Big Four audit practice puts AI at the core of workforce optimization with Dayshape Advise

From pilot to production: how a Big Four audit practice embedded AI-powered workforce allocation with Dayshape Advise.

Rebuilding the operating model: From strain to stability

One of the world’s largest audit practices turned to Dayshape’s AI-powered platform to transform how work is planned and deployed across the firm.

A senior Partner with more than 25 years at the firm put it simply:

“Professional services firms, even in the new AI world, are fundamentally resource management businesses. You make your money by getting the right people on the right job at the right time at the right price.”

At this firm, that capability had come under significant strain – pressured by rapid growth, fee compression, regulatory scrutiny, and disconnected systems that limited visibility between finance and resource management.

“A stupidly high proportion of our engagements made no money.”

Attrition reached 17–18 percent. At some grades, nearly two in five professionals were leaving the firm.

The firm recognized the operating model needed rebuilding.

Working closely together, Dayshape implemented a unified resource management platform connecting workforce planning, scheduling, and financial performance data across the audit practice.

For the first time, the firm had a single view of capacity, demand, engagement budgets, and delivery performance – enabling teams to plan work from the same real-time data and quantify the financial impact of staffing decisions.

“Dayshape joined up our resource management and our finance function so they could talk to one another.”

The impact

Forecast accuracy improved

Forecast variance dropped to below 0.5%.

By connecting workforce planning with financial data, the firm could track engagement performance in real time and adjust staffing decisions before variances developed.

“The variance between forecasts and actuals fell to below 0.5%. Tiny variances. We actually found the finance system was more wrong than the Dayshape system.”

Margin discipline strengthened

Profitability improved within the year.

Staffing decisions now took place with real-time visibility of financial impact. Engagement teams could see how resource decisions affected revenue, cost, and margin before work was delivered.

“Dayshape gave us the ability to question budgets in real time and make sure engagement leads were having the right conversations on fees. We could now see exactly where the problems were and understand the scale of them.”

“Flattening the demand curve meant suddenly we were profitable by the end of the year.”

Workload pressure reduced

Attrition fell to 12 percent and workload pressure eased.

Firm-wide visibility into utilization, capacity, and engagement demand allowed resource leaders to rebalance workloads earlier and identify where additional staffing was required.

“We took more than 50 hours per engagement out of the upcoming busy season workload. A significant contribution to wellbeing.”

“We went from somewhere where people felt continually overworked and not listened to, to one where people felt supported more than anywhere else in the market.”

With that foundation in place, the firm was ready to embed AI directly into the allocation process.

Activating Dayshape Advise

The firm piloted Dayshape Advise in live allocation workflows, selecting graduate portfolio allocation as its initial AI use case – high volume, high complexity, and multiple engagements competing for capacity.

Embedding AI into the allocation process

Dayshape Advise generates real-time allocation recommendations using connected workforce and engagement data. The AI evaluates thousands of potential staffing combinations across skills, availability, grade, engagement budgets, workload balance, and portfolio priorities – surfacing best-fit staffing options for each engagement in seconds.

Resource managers remain in control, reviewing, adjusting, and approving recommendations before allocations are confirmed.

The system also enables resource managers to bulk allocate work across multiple engagements, dramatically reducing the time required to build and adjust schedules across the portfolio.

The result:

Early production feedback validated allocation quality and usability:

• Functionality rated 4–5 out of 5
• Recommendations rated "very good"
• 80% of allocations accepted outright; the remainder resolved in minutes, not days
• Work distributed evenly

The pilot delivered the confidence and operational proof required to scale.

Dayshape Advise was enabled across all resource managers within the audit practice – moving AI from experiment to embedded capability.

Scaling AI-powered resourcing

For a firm operating across thousands of professionals and multinational audits, AI allocation amplifies human judgment. Administrative load falls. Allocation decisions accelerate. Workload consistency improves. Commercial conversations strengthen.

As the Partner noted:

“If the finance system, the scheduling system and the auditing system all speak to one another, suddenly the power to optimize your deployment is much greater.”

Integrated systems unlocked AI-powered allocation at scale – including cross-border deployment.

“Being on the same system across Europe meant we could deploy people at scale for the first time.”

Defining the future operating model

For this Big Four audit practice, AI-powered resource management is no longer a pilot – it sits at the center of how the firm plans, deploys, and performs financially.

It started with visibility.
Visibility created control.
Control strengthened performance.
Performance protected margin and long-term financial sustainability.

Now, Dayshape's AI scales that capability across the firm.

“We are a resource management business at heart. And as a business, that is where we make our money.”

For firms managing scale and complexity, resource management has always been foundational to commercial performance. Now, elevated and accelerated by AI, it is unlocking new levels of operational performance and defining the future operating model for professional services firms.