In part one of this series, we looked at why AI is changing the economics behind the traditional consulting pyramid.
Now comes the harder question: What do you build in its place?
Consulting firms can gain plenty of productivity from AI without becoming more adaptable. Faster research and drafting won’t solve an expertise shortage. Automating junior work won’t automatically produce the next generation of senior consultants. And giving people AI tools won’t tell leaders where critical skills lie or who can move on to the next high-value engagement.
Those are workforce questions.
For HR, workforce planning, and consulting operations leaders, the opportunity is to rethink how the firm develops, finds, rewards, and deploys capability. The goal isn’t simply a smaller pyramid. It’s an operating model that can respond faster to customer demand, skills, and changes in the work itself.
Before looking at how to build that model, it helps to see how the questions themselves are changing.
Key takeaways
- Start with the shift in consulting economics. As explored in part one, AI is compressing routine knowledge work, changing how consulting firms create value, and putting greater pressure on the development and deployment of expertise.
- Move beyond headcount planning. Skills-based workforce planning gives consulting firms a clearer view of the capability behind the numbers.
- Develop expertise deliberately. As AI changes traditional junior work, structured practice, coaching, and real-world learning become more important.
- Protect scarce skills. Performance, compensation, and succession can help firms retain and grow the judgment, expertise, and organizational knowledge that are becoming harder to replace.
- Make mobility easier. Better skills visibility can help firms redeploy people as customer demand and the work itself change.
- Connect workforce information. A unified HCM platform can give leaders a clearer view of skills, capacity, performance, development, and workforce needs, enabling more informed decision-making.
- Treat AI readiness as a workforce capability. Sustainable advantage comes from how effectively people, skills, organizational context, and AI work together—not simply from access to AI tools.
The questions consulting leaders need to ask are changing
For years, the traditional consulting model made some workforce questions relatively predictable:
- How many people do we need?
- At which levels?
- How many projects can our teams support?
- Where are our utilization gaps?
- How quickly do we need to hire?
Those questions still matter. But as AI takes on more routine knowledge work and value shifts toward specialist expertise and judgment, they’re no longer enough.
Consulting leaders increasingly need to ask:
- What capabilities does this work actually require?
- Where do those skills and areas of expertise exist today?
- Which capabilities are becoming scarce, overloaded, or concentrated in too few people?
- Who has adjacent skills that could be developed or redeployed?
- Which work should be handled by people, supported by AI, or automated?
- How will early-career professionals build the judgment that routine work used to develop?
- Can we move people and expertise quickly enough to keep pace with changing customer demand?
These questions shift workforce planning from managing a hierarchy to managing capability.
And they put HR much closer to the firm’s commercial heart. When people, skills, utilization, and customer demand are tightly connected, workforce decisions directly influence delivery capacity, cost, retention, and growth.
1. Move from headcount planning to capability planning
Most workforce planning begins with roles and numbers: How many consultants do we need? At which levels? In which locations? And at what cost?
Keep those questions, but add another layer.
Start by identifying the capabilities the work actually requires. A project might need someone who understands a regulated market, someone who can verify AI-assisted analysis, someone who can lead a sensitive customer conversation, and someone who can design an automated workflow. Those examples illustrate a more task- and skills-based approach to workforce planning: define the work by the tasks to be done and the skills required to do them.
A job title won’t necessarily tell you who can do those things.
A practical starting point is to:
- Define the capabilities behind important projects and service lines, rather than relying only on job titles.
- Build visibility into where those capabilities currently sit across the business.
- Identify critical expertise concentrated in too few people that could create delivery or succession risk.
- Look for adjacent capabilities that could support redeployment when demand for particular work changes.
- Compare the skills available today with the capabilities future customer demand will require.
This gives the business a more useful question than “Do we have enough people?”
You can start asking, “Do we have the capability to deliver what customers need next?”
2. Replace passive apprenticeship with intentional development
Once AI takes on more research, drafting, and first-pass analysis, firms can’t assume early-career professionals will learn simply by being around the work.
Instead, identify what the old tasks actually taught.
If drafting developed structured thinking, create assignments where people have to defend the logic behind an AI-assisted draft. If research is built on a source discipline, run source-verification exercises. If project exposure develops judgment, give people realistic cases where they have to make and explain decisions.
Practical approaches can include:
- Case clinics based on real engagements
- Simulated customer situations
- AI-output critique sessions
- Expert shadowing
- Structured coaching
- After-action reviews
- Progressive assignments with more ambiguity over time
The important question isn’t whether someone can use AI. It’s whether they understand the work well enough to challenge it, improve it, and remain accountable for the outcome.
3. Protect and reward the expertise that becomes scarce
As baseline output becomes easier to create, expertise becomes more important to protect.
Look at the capabilities your firm cannot easily replace: domain knowledge, customer trust, critical judgment, governance, institutional memory, and the ability to supervise high-risk AI-assisted work.
Then ask whether your performance and reward systems reflect that value.
For example:
- Are experts recognized for coaching others, or only for their own billable work?
- Does performance distinguish good reasoning from polished output?
- Are people rewarded for creating reusable knowledge?
- Does succession planning identify expertise risk as well as leadership risk?
- Does compensation reflect skills that are genuinely scarce?
HR has an important role here because performance, compensation, learning, and succession can no longer operate as separate processes. Together, they determine whether valuable capability grows or becomes concentrated in an increasingly small group of people.
4. Make internal mobility part of workforce planning
When demand shifts, external hiring isn’t always the first answer.
Someone already in the firm may have customer knowledge, institutional context, or adjacent capabilities that make them a strong candidate for the work.
Build mobility into the planning process:
- Identify work that is shrinking or changing.
- Look for people with transferable skills.
- Define what additional capability they need.
- Create a realistic development route.
- Make that talent visible to the teams that need it.
This can help firms retain organizational knowledge rather than losing experienced people in one area and having to recruit from scratch elsewhere.
But mobility depends on visibility. If capability is buried inside job titles, spreadsheets, or managers’ memories, moving talent quickly becomes much harder.
5. Build workforce visibility into the operating model
The on-demand webinar, The end of the consulting pyramid: How AI is forcing a workforce reset, explores a practical problem facing many professional services firms: staffing decisions are still made through spreadsheets, email, Slack, HR requests, disconnected systems, and individual managers’ knowledge.
That makes it difficult to answer basic questions quickly: Who is available? Who has the right skills? Who is overloaded? And where can talent be redeployed?
That’s why workforce visibility becomes a core part of the operating model.
A useful workforce view should help leaders understand:
- Skills and capability
- Capacity and utilization
- Development and performance
- Critical-role and succession risk
- Mobility opportunities
- Workforce costs
- Future demand
For HR, this changes the conversation, too. Instead of reporting headcount after decisions have been made, HR can bring workforce context into decisions about growth, staffing, cost, risk, and delivery.
6. Know what to look for in an HCM platform
Workforce visibility only helps when it stays connected to the decisions and people processes that shape capability over time.
When evaluating an HCM platform for a professional-services organization, look beyond employee records. Consider whether it can connect the processes that keep skills, development, performance, mobility, and workforce plans up to date as the work changes.
Useful capabilities may include:
- A shared structure for roles and skills
- Workforce and headcount planning
- Performance management
- Learning and development
- Compensation planning
- Succession planning
- Workforce analytics
- Internal mobility
- Connected people data that gives leaders and managers a consistent view
The goal isn’t more software. It’s turning workforce visibility into a more connected way to plan, develop, and deploy capability.
For a consulting firm, that might mean spotting a skill shortage earlier, identifying where expertise is underused, aligning development with future demand, or understanding the workforce implications of a new staffing model before acting.
A unified platform can make skills-based planning practical by giving HR, managers, and business leaders a more consistent view of people, skills, and workforce needs.
Recommended For Further Reading
7. Build the workforce advantage, not just the AI advantage
AI tools will continue to improve, and access to them will become increasingly common.
What will be harder to copy is the way a firm organizes around them.
Can you see where your expertise sits? Can you move it quickly? Can you keep developing future specialists? Can managers make better staffing decisions? Can HR connect workforce decisions to the commercial reality of the business?
Those are organizational capabilities.
And they’re what help turn AI productivity gains into a more adaptable way of operating.
The firms that succeed won’t simply adopt AI faster. They’ll redesign how work, skills, and people come together.
<<See how HiBob can help your firm build a skills-based, AI-ready workforce.>>
FAQs
An AI-ready consulting workforce combines the right skills, expertise, workforce visibility, and development opportunities to help a firm adapt as AI changes the work. It is not simply a workforce that has access to AI tools. It can use them with sound judgment, accountability, and a clear view of where capability is needed.
AI is changing the tasks consultants perform, and the capabilities firms need to deliver value. That means workforce planning needs to go beyond headcount, job levels, and utilization. Consulting leaders need clearer visibility into skills, expertise, capacity, development needs, and future customer demand.
Skills-based workforce planning focuses on the capabilities work requires, not only the number of people or job titles a firm has. It helps leaders identify where critical expertise sits, where skill gaps or risks may be emerging, and which people could be developed or redeployed as demand changes.
Internal mobility helps firms respond to changing customer demand without relying only on external hiring. When leaders can see transferable skills, customer knowledge, and adjacent capabilities across the business, they can create development paths and move people into new opportunities more effectively.
Consulting firms should look for an HCM platform that connects the people processes behind capability planning, including skills, workforce planning, performance, learning, compensation, succession, analytics, and internal mobility. A connected view of workforce data helps HR, managers, and business leaders make more informed staffing and development decisions.