🧠 The Revenge of
HR Professionals.
For too long, HR has queued up for IT's roadmap to solve problems we already know how to frame. AI changes that. No more six-month waits. No "we'll need a developer for that." You build it. You own it. You deploy it. Build on your real HR data, alongside peers, with Deepika teaching every session live.
Deepika Manchanda
teaches this.
Not a lecturer. A builder who works at the intersection of HR and AI.
Deepika does not teach you about AI in HR — she builds with you in the session. Share your screen, show the real problem, and she will show you exactly where the model is failing you and how to fix it before the call ends.
Global HR and AI Transformation Leader with 18+ years advising C-suite executives on people, talent, and organisational strategy across 10+ countries. Former Managing Director (Partner) at Accenture, where she built and scaled the regional Talent & Organisation AI practice, led a multi-million-dollar P&L, and delivered enterprise-scale transformation programmes embedding AI-driven HR capabilities across financial services, government, retail, and energy sectors. Recognised speaker at CHRO Roundtables, Oracle CloudWorld, AI MENA Network, and Aurora50.
Every session ends with a deployable output. Not a plan. Not notes. The actual thing, in your actual HR tool, ready to use the next morning.
Four things you walk away with.
None of them are certificates.
You build something in your actual HR role, on your actual data, that runs without you manually triggering it every time. The gap between knowing about AI and knowing how to use it is one most HR professionals have not crossed. Four weeks closes it.
Every automation currently requires a sprint, a developer, and a roadmap. After this lab you build the small stuff yourself — a JD template, a screening workflow, a feedback synthesiser. Not everything. Enough to stop waiting.
When IT says "that takes three months," you will know enough to ask: what is the architecture constraint? Could we prototype first? What is the governance requirement? You will not replace the IT conversation. You will change it.
Every participant leaves with a verified AIQ credential showing their tier level and score, a Proof Pack documenting the AI tool they built and its measured impact, and before and after AIQ scores that show exactly which dimensions moved.
Four weeks. Your HR problem.
One new output every week.
Every week builds on the last. By Week 4 you have a deployed AI workflow running in your actual HR process.
Group (45 min): What AI actually is and is not. Trends across the HR lifecycle: where AI is already changing recruiting, onboarding, performance, L&D, and ER. Three real HR AI failures and what went wrong.
Pod lab (45 min): Every participant maps their own AI use in the last month. Then names one specific HR problem they want to solve. Pod agrees shared territory for the next 3 weeks. One-paragraph problem brief written by end of session.
Group (45 min): Live demonstrations across the full HR lifecycle: recruiting, onboarding, performance, engagement, L&D, ER. The five elements every HR brief needs: role context, audience, constraints, output format, and what AI must not invent.
Pod lab (45 min): Write your brief for your specific problem. Pod reviews it before AI sees it. Run the brief, review the output, iterate twice in the session. Mentor challenges what you have left out. Something rough must exist by end of this session. Not perfect. Real.
Group (45 min): Live build of a complex HR workflow: an end-to-end candidate screening system that takes a role brief, applies inclusive criteria, ranks applicants, generates interview questions, and flags outputs for human review. Group challenges each step — where could this go wrong, who owns it when it fails.
Pod lab (45 min): Extend your Week 2 output into a multi-step workflow. Define input, processing steps, human review triggers, and output format. Map governance: what data is used, who reviews before it acts, what the escalation path is. Documented in writing, not just running in a chat window.
Group (45 min): Every pod demonstrates their deployed AI workflow to the full cohort. Not a presentation — a live demo of something running in their actual HR process. Group gives structured feedback. AIQ retake completed as a cohort. Score movement discussed openly: which dimensions moved and by how much.
Pod lab (45 min): Proof Pack completion: document what was built, what it does, the governance rule, and the measurable impact. AIQ credential issued. Cohort closes with one commitment each — read aloud — on what changes in your HR role next Monday.
What HR builders make in four weeks.
Your Week 1 problem brief determines what you build. These are the kinds of solutions pods have deployed.
Reads and synthesises inbox and calendar each morning. Surfaces what needs a decision and what you can skip.
Converts a JD into a structured interview guide with competency questions and scoring rubric.
Synthesises engagement data to surface teams at elevated attrition risk before it becomes a replacement hire.
Drafts a JD and simultaneously flags discriminatory language. HRBP reviews before posting.
Turns raw 360 responses into structured themes, evidence, and development priorities. Manager reviews before sharing.
Generates a 5-email onboarding sequence personalised to role, location, and manager. HR reviews before send.
Two ways in.
Apply for a free place or enrol directly. The programme is identical either way.
Build the real thing.
Leave with proof.
Four weeks with Deepika. Your real HR problem on screen every session. AIQ score and Proof Pack on graduation.