp Comm 1–2 monthsLEARNING ARCHITECTURE
The programme mix is selected after pre-screening. Every level produces a usable output.
RICF / RICTF prompts that remove ambiguity, set evidence rules and define the output.
Emails, meeting minutes, HR documents, presentations and management narratives.
Power BI workforce and manpower-cost view with relationships, DAX and filters.
Power Automate triggers, approvals, reminders, document handling and escalation flows.
Seven ready-to-configure HR agents grounded in approved Microsoft 365 sources.
A five-phase folder workflow that creates a controlled CHRO review pack.
PROGRAMME OUTLINE
The core eight-hour format can expand into role-based labs, implementation sprints or a multi-stage HR AI academy.
OutputResponsible AI Checklist for HR
OutputHR Prompt Library: Foundation Set
OutputMeeting Minutes and Action-Tracking Template
OutputAI-Assisted Recruitment Toolkit
OutputHR Analytics and Payroll Validation Prompt Pack
OutputLMS Effectiveness Review Template
OutputEmployee Engagement Communication Pack
Output30-Day HR AI Action Plan
CASE-BASED LEARNING
Cases use fictional or sanitised data. They test whether participants can validate, explain and control an AI-assisted workflow.
Participants improve the prompt layer by layer, reconcile row-level arithmetic, inspect mixed formats and use remarks as evidence before producing the monthly summary.
Creates: audited executive summary + exception list + correction requestsParticipants import data, create a simple model, build core DAX measures and develop KPI cards, workforce-mix charts and interactive filters.
Creates: working PBIX dashboard + validated KPI logicThe workflow reconciles HR files, creates workforce and cost insights, reviews talent and learning, analyses employee voice and prepares a CHRO action pack.
Creates: CHRO review pack + action tracker + auditable workflow logTeams work with agents for reporting, data quality, policy Q&A, recruitment, L&D, feedback and cross-file analysis, then prototype tools such as an onboarding tracker or interview-kit builder.
Creates: approved agent instructions + starter prompts + implementation controlsPARTICIPANT DELIVERABLES
Reusable prompts for reporting, recruitment, data validation, analytics and communication.
JD structure, weighted criteria, CV comparison, interview guide and evaluation scorecard.
Validation rules, exception reporting, manpower-cost, payroll and attrition review prompts.
Ready-to-configure instructions, knowledge-source placeholders and starter prompts.
Meeting actions, LMS effectiveness, engagement communication and management reporting.
Prioritised workflow, owner, data requirement, controls, implementation step and measure.
BEFORE, DURING AND AFTER
The curriculum is modular. Participant screening decides the depth, case mix and tools used for each HR role.
Role, experience, AI comfort, tool access and priority workflow survey.
Current use, data readiness, governance controls and adoption barriers.
Choose use cases, datasets, licences, level tracks and success measures.
Hands-on cases, review gates, templates, agents and role-based outputs.
30-day pilots, adoption evidence, time baseline and implementation roadmap.
AI COST ECONOMICS
The programme teaches HR teams to separate typing tasks from thinking tasks, choose the right tool boundary and quantify whether an automation deserves implementation.
Business case: annualised capacity value + avoided rework and risk − tool and implementation cost.
RESPONSIBLE AI FOR HR
Use approved enterprise locations for employee-level data.
Show source, period, row count and calculation behind material findings.
Keep unmatched records visible; never silently delete or correct source data.
Protect anonymity and avoid reporting findings from groups that are too small.
Recruitment, appraisal, disciplinary and separation decisions stay with authorised people.
AI FOR HR FAQs
Explore the programme by topic, from practical HR applications and responsible AI to customization, delivery and measurable outcomes.
The AI for HR program is designed for HR leaders, HR business partners, Talent Acquisition teams, HR Operations, Payroll and Compensation teams, Learning & Development professionals, Employee Engagement teams and HR Analytics professionals who want to apply AI to practical HR workflows.
BUILD YOUR HR AI PROGRAMME
We will assess participant maturity, data readiness, tool access and business priorities, then configure the programme, case materials, deliverables and measurement plan.
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