December 19, 2025

SOX Automation: How to Improve Audit Compliance with AI

Deirdre Dolan

Sr. Director of Product Marketing

Increasing trust with AI for audit and advisory firms.

Manual SOX compliance processes are increasingly difficult to scale as audit complexity, control populations, and documentation requirements continue to grow. According to KPMG's 2025 SOX Survey, organizations now spend an average of $2.3 million annually on SOX compliance, with 45% reporting year-over-year cost increases driven by expanding system complexity and evolving PCAOB requirements.

Audit and advisory firms managing these engagements absorb significant portions of this burden through labor-intensive testing, documentation, and evidence collection that stretches staff capacity while limiting profitable growth opportunities.

Engagement automation platforms powered by agentic AI help audit and advisory firms execute substantive testing procedures more efficiently, handle larger control populations without proportional staff increases, and reallocate hours from routine documentation to higher-value advisory services. The shift demands fundamental process redesign, data standardization, and careful attention to external audit acceptance criteria.

This article examines how audit and advisory firms can implement engagement automation for SOX compliance effectively, the documented efficiency improvements and cost reductions achieved, and practical workflows for AI-driven compliance.

What is SOX automation?

Engagement automation for SOX compliance represents the technology-enabled transition from manual, periodic control testing to AI-assisted testing workflows that execute procedures within practitioner-defined parameters. Instead of auditors manually selecting samples, requesting evidence, matching documentation to control requirements, and documenting findings across disconnected systems, automated platforms accelerate these repetitive steps while practitioners retain control over methodology, review, and final judgments.

The fundamental shift moves auditor time away from administrative tasks toward higher-value activities. Traditional approaches require practitioners to download files, organize folders, track versions across team members, email status updates, and manually compile evidence for each control test. AI-assisted approaches centralize these workflows within a single platform where practitioners can access real-time engagement status, track evidence requests, and review AI-generated findings without switching between disconnected systems.

This doesn't eliminate auditor involvement: it refocuses professional expertise on control design, risk assessment, stakeholder engagement, and judgment-intensive evaluations. Roles evolve as practitioners establish parameters and review AI-generated findings rather than performing every procedural step manually. The distinction matters for audit and advisory firms evaluating adoption: automation assists practitioners by executing defined workflows within parameters professionals establish, rather than replacing the judgment that defines audit quality.

How does SOX automation work?

The transition from manual to automated workflows happens through integrated platform components rather than point solutions. Comprehensive engagement automation platforms integrate multiple workflow components that replace the fragmented spreadsheet-email-shared drive architectures most audit and advisory firms currently manage:

Client request management: Centralized tracking of evidence requests, responses, and follow-ups across engagements
Evidence collection workflows: Streamlined, practitioner-initiated collection and centralized organization of supporting documentation from client systems.
Controls testing: AI-powered execution of test procedures within practitioner-defined parameters
Workpaper documentation: Structured documentation with version control and real-time collaboration
Report generation: Streamlined report creation requiring practitioner review and approval

These integrated components eliminate the disconnected workflows that currently force Managers to spend hours manually compiling engagement status reports before they can update Partners on where each engagement actually stands.

For Partners handling multiple concurrent engagements, this consolidation provides real-time visibility into engagement status, outstanding evidence requests, and testing completion rates that manual processes obscure until Managers compile status reports. The operational difference is substantial: instead of waiting days for a Manager to manually aggregate status across five SOX engagements, Partners access dashboards showing exactly which controls have complete testing, which evidence requests remain outstanding, and where bottlenecks threaten realization targets.

Compliance and SOX automation

External auditors and regulators haven't provided blanket approval for AI-driven SOX compliance, creating implementation complexity. Audit and advisory firms must carefully document AI methodologies, maintain evidence of human oversight, and design approaches that withstand external audit scrutiny. The PCAOB's 2024 standards addressing technology-assisted analysis provide regulatory guidance supporting automation while establishing documentation expectations. This regulatory framework matters: firms can't simply deploy AI and assume compliance. Every automated workflow requires documentation showing how practitioners established parameters, how the AI executed procedures, and where human judgment reviewed results.

Why audit and advisory firms should automate SOX compliance

The business case for engagement automation rests on three quantifiable dimensions: direct cost reduction, capacity expansion that supports revenue growth, and competitive positioning as client expectations shift toward technology-enabled service delivery.

Cost reduction

Audit and advisory firms implementing automation reallocate staff hours from routine testing to premium-priced advisory services rather than reducing fees proportionally. The economics are straightforward: when automation handles repetitive control testing, practitioners have capacity for consulting engagements that command higher rates than compliance work. This matters particularly for Partners managing profitability targets, where realization rates directly impact compensation.

The financial impact breaks down across three key areas:

Per-control savings: According to research from KPMG, each control automated eliminates approximately 12 hours annually through reduced redundant testing, streamlined evidence gathering, and automated documentation. For a firm managing 200 controls across a SOC 2 or SOX engagement, that's 2,400 hours, which is effectively 1.2 full-time equivalents reallocated from manual reconciliation to client-facing advisory work.
Fee optimization: Those automating at least 25% of internal controls achieve 27% lower fees compared to peers relying entirely on manual processes. For audit and advisory firms, this efficiency doesn't necessarily translate to fee reductions. Instead, firms maintain competitive pricing while improving margins through reduced labor costs.
Multi-year returns: Firms integrating engagement management, document control, testing automation, and reporting can achieve strong multi-year returns, with results varying based on implementation scope, data readiness, and firm size.

The margin improvement extends beyond direct labor savings. Automated platforms reduce project overruns that erode realization. When Managers have real-time visibility into outstanding requests and testing completion, they identify problems while there's still time to address them rather than discovering budget overruns during final review. This predictability matters for Partner compensation tied to engagement profitability.

Platforms delivering these efficiency gains share common architectural characteristics. Fieldguide's engagement automation platform illustrates how these capabilities work in practice. Fieldguide provides agents that automate the execution of defined testing tasks and surface analysis to support practitioners within a practitioner-in-the-loop workflow. Agents handle routine activities such as evidence collection, data extraction, and execution of practitioner-defined procedures, while all findings and conclusions remain subject to practitioner review and final sign-off.

Capacity expansion

Automation breaks the talent shortage constraint by expanding what current staff can handle without proportional headcount growth. Audit and advisory firms can't hire enough qualified staff to handle demand, forcing them to decline profitable engagements or overextend existing teams to burnout levels. AI-assisted workflows change this equation by letting practitioners accomplish more with existing resources.

The capacity multiplication effect is measurable. Professionals using generative AI effectively add 21% more billable hours to their capacity by reallocating roughly 3.5 hours per week from routine data entry to high-value tasks requiring professional judgment. That additional capacity compounds across an entire practice: a 20-person risk advisory team gains the equivalent of four additional professionals without hiring, recruiting, or training costs.

The value proposition varies significantly depending on where practitioners sit in the firm hierarchy. Each level experiences distinct efficiency gains that compound to create firm-wide capacity expansion:

Partners: Partners handling 3-7 engagements simultaneously gain hours back for business development and client relationship building that directly impacts their book of business. Real-time engagement dashboards replace the hours previously spent requesting status updates from Managers, letting Partners identify bottlenecks before they affect profitability.
Managers: Managers spend less time updating spreadsheets and more time reviewing substantive work that requires their expertise. Rather than compiling evidence from email chains and shared drives, they access centralized repositories where AI has matched documentation to control requirements within the parameters they established.
Associates: Associates studying for their CPA exams eliminate tedious reconciliation work. Autonomous AI agents execute the repetitive testing procedures that previously required manually downloading PDFs, copying data into Excel, and reformatting reports.

These role-specific benefits create a multiplier effect across the entire firm, where efficiency gains at every level compound to dramatically expand overall capacity.

Market positioning

Client expectations have shifted as organizations implement their own automation and expect audit and advisory firms to match that technological sophistication rather than arriving with clipboards and spreadsheets. Partners competing in RFPs find that demonstrating AI-powered testing capabilities differentiates proposals in ways fee reductions alone cannot.

The adoption curve is accelerating rapidly. According to The IIA 2025 Survey, GenAI adoption among Chief Audit Executives more than doubled from 15% to 40% year-over-year. Audit and advisory firms delaying investment may face competitive disadvantage as leading firms demonstrate operational efficiency advantages and evolving client expectations.

The PCAOB has characterized AI technologies as potentially serving as "a catalyst for" improved audit quality according to Board Member remarks. This regulatory endorsement signals that automation adoption is increasingly viewed as essential to maintaining audit quality standards as transaction volumes and complexity increase beyond what manual testing can reliably handle.

Building automation capabilities in your practice

Audit and advisory firms implementing engagement automation for SOX compliance achieve documented efficiency gains while expanding capacity without proportional headcount increases. The transition requires careful attention to external audit acceptance, data standardization, and fundamental process redesign. Firms that successfully adopt automation gain competitive advantages in both operational efficiency and client perception, differentiating themselves in competitive RFPs through demonstrated technological sophistication.

The strategic advantage extends beyond individual engagements. As Chief Audit Executives increasingly adopt AI technologies and client expectations shift toward technology-enabled service delivery, automation capability becomes a qualification threshold rather than a differentiator. Firms positioning automation as optional risk finding themselves behind both competitive and regulatory expectations.

Fieldguide’s engagement automation platform supports audit and advisory firms across the engagement lifecycle by centralizing requests, documentation, testing workflows, and review processes within governed, practitioner-led workflows. Verified implementations show 5X practice growth and 30-50% efficiency gains while maintaining audit quality standards.