Consultants Using AI Complete 12% More Tasks and Finish 25% Faster. GTA Firms Billing by the Hour Should Pay Attention.

AI for professional services refers to AI agents and tools configured to handle the non-billable operational work that drags utilization below target in consulting, advisory, and accounting firms. For GTA firms billing by the hour, the business case centers on converting administrative overhead — proposal drafting, client intake, research compilation, time entry — back to billable capacity without adding headcount.

Harvard Business School and Boston Consulting Group ran one of the largest controlled experiments on AI and knowledge work ever conducted. They gave 758 BCG consultants access to GPT-4 (Harvard Business School) and measured what happened. Consultants using AI completed 12.2% more tasks, finished 25.1% faster, and produced results that were 40% higher in quality compared to those working without AI. Consultants who previously scored below average improved their output by 43%.

That study was published in 2023. Since then, McKinsey rolled out its internal AI platform Lilli firmwide. McKinsey reports that 72 percent of the firm is active on it, with colleagues reporting up to 30 percent time savings in searching and synthesizing knowledge (McKinsey).

BCG followed with Deckster, which reviews and polishes client presentations against senior-partner standards.

The Big Four have noticed. Graduate hiring intakes across the UK branches of the Big Four dropped by 6% to 30% in the past two years, as firms determined that AI tools can handle many tasks previously assigned to junior analysts. (McKinsey, via Future of Consulting)

This is not a future scenario. This is the operating reality at the firms GTA professional services companies compete against for talent, clients, and margin.

The Utilization Problem That AI Solves

Professional services firms live and die by billable utilization. The industry target is 70% to 80% — meaning seven or eight out of every ten working hours generate revenue. In practice, the global average fell to 68.9% in 2024 and the trend was downward, on SPI Research's professional-services benchmark (SPI Research).

The gap between target and reality is not laziness. It is structural. Global average billable utilization across professional services was 68.9% in 2024, down from a 73.2% high in 2021, against the 75% SPI considers optimal (SPI Research; Deltek, reporting SPI's benchmark) — so roughly a third of available hours are not billable.

Work it as a model. For a consulting firm billing at $200 per hour, each percentage point of utilization is worth roughly $400,000 a year at a mid-sized firm, so a six-point move is around $2.4 million in recovered billable capacity. Substitute your own rate and headcount — the arithmetic holds, the numbers are yours. The math is simple. The execution is where most firms stall.

The non-billable hours that drag utilization down follow predictable patterns. Proposal drafting. Client intake documentation. Meeting summaries. Status reporting. Research compilation. Knowledge retrieval from past projects. These are the tasks that AI handles well — not the strategic advisory work that justifies premium billing rates, but the administrative scaffolding around it.

Where AI Delivers Returns for Professional Services

Four areas consistently produce measurable results for GTA consulting, advisory, and accounting firms.

Proposal generation is the most immediate win. Drafting is the step AI compresses hardest, turning days of writing into hours of review and refinement, and RFP requirement extraction goes from a manual read-through to near-instantaneous. We have not found a published figure for how much time that saves across firms, so measure your own cycle before and after rather than trusting a vendor number. What it displaces is senior billable time on non-billable activity.

Client intake and document processing is the second area. Intake that runs on structured questionnaires, document collection and routing is largely rule-based work, and it is the first thing an agent absorbs. Vendor write-ups report large reductions in intake and onboarding time, without publishing the sample behind them (SmartDev).

Research and knowledge synthesis is the third. McKinsey's Lilli scans 100,000-plus internal documents in seconds and surfaces relevant precedents, frameworks, and data points that would take a human analyst hours to locate. For mid-market GTA firms without McKinsey's proprietary tools, AI agents can be configured to perform the same function across a firm's own document repository, CRM history, and project archives.

Internal operations represent the fourth category. A Grant Thornton study on Microsoft 365 Copilot deployment found an average of 7.5 hours saved per employee per week in knowledge-work contexts. (SmartDev) Osborne Clarke's AI-powered time capture pilot recovered 1.5 additional billable hours per user per week — time that was previously lost to incomplete tracking. (SmartDev)

Why GTA Firms Face This Sooner Than They Think

Toronto's professional services concentration is unusually high. Ontario's professional, scientific and technical services industry accounts for 59.7% of the province's professional workforce, representing 13.6% of total Toronto employment, and the sector grew 7.5% in 2024. (Job Bank Canada)

That density creates competitive pressure. When one firm in a market this concentrated adopts AI and improves utilization, client expectations shift. Response times compress. Proposal quality rises. Research depth increases. Competing firms do not get to choose whether AI changes their market — they only get to choose whether they adopt before or after their competitors. A Fractional AI Officer__ brings the strategy and coordination to make that choice work. Most firms should book a readiness assessment__ first.

In Statistics Canada's Q2 2026 data, AI use in Canada's professional, scientific and technical services sector reached 32.4% — third across all industries, behind information and cultural industries (42.3%) and finance and insurance (40.4%) (Statistics Canada). That is up from 30.6% in Q2 2025. Across all Canadian businesses, AI use tripled in two years, from 6.1% in Q2 2024 to 19.2% in Q2 2026 (Statistics Canada).

The firms moving fastest are not necessarily the largest. The Harvard/BCG experiment showed that below-average performers gained the most from AI — a 43% improvement, compared to 17% for those above average (Harvard Business School / BCG). For mid-market GTA firms competing against Big Four offices with enterprise AI budgets, that finding matters. AI closes the capability gap from the bottom up.

What the Big Four Are Doing — and What It Means for Everyone Else

This is not replacing consultants. It is changing what a consultant's hour is worth. When an associate at a Big Four firm spends two hours on research that AI could complete in five minutes, the firm is paying associate rates for work that produces near-zero marginal value. The firms that recognized this first cut junior hiring and redirected those roles toward AI-augmented workflows.

For GTA firms in the $500K to $50M revenue range, the implication is different but equally significant. These firms cannot afford to maintain a bench of analysts for research and slide work. But they also cannot afford to have $300-per-hour partners spending 30% of their time on non-billable administrative tasks. AI agents handle the administrative layer — proposal first drafts, meeting summarization, client intake processing, internal knowledge retrieval — so that every human hour goes toward the advisory work clients actually pay for.

PwC's 2025 Global AI Jobs Barometer, built on an analysis of close to a billion job postings, found the wage premium for AI skills rose to 56%, up from 25% the year before (PwC). The market is pricing AI capability into professional services — not as a novelty, but as an expected standard.

What This Looks Like in Practice

Worked example (modelled, not measured): take a hypothetical management consulting firm in Mississauga that processes 40 proposals per quarter. Each proposal takes 8 to 12 hours of non-billable time across research, drafting, formatting, and internal review. That is 320 to 480 hours per quarter spent on work no client is invoiced for.

An AI agent configured for that firm's proposal workflow handles the first draft, extracts requirements from RFPs, pulls relevant case studies from the firm's project archive, and formats the output to match brand standards. The human role shifts from writing to reviewing and approving. If cycle time drops from days to hours, most of those 320 to 480 hours could convert back to billable capacity.

Apply the same logic to client intake documentation, meeting transcription and summarization, competitive research, and internal knowledge management, and the utilization impact compounds. A firm that recovers even five billable hours per consultant per week at $200 per hour adds $1,000 per consultant per week in recovered capacity — $52,000 per consultant per year.

DeployLabs builds AI agents for professional services firms across the GTA. Not off-the-shelf software that requires your team to learn another platform — coordinated AI systems that integrate with your existing tools, operate on your data, and execute the repetitive workflows that are dragging your utilization below target. The engagement starts with a $2,500 AI readiness assessment — a structured evaluation of where AI delivers the highest return for your specific operation, credited in full toward any build. Custom systems run $7,500 to $15,000 per agent for a single workflow, fixed price, scoped in the assessment, with 60 days of monitoring and tuning included, followed by an optional care plan from $500/month, month-to-month, cancel anytime. Complex, multi-system workflows run up to $30,000.

Book a discovery call to see where your firm's non-billable hours are hiding recoverable revenue Before committing, understand AI implementation costs__.