Research report | Professional services: Navigating a new operating era

Foreword

Professional services has reached its next inflection point. AI is redefining the operating equation, transforming how firms deliver work, create capacity, and build capability. In doing so, it is reshaping the economics of growth.

For the first time, professional services firms are no longer creating value through people alone.

For decades, growth followed a familiar formula: win more work, hire more people, deliver more work. Today, firms are building delivery capability in fundamentally different ways, combining people, AI, and global delivery, breaking the traditional link between headcount and growth.

But creating new sources of capacity is only part of the equation. Performance will increasingly depend not on creating more capacity, but on coordinating every source of capacity more intelligently.

At the same time, firms face growing pressure to deliver profitable growth, demonstrate returns on AI investment, adapt to evolving pricing models and governance requirements, and meet ever-rising client expectations. Together, these forces are making the operating model itself a source of competitive advantage.

Last year, Dayshape’s report, Inside the leadership growth agenda explored the visibility challenge limiting growth across professional services, highlighting how operational blind spots contributed to revenue leakage, weaker financial performance, and missed opportunities.

This year’s research shows that the conversation has moved on. Visibility is no longer the destination. It’s the starting point.

The firms pulling ahead are moving beyond visibility toward a more connected operating model, capable of coordinating people, AI, and global delivery as one.

As the definition of a resource expands to include AI alongside people, so too must the discipline responsible for optimizing how it’s deployed. That is why resource management is one of the defining strategic capabilities of the next operating era.

For me, that’s the opportunity. Professional services has always evolved alongside technology. But this time it’s different. Firms have the opportunity to rethink not just how work is delivered, but how growth itself is created through an entirely new workforce model.

The firms that do that successfully will define the next operating era of professional services. I hope this research provides both the insight and the inspiration to help your firm lead it.

 Matt Cockett, CEO, Dayshape

Executive summary

Professional services is entering its next operating era. For decades, growth followed a familiar formula: win more work, hire more people, deliver more work. That model is changing. 

AI is reshaping how work is delivered, while global delivery models are expanding how firms access and deploy talent across onshore, offshore, and nearshore teams. Firms are building delivery capability through an increasingly diverse mix of people, AI, and global delivery. As the number of moving parts grows, so too does the complexity of coordinating them. Competitive advantage will increasingly depend on how effectively firms bring these different sources of capacity together through one connected operating model.

So what does operational maturity look like when work is no longer delivered by people alone?

Drawing on insights from 400 C-suite and senior leaders at professional services firms with 750+ employees across the UK and US, this research explores how firms are adapting, and the capabilities separating those pulling ahead from those still building the foundations.

At a glance

The defining tension: Strategic ambition is outpacing operational execution.

AI adoption is now widespread, while resource management has become firmly established as a strategic business capability. But across both, operational maturity has further to go.

Four findings show how this tension is playing out across the industry:

1. The priorities behind growth are changing.

AI is now the industry’s leading strategic priority, with 41% prioritizing AI for internal operations and 38% for client delivery. Improving client retention (32%) also ranks ahead of winning new clients (27%), while increasing delivery capacity (19%) sits lower on the leadership agenda.

The findings point to a shift towards technology, productivity, and strengthening existing client relationships as drivers of growth.

2. AI is delivering value, but operational maturity remains uneven.

79% of firms already use AI to deliver client work, with 69% reporting improved planning and forecasting accuracy and 66% improved efficiency and reduced manual effort. Yet only 16% use AI-supported demand forecasting and 14% have embedded AI across all resource operations.

3. Resource management has reached the boardroom.

98% of senior leaders recognize the importance of resource management to financial performance, 93% use its data in executive decision-making, and 82% view workforce planning as a strategic lever for growth.

4. Execution has yet to catch up.

Despite that strategic recognition, 55% of firms still miss, delay, or turn down client work because of capacity constraints, while 53% say poor resourcing decisions regularly reduce project margin.

Looking ahead.

Closing the gap between ambition and execution will require firms to rethink how they plan and deploy capacity. The challenge is not simply creating more of it, but understanding and coordinating an increasingly complex mix of people, AI, and global delivery against changing demand and commercial priorities.

Throughout this report, we explore why connecting workforce, demand, delivery, and financial intelligence could make capacity intelligence

Introduction: A profession at an inflection point

The professional services industry is no longer powered by people alone.

Across the industry, AI is now central to how professional services firms deliver work. Individuals and teams are increasingly expected to demonstrate measurable productivity gains, while leadership teams face mounting pressure to prove a return on growing AI investment. At the same time, firms are being forced to question long-established commercial models, from how work is priced to how value is measured.

The signals are everywhere. Chief AI Officer and equivalent executive roles are emerging across many of the world’s largest professional services firms. AI strategy is no longer confined to innovation teams. It has become a C-suite priority.

Yet for all the attention surrounding AI, the reality appears far more nuanced.

Some firms are already embedding AI into delivery and building more connected operating models. Others are still working to operationalize offshoring, strengthen workforce planning, improve data quality, and establish the foundations needed for AI to deliver meaningful business value. AI is less forgiving of weaknesses in data and processes that human teams may have worked around for decades, making previously hidden inefficiencies more apparent in both the quality and cost of AI-enabled delivery.

As a result, operational maturity is increasingly uneven, not only between firms but across functions and departments within them. The industry is moving in the same direction, but not at the same pace.

Dayshape’s 2025 Inside the leadership growth agenda report explored the internal barriers limiting growth across professional services. It showed how weaknesses in planning, forecasting, resource management, and operational visibility were quietly contributing to revenue leakage, weaker financial performance, and missed opportunities. The report concluded that predictable growth depended on stronger planning, forecasting, resource management, and the operational visibility needed to support better decisions.

This visibility remains fundamental. But the real challenge is what firms do with it.

The next operating era demands more than a clearer view of capacity. It requires the mechanisms to coordinate that capacity, orchestrate delivery, and maintain control across people, AI, and global delivery.

This report examines how organizations spanning audit, assurance, tax, accounting, advisory, consulting, business and management consulting, and law are responding to the next challenge. It explores the capabilities that define operational maturity in this new environment, and what separates those pulling ahead from those still building the foundations.

The economics of growth have changed

Growth remains the objective. The model for achieving it is being redefined. 

For decades, professional services growth was closely linked to workforce growth. That relationship is beginning to change as firms explore how AI, productivity, and new delivery models can create capacity without relying on headcount growth alone. 

This shift is visible in leadership priorities

AI now tops the strategic agenda, improving client retention ranks ahead of winning new clients, while increasing delivery capacity sits much lower.

Strategic priorities for the next 12 months

Strategic priorities: Then → Now

Comparing findings from Dayshape's 2025 Inside the leadership growth agenda research with this year's survey.

The priorities behind growth have become more targeted.

Last year’s research showed technology investment as a broad strategic priority. This year, that focus has become more specific, with leaders prioritizing where AI can create value across both operations and client delivery.

Growth priorities are shifting too. Improving client retention now ranks ahead of winning new clients, while increasing delivery capacity sits at the bottom of the priorities measured.

Rather than signaling a retreat from growth, the findings point to a change in how firms are pursuing it: placing greater emphasis on technology, productivity, and getting more value from existing client relationships and capacity.

This reflects a broader shift across professional services. Deloitte’s latest State of AI in the Enterprise research similarly points to organizations moving beyond broad AI adoption toward measurable business outcomes. AI investment is increasingly being judged by the business performance it can create, rather than adoption alone.

One detail in the data is particularly interesting: firms place slightly greater emphasis on AI for internal operations (41%) than client delivery (38%).

The difference is modest, but it reinforces an important point. AI investment is not only focused on changing the services firms deliver. It is also being directed toward how the business itself operates, from planning and forecasting to the decisions that shape delivery.

Growth constraints: Then → Now

While leadership priorities are evolving, several of the barriers limiting growth remain familiar.

Operational capability is becoming just as important as workforce capacity.

External market pressures remain the biggest constraints on growth. But technology limitations (34%) now rank alongside talent shortages (35%), while inefficient workforce planning and allocation (28%) remain among the largest controllable barriers.

This matters because these are the same operational capabilities firms are now looking to strengthen through AI.

The opportunity is not simply to invest in new technology, but to use it to improve how firms plan, allocate, and deploy increasingly complex sources of capacity.

The economics of growth may be changing, but the fundamentals remain: firms still need the right capacity, in the right place, at the right time. The difference is that capacity is no longer defined by headcount alone.

Emerging pressures in 2026

From AI adoption to operational impact

AI investment only creates advantage when it changes how a business performs.

AI adoption in professional services has accelerated rapidly. Almost four in five organizations (79%) already use AI to deliver client work, while AI for internal operations is now the top strategic priority for the firms surveyed.

The question is no longer whether firms are adopting AI, but whether that adoption is changing how the business performs. The findings suggest that shift is already underway. More than three quarters of leaders (76%) say AI is already improving resource planning and allocation decisions, reinforcing the shift from AI adoption toward operational impact.

Among organizations using AI in resource operations, improved planning and forecasting accuracy is the most commonly reported benefit (69%), followed by efficiency (66%), and resource allocation and utilization (53%).

The findings point to an important shift in where AI is creating value. While productivity remains important, AI is increasingly supporting the planning and allocation decisions that determine how effectively firms deploy their capacity.

Where organizations are realizing the greatest value from AI

Operational impact: Then → Now

Comparison of findings from Dayshape's 2025 Inside the leadership growth agenda and this year's survey.

A year on, firms are beginning to report the operational impact.

Last year’s research showed firms preparing to use AI to strengthen workforce planning and capacity management. This year’s findings show that investment is beginning to translate into measurable improvements.

AI adoption is widespread. Operational maturity is still developing.

The impact is already visible, but the depth of AI integration varies considerably. Only 14% have fully embedded AI across resource operations.

For most, adoption remains concentrated in specific processes or use cases. More than half (55%) use AI across multiple or specific resource management processes, while a further 27% have AI capabilities in place but are making only limited use of them.

This pattern is reflected in wider industry research. The Resource Management Institute’s 2026 The Emergence of AI in Resource Management report found that while 60% of organizations use AI to support resource management, fewer than 15% use it systematically across the function.

This points to an uneven picture of AI maturity within firms: while AI is already widely used in client delivery, its adoption across the operational capabilities that support that delivery is progressing more slowly. The result is a gap between AI-enabled delivery and the planning and coordination behind it.

Where organizations are realizing the greatest value from AI

Planning maturity remains uneven.

The industry is moving in the same direction, but not at the same pace. The same pattern can be seen in demand forecasting. Only 16% of firms have reached AI-supported demand forecasting, while a further 19% use predictive, scenario-based approaches.

For most firms, planning remains grounded in historical and current data rather than predictive intelligence. And despite growing investment in AI, only 4% can accurately forecast workforce capacity more than 12 months ahead.

The opportunity is not simply to introduce AI into existing planning processes, but to use it to extend how far ahead firms can see, model different scenarios, and respond earlier to changes in demand.

Demand forecasting maturity

Sector spotlight: Accounting

Accounting firms show signs of more advanced AI adoption across resource operations:

• 22% have AI embedded across all resource operations, compared with 14% overall

• 38% use AI across multiple client service lines, compared with 32% overall

• 46% describe themselves as very confident in their ability to forecast workforce requirements

While maturity remains uneven, the findings indicate that accounting firms may be moving further toward integrating AI into both service delivery and the operational capabilities behind it.

The shift from adoption to integration.

AI has crossed the adoption threshold in professional services. The next challenge is integration.

The firms that gain the greatest advantage will not necessarily be those deploying the most AI, but those that embed it into the operational decisions that shape how work gets delivered.

That means connecting AI with the data, planning processes, and resource decisions that determine capacity, utilization, delivery, and ultimately business performance.

The next phase of AI maturity will be defined not by deploying more AI, but by embedding it more deeply into planning, forecasting, resource allocation, and operational decision making.

Resource operations maturity among accounting firms

Resource management has reached the boardroom

The strategic importance of resource management is no longer up for debate.

What was once viewed primarily as an operational discipline has arrived as a strategic business capability, influencing financial performance, workforce planning, and long-term growth. 

The evidence is clear.

Almost every senior leader surveyed recognizes the importance of resource management to financial performance, while more than four in five view workforce planning as a strategic lever for growth.

Resource management is no longer simply about utilization and scheduling. It is now widely expected to inform workforce planning, commercial decisions, client delivery, and business performance.

Resource management has become a strategic business capability

From visibility to business impact: Then → Now

Comparing findings from Dayshape's 2025 Inside the leadership growth agenda research with this year's survey. 

The progression is evident.

Last year’s research showed firms prioritizing technology investment alongside better visibility, forecasting, and operational planning. One year later, the conversation has moved on.

Visibility remains essential, but the expectation now is that workforce intelligence should inform business decisions. 93% say resource management data is already used in executive decision-making, while AI is beginning to strengthen the planning and forecasting capabilities behind those decisions.

Visibility is no longer the destination: it is the foundation.

Confidence versus operational reality: Then → Now

Comparing findings from Dayshape's 2025 Inside the leadership growth agenda research with this year's survey. 

Most organizations are confident in their ability to plan effectively, yet many continue to lose or delay client work because of capacity constraints, rework workforce plans during delivery, and staff projects based on availability rather than suitability.

Workforce planning today

The challenge is no longer proving that resource management matters. It is turning that strategic importance into more consistent operational execution.

The tools and approaches supporting workforce planning help explain why that transition remains a work in progress.

Approaches to workforce planning

The picture is one of transition. Data, dashboards, and AI are increasingly part of workforce planning, yet spreadsheets, static reports, and individual judgment remain widespread.

At the same time, 76% of leaders say AI is already improving resource planning and allocation decisions. The opportunity now is to build on those gains with more connected, forward-looking planning.

Only 4% of firms can accurately forecast workforce capacity beyond 12 months. As delivery models become more complex, near-term visibility alone will not be enough. Firms need a forward-looking view of both capacity and demand, allowing them to anticipate gaps, model scenarios, and make earlier decisions about how work will be delivered.

That requires more than better forecasting tools. It depends on connected data and technology that bring workforce planning, demand, delivery, and commercial priorities together.

Sector spotlight: Accounting

Accounting firms show signs of greater maturity across several workforce planning measures.

• 95% say planned billable time accurately reflects delivery requirements.

• 46% describe themselves as very confident in workforce forecasting.

• 22% have AI embedded across all resource operations.

The findings indicate that accounting firms may be further along in embedding AI and workforce planning into day-to-day operations, providing an early indication of how these capabilities could evolve across the wider market.

Workforce planning maturity among accounting firms

The control tower for the next operating era

The growing strategic importance of resource management reflects a bigger change in the professional services operating model.

Firms are increasingly using onshore, offshore, and AI resources to deliver work. As the sources of capacity become more diverse, the challenge is no longer simply understanding what capacity exists. It is coordinating that capacity against demand, economics, and business priorities.

If we imagine a firm to be an airport, resource management is the air traffic control tower. As airspace becomes busier, better radar provides visibility, but visibility alone cannot coordinate every aircraft.

The control tower must continuously respond to changing conditions and coordinate thousands of interconnected decisions as one system.

Professional services firms face a similar challenge.

The first generation of workforce planning focused on visibility: where people were, what skills they had, and where capacity existed. That visibility remains essential, but the next operating era demands more.

Firms need to understand the full mix of capacity and capabilities available across people, AI, and global delivery; anticipate what they will need; understand the economics; and continuously align that capacity with demand and commercial priorities.

This is capacity intelligence.

Conclusion: Defining the next operating era

A fundamental shift in how professional services firms operate.

Throughout this report, we've explored how the economics of growth are changing, how AI is reshaping operations, and why resource management has become a strategic business capability. Together, these findings point to something much bigger than technology adoption or workforce planning. They point to a fundamental shift in how professional services firms operate.

For decades, growth in professional services was closely tied to adding more people. Today, firms are looking for new ways to increase productivity, improve delivery, protect margin, and create more value from the capacity already available to them.

AI is accelerating that shift. Nearly four in five firms now use AI to deliver client work, yet its integration into the operational capabilities that support that delivery remains at a much earlier stage. The next phase of transformation will be defined not by AI adoption alone, but by how effectively firms evolve the operating model around it. 

At the same time, that operating model is becoming more complex. Firms are increasingly combining people, AI, and global delivery to deliver work.

As the sources of capacity become more diverse, the challenge is no longer simply creating or understanding capacity. It is coordinating it.

Doing that well requires more than visibility. Firms need to understand the capacity and capabilities available to them, anticipate future demand, understand the economics of different delivery choices, and continuously decide how each source of capacity should be deployed.

The opportunity is to build the operating model that makes that possible.

Capacity intelligence is the ability to understand the full mix of capacity and capabilities available to the firm, across people, AI, and global delivery, and continuously align them with future demand, economics, and commercial priorities. It moves the focus from managing the capacity the business has today to continuously shaping the capacity and capabilities it will need tomorrow.

From visibility to capacity intelligence

The capabilities behind capacity intelligence

Building this capability requires firms to connect information that has traditionally been fragmented across the operation. Real-time capacity visibility needs to sit alongside connected data, real-time financial data, and a forward view of demand.

1. Real-time capacity visibility

Capacity, availability, skills, and capabilities across people, AI, and global delivery.

2. Connected data across the firm

Workforce, project, skills, demand, and delivery data connected rather than sitting in silos.

3. Real-time financial data

Revenue, cost, margin, and project economics available to inform decisions as they are made.

4. Future-facing demand and capacity planning

What work is coming, what capacity and capabilities will be required, and where they should come from.

5. Continuous decision-making and coordination

The ability to respond as demand, capacity, economics, and business priorities change.

Together, these capabilities create a more complete, forward-looking view of the business: what capacity and capabilities are available, what demand is coming, what different delivery choices will cost, and how capacity should be deployed against the opportunities ahead.

This is the opportunity at the heart of the next operating era: moving from managing the capacity the business has today to continuously shaping the capacity and capabilities it will need tomorrow.

Firms that can bring these capabilities together will be better positioned to make earlier decisions, adapt their delivery model as demand changes, and turn workforce intelligence into stronger execution and more profitable growth.

Five questions every leadership team should ask. 

As professional services enters its next chapter, the questions leadership teams ask will become just as important as the technologies they invest in.

1. Are we planning today for how client work will be delivered three years from now, through the right mix of onshore teams, offshore teams, and AI?

2. Is AI improving individual productivity, or is it improving how the business plans, allocates, and delivers work?

3. Are workforce decisions directly connected to commercial outcomes such as revenue, margin, and client delivery?

4. Can we continuously coordinate capacity as demand,

priorities, and delivery models evolve?

5. If demand increased by 20% tomorrow, could we deploy capacity differently without hiring more people?

Methodology

This report is based on a survey commissioned by Dayshape and conducted by OnePoll between June 18 to 25, 2026. 

Survey audience

Senior leaders at professional services firms in the UK and US with 750+ employees, spanning accounting, assurance, audit, business and management consulting, law, and tax. The sample included 200 respondents from accounting firms.

The survey focused on firm-level priorities, challenges, and investment plans for the year ahead. Questions included a mix of single- and multiple-response formats (e.g., “select up to three” or “select all that apply”).

Data collection and analysis

Data collection was carried out online via OnePoll’s platform, which adheres to the MRS Code of Conduct, ESOMAR guidelines, and British Polling Council standards. OnePoll also upholds commitments to inclusion, equality, and cybersecurity through recognized certifications. The survey was designed and analyzed by Dayshape and ASPR.