Looking at the HR authorities I reference — CIPD, SHRM, Josh Bersin and Dave Ulrich — they start from four different places but arrive at the same point: I'm now convinced that rolling out AI responsibly across the organization is HR's job. To take on that job, however, the function itself must be AI literate. Here is a new newsletter with the four-layer readiness framework that builds that fluency, zero-cost courses, and the reference and benchmark notes you'll want by your side when making the call.
In my conversations with HR professionals and even consultants, I've noticed a shift in one concept. No one asks me anymore "how do I learn AI" — some don't run it through their own filter or simply take help, but they are learning. The question has matured: "How do I roll out AI in my organization in a useful and responsible way?"
I think that question reads HR's role at the right time and clearly. Because from everything I've reviewed and followed, embedding AI into a company is not a software rollout topic; it sits at the center of people and culture — and that is exactly the domain of management and HR.
Of course this is not just my view; in this piece I share the expectations and analyses of different authorities together with my own perspective.
CIPD has stated that the role of the people profession in the responsible use of AI is vital and is openly calling on HR to lead this rollout. It emphasizes that HR should lead on ethics, culture and policy development.
SHRM, Josh Bersin and Dave Ulrich reach the same conclusion by different paths. So the question is no longer "when will HR be ready for rollout?"; it has become "does HR have the fluency (literacy) to do this?"
What I want to touch on in this piece is exactly how to build that fluency: I first looked at what the four schools expect from HR, then, out of the courses and trainings I personally reviewed, I shared the ones that genuinely add value for HR — and the order that works best.
The owner of the rollout is clear, but where is the readiness?
According to CIPD research, 58% of workplaces have not given their employees a clear AI plan, 67% have provided no AI training at all, and only 11% see their leadership team as ready for the AI era. SHRM says 92% of CHROs expect more integration. Given the maturity gap between ownership and readiness, this is the clearest case for HR to build its own fluency.
IN THIS NEWSLETTER;
- The role the four schools expect from HR: what do CIPD, SHRM, Josh Bersin and Dave Ulrich say, and where do they diverge?
- A four-layer framework for HR to prepare itself: understanding, fluency, judgement, integration
- Seven zero-cost AI courses for HR professionals — with reviews and assessments
- A staged learning plan, benchmark data, and where to start applying it in HR tasks
Where has the expected role of HR moved to?
Before spending time and effort developing a competency, the question "is this really my job?" needs an answer. According to the WEF, 59% of the global workforce will need reskilling by 2030; who will own a transformation of that scale? I tried to get the answer from four separate schools on HR.
CIPD — HR as a core member of the governance team. CIPD's framework lands with me like this: for an AI tool to create value in the organization, it must be aligned with people, culture, structure and work; the tool itself is only one part of the fabric. That's why CIPD wants HR at the table wherever AI touches people — at least as much as IT, legal and compliance — and lays out a five-step path for the function: first build your own knowledge and skill, take ownership of employee data, join the governance conversations, audit people-related risks, embed human-centered principles into the culture. Note that the first step in the sequence is learning.
SHRM — the real topic is decision architecture. SHRM reduces the same topic to a formula: AI + HI = ROI. The sum of artificial intelligence and human intelligence. HR's job here is to tell where AI strengthens human judgement and where it tries to replace it. This is less about tool selection and more about building decision architecture. SHRM's own data shows the HR function is only just beginning: AI in HR is used most in recruiting (27%), HR technology (21%) and learning-and-development (17%).
Bersin — the real work is redesigning the work. I want to share a key sentence from Josh Bersin's Superworker research: "success with AI is a human matter; if it is read as a technology matter, the transformation will not happen at the expected pace and will fall behind." For him today's challenge doesn't end with deploying AI; the real work is redesigning jobs and processes around it. Bersin sees this journey in four stages — assist, augment, delegate, autonomy. The fifth item on the 2025 agenda is exactly this newsletter's subject: accelerate the shift to Systemic HR, experiment with AI tools in HR, and train the HR team on AI. Bersin recommends every HR function set up its own "AI transformation team." In the 2026 agenda he raises the bar another notch, asking the HR professional to become a citizen developer. In the HR 2030 vision the forecast is clear: HR teams will shrink 30-40%, remaining skills will deepen, HR business partners will turn into agent managers. McKinsey data explains this urgency — 88% of organizations use AI in at least one function, but only 21% have redesigned their workflows. Almost everyone has the tool; those rebuilding the work around it with this preparation and approach remain a minority.
Ulrich — a human capability revolution. Dave Ulrich holds the topic from an entirely different angle. For him AI is launching a human capability revolution, and HR's role must evolve from finding and retaining the right people for today's job expectations to building the workforce's continuous learning and adaptation capacity. In classic Ulrich style I want to add: HR that only looks inward is looking at a mirror; you have to replace the mirror with a window. Ulrich's own data strongly supports this newsletter's view — according to a thirty-year HR competency study, roughly 30-40% of competencies renew every four to five years. On the AI side he gives HR a concrete list: build talent that can do AI, set up responsible and no-harm policies, elevate processes with AI, own the human-technology interface. And he draws a clear line: if AI is used in place of judgement it backfires; if it is used to fuel better conversations, it elevates them. Ulrich's observation also tells us where the function stands: HR is only 20-25% along the value creation curve with AI. LinkedIn data supports this view, I think — a 177% increase in AI skills added to profiles since 2023, while 91% of L&D professionals say human skills like critical thinking, empathy and communication are more valuable than ever.
Where do Bersin and Ulrich diverge?
Bersin is on the side of speed and his forecast is bold: super-agents are rebuilding everything from hiring to learning, from compensation to internal mobility; the HR team shrinks; the remaining skill set deepens. Ulrich looks at it a little differently. In his research, among the four paths of human capability, the organization is the one that most strongly explains stakeholder value; the HR function itself is the weakest. So Bersin's call to "redesign HR's operating model," read together with Ulrich's data, can mean investing in the lowest-leverage area.
I think this is a sequencing priority that needs to be resolved. Bersin tells you how fast to move; Ulrich tells you what for. If HR's own fluency becomes the goal, Ulrich is right; if that fluency is used to change the organization and external stakeholder value, Bersin's tempo is in the right place. The same distinction holds in daily work: speed up on first drafts and grunt work; on calibration and ethics, remember Ulrich's warning. To make this distinction, HR first has to know the tool. You can't decide where a tool you don't know will stand.
How does HR prepare itself? Four layers
When I put the expectations of the four schools side by side, they all sit on four separate layers. The order matters, because each layer sits on top of the previous one.
1. Understanding. Knowing what AI can and cannot do. Ulrich's awareness expectation from leaders sits here: knowing at a basic level how the tool works, what data it uses and what risk it carries. With this awareness, you have something to say at the governance table.
2. Fluency. Building a way of thinking with AI. Bersin's Superworker definition overlaps with this skill — an employee who learns to optimize systems multiplies their own output. Tools change, but this way of thinking does not go out of date.
3. Judgement and governance. Deciding where to delegate and where to keep the decision. Ulrich's AI criteria around judgement (responsible policy, accountability, human-technology interface), SHRM's AI+HI distinction, and CIPD's governance steps all meet on this layer. Ethical evaluation, bias control and ownership of employee data are discussed here.
4. Integrate. Bringing literacy into HR processes. CIPD's fifth step and Bersin's recommendation that "every HR function set up its own AI transformation team" both point here. It will be hard for the function to lead the rest of the company without its own work changing; and this kind of transformation also wants pilot practice.
That's why I look at the courses below not as "personal curiosity" but as the infrastructure that builds these four layers. First you become fluent; then you make the organization fluent.
How I selected the courses
There are hundreds of "AI literacy" resources in the market and most can look similar. I focused my research on courses from the companies that build these tools themselves and from recognized education institutions; the approach is simple — the maker of the tool is the best place to explain it. My evaluation approach is also:
- Who it suits — who actually gets value from it?
- Strength — what can you use the very next day?
- Limit — where does it fall short?
I tried all seven options below; which one suits you depends on your starting level and the tools your organization uses.
The 7 AI courses I evaluated for HR
1. AI Fluency: Framework & Foundations — Anthropic
Who it suits: As you know, this is the maker of Claude and in my view one of the strongest tools among AI options. Anyone ready to go beyond tools and think with AI. So pretty much everyone reading this newsletter.
Strength: Goes beyond a specific tool and focuses on "how to work and think with generative AI." The 4D framework of four competencies (Delegation, Description, Discernment, Diligence) is applicable and durable; tools change, this way of thinking will not. About 3-4 hours, with an assessment and completion certificate at the end. Completely free.
Limit: The interface could be better; exercises can hide at the bottom of the page.
My strongest recommendation on the list. Goes beyond using a tool and teaches you the way of working with AI; you can review the content on Anthropic Academy. (The same course is also on Coursera).
2. Google AI Essentials — Google (Coursera)
Who it suits: Pure beginner level.
Strength: Sets the fundamentals well; makes room for collaborative low-risk tasks and a surprisingly good prompting section. Five short courses, about 8-10 hours.
Limit: The videos are quite scripted and distant. Adds little for someone who knows the basics. Videos and materials are free; Coursera fee needed for certificate and graded assignments.
A solid foundation for those starting from zero. Check out Google AI Essentials.
3. Google Prompting Essentials — Google (Coursera)
Who it suits: HR professionals who have the basics but can't lift the quality of their output and want practical wins in daily work.
Strength: Runs through examples directly useful for HR: drafting emails, turning meeting notes into action, extracting insight from a report, even rehearsing a tough conversation. Teaches you to build a reusable prompt library and to evaluate output for bias and error.
Limit: More application than conceptual depth; the Anthropic course does the "why" side better. Certificate paid, videos and materials free.
The most practical choice for those who want to apply what they've learned the next day. See Prompting Essentials.
4. AI Fluency — Microsoft Learn
Who it suits: If your organization's main AI tool is Copilot and you work in the Microsoft ecosystem, this is directly for you.
Strength: A comprehensive path from basic concepts to responsible AI, and from generative AI to daily use of Copilot. Fully free and self-paced.
Limit: Quite long and in places full of "nice-to-know" content; you need to pick and choose the parts you need. Limited value if you don't use Copilot.
A fitting starting point for Microsoft-based organizations. AI Fluency path on Microsoft Learn.
5. Career Essentials in Generative AI — Microsoft & LinkedIn
Who it suits: Basic-to-intermediate HR professionals who want a free certificate they can quickly show on their LinkedIn profile.
Strength: Five modules cover the basics of generative AI, building prompts, and the distinction between a search engine and a reasoning engine. Free Professional Certificate on completion. About 5 hours.
Limit: Coverage is shallow; not enough for an advanced level, better viewed as an intro and a visibility tool.
Efficient for a quick foundation + visible credential. Review on LinkedIn Learning.
6. AI for Everyone — DeepLearning.AI (Andrew Ng)
Who it suits: HR leaders who want to grasp the strategy of AI more than using the tool; who will explain to their team or employer "what this means for us."
Strength: Delivered by one of the field's most respected names, Andrew Ng; no code, no equations. Builds the ability to see where AI will create value in an organization. As a more up-to-date alternative, Generative AI for Everyone focuses on generative AI.
Limit: No hands-on tool use; entirely conceptual. Free to audit, certificate paid.
Valuable for strategy and decision perspective. Review AI for Everyone.
7. Elements of AI — University of Helsinki & MinnaLearn
Who it suits: Pure beginner level looking for an answer to "what AI is, what it can and cannot do" without drowning in math.
Strength: A classic completed by more than two million people, translated into 26 languages, fully free.
Limit: Generative AI and the LLM side are not up-to-date; foundation is solid but doesn't reflect recent developments. No Turkish option.
Still a good, free intro for laying the mental foundation. Review Elements of AI.
Bonus — HR-specific: SHRM AI+HI Specialty Credential
The seven courses above help you build AI literacy in the general sense. If you want an HR-specific program embedded across the function from hiring to performance and learning, SHRM's AI+HI Specialty Credential is the most specific option. Not free and built around SHRM membership; but the content closest to the HR context is here. I see it as an upper layer to consider after building general literacy.
An important note
You may have found different free or paid AI trainings and courses too, and you may think almost all of them still consist of traditional modules, videos and exercises. Very little AI is used while teaching AI.
Another issue I see: most of these courses target the general employee and don't put HR's own work — hiring, performance calibration, workforce norms, competency architecture — at the center. They build literacy (which is my purpose in this article), but carrying that literacy into your context is largely up to you. The plan below is meant to make that easier.
The path I would follow if I were starting from zero
If I were starting from zero on AI in HR today, I would follow a plain path that builds the four layers above in order. I've also written next to each step which expectation it addresses.
Four-layer learning plan
- Foundation layer — Understanding: Learn what generative AI is and how it works with Google AI Essentials or Elements of AI. Ulrich's expectation of knowing how the tool works, what data it uses and what risk it carries is met here.
- Thinking layer — Fluency: Learn to think with AI through Anthropic AI Fluency. Bersin's Superworker definition sits on top of this layer; never skip this step, it's the only lasting investment.
- Practice layer — Judgement: Apply what you learn to your own HR tasks with Google Prompting Essentials — generating interview questions, summarizing policy, analyzing an employee survey. SHRM's AI+HI distinction only takes on practical meaning here.
- Organizational layer — Integrate: Embed an AI tool (Claude, Copilot or any you have access to) into your daily workflow and roll it out to your team. CIPD's fifth step and Bersin's Systemic HR call meet on this layer.
A few notes by context
- If yours is a Microsoft-heavy organization, you can replace Google with Microsoft AI Fluency in step 1.
- If you already know how generative AI works, skip step 1 and go straight to 2 — but never skip 2.
- For your practice area, use any tool you have; what matters is tying what you've learned to a real piece of work.
Where to apply it in HR
Literacy is not the goal in itself; the real win comes when you embed it inside the function. SHRM data also shows where adoption is most concentrated; I would call these the starting points for quick wins.
- Recruiting (27%): Writing job postings, generating screening questions, drafting interview guides.
- HR technology (21%): Simplifying policies and procedures, first response to employee questions.
- Learning & development (17%): Content drafts, learning scenarios, assessment question banks.
- Employee experience (14%): Analyzing open-ended survey responses, feedback summaries.
The most important piece of advice I can give you when working with AI is: delegate operational work to AI, keep "judgement" — idea generation — to yourself. Calibration, ethical evaluation and the final call must be OURS — this is why the LinkedIn data foregrounds human skills.
Final word
Which AI model you pick and which courses will work best depends on your context, your level and your goal. But one thing I can say clearly: AI literacy is no longer a topic to leave "to those who are interested" in HR; it has become one of the function's core competencies. That is also the common point of the four schools from CIPD to Ulrich. I'm sure that the HR team that moves early will be in a position to guide the rest of the organization.
I hope this piece helps you both build your own skill and empower those around you with AI.
Would you like to measure your organization's HR AI maturity?
To see where your HR function stands, you can use IC Consulting's HR Digital & AI Check-Up — we start from your existing strengths and shape your roadmap together.
IC Consulting | İlhan Çağlar — HR and Management Consultant