How I Became an AI-Augmented HR Consultant—and Solved Consulting’s Trickiest Equation

For decades, the consulting equation has meant trade-offs: time, cost, or quality — pick two. With generative AI, I finally found a way to get all three. Here’s how.

After 20+ years in large-scale HR consulting—leading client projects with full teams of writers, designers, and project managers—I now work independently with equally sophisticated clients on engagements just as complex.

But I hardly think of myself as a one-person operation, thanks to generative AI. So, imagine my delight when I recently came across the concept of the AI-augmented professional—someone who combines deep expertise with generative AI to dramatically amplify what one person can deliver.

It’s exactly that model that has helped me solve one of consulting’s oldest challenges.

My clients are thrilled. And here’s why.

Every Consultant’s First Lesson

It’s the so-called Project Management Triangle. It reflects the three constraints to consider when defining, pricing, and delivering a project: scope or quality; time; and cost.

It goes something like this: In the ideal engagement, all three are balanced—forming a perfect equilateral triangle where both client and consultant are happy. But in real consulting life, that perfect balance is rarely feasible. Constraints happen. You can generally optimize two sides of the triangle, but not all three.

For example, if a client needs a deliverable fast, time becomes the constraint. That affects cost—typically upward for rush fees or for engaging more senior consultants. Or the project scope may have to be scaled back to stay within the same budget. Pick two. The client can’t have all three—a rush timeline, full scope, and regular fees. No one is entirely happy.

What if that could change?

Enter Generative AI

The journey started over two years ago when I signed up for a paid subscription to ChatGPT.

It was specifically to help with client work. I was getting very busy and I wanted to see what it could do.

To accelerate my learning curve, I also joined an informal but highly informative collaboration of ChatGPT users who leverage generative AI for everything from hardcore day trading research, to generating content for a highly successful gaming app, to writing code at a local tech start-up. We share tips, new discoveries, success stories, lessons learned.

There’s plenty of debate in the media and elsewhere about what business value AI actually delivers. I’m pleased to report that it’s helped me solve the equation for the perfect Project Management Triangle. Consultant and client are both happy.

Of course, solving the triangle didn’t happen overnight. It took experimentation, risk-taking, some trial and learning.

Here’s How I Did It

I’ll admit: I was very cautious at first about telling clients I was using generative AI.

I worried they might think I was cutting corners or letting technology do all the work for me. And at first, I was using it for the simplest of tasks, such as reworking a tricky paragraph or editing and proofreading my work.

I got bolder over time. I discovered that the more precisely I primed, the better the model performed. I began experimenting with multi-stage prompting—building context in layers, feeding ChatGPT background materials, audience profiles, and sample tone before ever asking it to draft. I learned how to train tone consistency across deliverables, run scenario simulations to stress-test messaging, and use iterative loops to refine frameworks until they met my standards.

What surprised me was how much human work it still required. To get exceptional output, I became, in effect, a kind of generative AI project manager—designing the workflow, sequencing the inputs, and pushing the model to its limits. The technology could accelerate production, but only if I guided it with clear strategy, creative judgment, and constant review and feedback.

ChatGPT and I are a partnership—but I’m very much still here. We work together like this:

• AI handles the legwork — deep research, data crunching, rapid synthesis, first-draft generation, option exploration, scenario stress-tests, editing, image generation, and so on.

• I manage direction and accountability —strategic direction, creative exploration, client context, tone, ethics, trade-offs, final decisions, peer review, quality assurance. And yes, this includes the not-so-simple task of priming the model to deliver up to or exceed my expectations.

In practice, I’m in the engagement every step of the way and doing pretty much the same things I did when I was leading client engagements as a Partner at Mercer. Still here.

And here’s the part that often gets overlooked: In the AI-augmented world, the technology can’t do any of this without me. It doesn’t know my client’s business, culture, or leadership dynamics. It can’t be certain when a tactic will land wrong or when a strategy needs rethinking. It’s my human expertise, insight, and judgement that transforms machine learning into something truly differentiating for my clients.

Moment of Truth

Eventually, I fessed up to my clients.

I was delivering more and more value to my clients. Turning around deliverables very rapidly. Not charging extra for extra work. Why keep the secret sauce a secret under those circumstances?

At the same time, the use of AI was becoming more normalized in the everyday business environment. Pretty similar to how things like calculators, Microsoft office, or Zoom—all tech innovations that have transformed business—have superseded lower-tech tools. Generative AI is no different. The tools change, but the consultant’s opportunity to make optimal use of them for the client doesn’t.

Even so, I still get questions about using ChatGPT. Yes, absolutely, AI can make mistakes, show bias, put out so-called workslop. So can humans. As one of my longtime mentors used to say, that’s why we have peer review.

What the Partnership Looks Like In Action

Here’s how generative AI helped me become a better consultant by solving the perennial Project Management Triangle equation.

Scope/Quality: Expanding What’s Possible

In consulting, constraints often dictate what can—and can’t—be delivered. As a result, essential elements too often become “nice-to-haves” and inevitably get left on the table. One of the most remarkable aspects of generative AI is that it erases many of those limitations. What used to be nice-to-have now becomes you-absolutely-can-have—without adding cost, time, or extra hands.

Earlier this year, for example, I helped several clients modify or sunset their DEI programs—a controversial change that required careful framing and nuanced communication. Using AI-assisted analysis and simulation, I was able to explore how different stakeholders might react, anticipate objections, and refine tactics and key messages with greater insight. The result: clear, confident communication through a sensitive transition. In the past, that level of rigor required weeks of costly research, focus groups, or long SME review cycles. Today, AI makes that analysis so accessible it can be used to test something as mundane as annual enrollment reminder postcard.

AI also allows me to easily deliver more holistic, robust solutions. Once the centerpiece deliverable of a project is complete, generative AI can very quickly leverage it to create companion collateral—quick-reference summaries, presentations, leadership talking points or scripts, visuals, online content, launch communications, and even more. It makes best-in-class HR communication and change management accessible to more clients—and for more situations—than ever before.

Time: Accelerating Delivery Without Sacrificing Quality

In traditional consulting models, time is the dimension most often squeezed. Coming from a highly leveraged, big consulting firm model, I was used to having more junior team draft content, then, after my review, we’d go through a cycle of reviewing and refining it through multiple rounds before anything reached the client. It worked and it delivered good work—but it was slow.

Now, generative AI functions as my entire team. Given the same level of direction I’d give a junior consultant, AI can generate strong first drafts of just about any HR content almost instantly. And the real advantage isn’t just speed; it’s agility. Projects can evolve in real time, allowing me to test multiple approaches, adjust direction immediately, and bring clients into the process sooner. It opens space for experimentation and creativity, the opportunity to play around with multiple concepts without really losing any time.

Recently, for example, I developed the full content and narrative for a 30-minute online training module in about one working day—from initial concept to client-ready draft. What once required a team, multiple meetings, and several weeks of back-and-forth was completed in a single day, with the same depth, clarity, and tone my clients expect.

That’s what AI augmentation looks like in practice: compressing timelines without cutting corners—delivering quality, speed, and adaptability all at once.

Cost: Delivering More for the Same Investment

Across the industry, many consulting firms are indeed using AI to make their work faster and more efficient. But the real question is this: are clients benefiting from it? In most cases, the efficiency gains stay on the firm’s side—improving margins, not reducing client fees. To me, that misses the point. The promise of AI isn’t just operational efficiency; it’s delivering more value for the same or better yet, lower cost.

For my annual retainer clients, for example, we typically start the contract year with a defined scope of work that outlines specific projects or support. As I’ve fully integrated generative AI into my workflow, I’ve been able to say “yes” to far more ad hoc requests—without increasing fees or saying “no” to or delaying other projects on the docket.

It’s the modern way to create value: more results, same investment. In my mind, it’s also essential to being a trusted advisor in today’s environment.

The Bottom Line

Consulting has evolved since I started my career in 2000—but the traditional models are about to get left behind. Generative AI has completely solved the project triangle: I can deliver more scope, faster turnaround, and higher quality for the same or—less—client investment. Perfect equilibrium—at last.

If your consultants aren’t doing the same things I am, you might be getting less than you could, waiting longer to get it, and paying more than you need to.