How AI-Powered GRC Is Transforming Controls Compliance

For years, building or refreshing an internal control program required thousands of hours of documentation, interviews, and testing support. External consultants often led execution, while internal teams struggled to maintain momentum once the engagement ended.

Workiva has introduced AI-powered GRC, a technology-enabled approach to governance, risk, and compliance, on its unified platform for finance, sustainability, and audit. Citrin Cooperman estimates that controls management, one of three new solutions, enables organizations to reduce the time of building controls programs by as much as 50 percent. Audit, risk, and controls functions that once depended on sprawling spreadsheets, static documentation, and manual walkthroughs are now being reshaped by AI-powered automation and workflows.

Enterprise adoption of AI is surging across industries as organizations seek measurable business impact from automation, efficiency gains, and process optimization. According to Workiva’s 2026 Executive Benchmark Survey, 91% of organizations report that AI has improved the timeliness and strategic value of financial decisions. The research also indicates that organizations are increasingly embedding automation and AI within reporting, governance, and compliance workflows rather than treating them as isolated initiatives. This shift signals that AI is becoming integrated into core operational processes, including governance, risk, and compliance.

AI-powered GRC reflects that momentum. It transforms historically time-intensive tasks such as control documentation, walkthroughs, testing, and remediation tracking into guided, scalable processes. The result is not simply faster execution, but a redefinition of how internal teams and external advisors collaborate.

From Manual Execution to Technology-Enabled Oversight

Traditional Model

• Manual documentation and testing
• Heavy external consultant execution
• Long timelines, high fees
• Bespoke programs, limited standardization

AI-powered GRC Model

• AI-enabled documentation and testing
• Internal teams execute; advisors review and validate
• Faster time to value, lower external spend
• Standardized, scalable, auditable programs

The traditional approach to building and maintaining controls programs relied heavily on manual documentation, consultant-led execution, and lengthy implementation timelines.

• AI-powered GRC introduces a different model
• AI-powered documentation and walkthrough conversion that reduces manual drafting time
• Embedded testing workflows that compress annual testing cycles
• Standardized risk and control libraries that promote consistency
• Role-based oversight that shifts advisors toward validation and quality assurance

In traditional builds, organizations could spend millions of dollars and up to two years standing up a SOX 404(b) ready controls program. With AI-supported automation, that timeline can be drastically accelerated, and external spend can be significantly reduced as advisors move from preparers to reviewers.

According to Scott Freinberg, Partner, Citrin Cooperman Advisors LLC, “There was a lot of buzz surrounding AI at the recent IIA GAM Conference. Not only were auditors discussing potential efficiencies, but they were also discussing greater assurance gained by leveraging AI models. There is a push towards letting technology perform a lot of the work and having auditor roles focus on quality assurance and review.”

The implications extend beyond cost savings. When documentation and testing follow standardized, system-driven processes, programs become easier to scale, audit, and sustain over time.

The Elevated Role of Risk Leaders and Their Advisors in an AI-Powered GRC Model

Modern GRC transformation is not just about efficiency; it represents a structural shift in how organizations view risk leadership.

Historically, audit and risk teams were consumed by documentation cycles and annual testing calendars. AI-powered platforms compress those timelines, freeing capacity for analysis, prioritization, and forward-looking risk oversight. This shift is critical, as it elevates the role of internal audit, providing the clear, real-time data executives and board-level audit committees need to accelerate strategic decision making. Workiva’s 2026 Executive Benchmark Survey reinforces this transition, showing that executive leaders view automation and data governance as essential to strengthening reporting confidence and organizational resilience. AI adoption is no longer experimental; it is increasingly operationalized within finance, risk, and compliance functions.

This broad adoption marks a transition from isolated pilots to AI as a work-integrated tool. But the same research also underscores that using AI doesn’t automatically translate into enterprise-level business impact until organizations redesign workflows and embed governance around its use. That’s where Workiva’s AI-powered GRC stands out; its auditor-trusted AI is embedded into core GRC processes and workflows, not added on later.

As execution becomes more efficient, expectations intensify. Risk leaders are increasingly asked to:

• Provide clearer visibility into emerging risks
• Align controls with enterprise growth initiatives
• Deliver board-ready reporting with greater speed
• Demonstrate measurable return on governance investments

AI-powered GRC provides a platform for risk leaders to expand their role and strategic influence, and advisory support must advance as this internal role reaches new heights. The focus shifts from drafting documentation to validating structure, ensuring AI-enabled programs are consistent, scalable, and defensible.

Advisors like the professionals at Citrin Cooperman now serve as quality stewards, reviewing automated documentation, evaluating control rationalization decisions, and reinforcing alignment with audit expectations. This discipline becomes especially important as organizations rely more heavily on standardized, technology-driven control environments.

From Execution Support to Strategic Validation

AI-powered GRC introduces efficiencies that materially change cost structures. Traditional control program builds could span more than a year and require substantial external spend. AI-powered documentation and testing compress timelines and reduce preparation-related fees.

Lower execution effort, however, does not eliminate governance risk; it concentrates it in design and oversight.

Organizations that adopt automation without structured validation may gain speed but lose alignment. Those that combine technology with disciplined advisory review gain both efficiency and confidence. External consulting shifts toward targeted validation and quality assurance, resulting in cost savings while strengthening program integrity. This model also accelerates the maturity of internal control. With less time spent drafting narratives, teams can focus earlier on optimization, risk prioritization, and continuous improvement.

AI-powered GRC makes modernization attainable. Advisory discipline makes it resilient.

These shifts in execution, oversight, and advisory roles are being enabled by new AI-powered capabilities across the core pillars of governance, risk, and compliance: controls, audit, and risk management.

Key Capabilities of AI-Powered Workiva GRC

With Controls Management, you can:

• Conduct testing, certifications, and ownership in a centralized, audit-ready control environment
• Perform ongoing control evaluations and monitor the performance of controls in real-time
• Leverage AI to generate control performance steps, analyze sample evidence, and create flowcharts from existing documentation

With Audit Management, you can:

• Manage a centralized audit universe with risk scores and planning inputs
• Gain full visibility with end-to-end task management and real-time dashboards
• Leverage AI to generate controls, identify issue patterns, and analyze sample evidence

With Risk Management, you can:

• Maintain a centralized enterprise risk register and build a connected view of risk across the organization
• Record risk interviews to build productive and collaborative business relationships
• Leverage AI-powered insights that summarize and enhance your interactions with functional leaders and risk owners

For more details on these capabilities, read Workiva’s recent announcement.

Together, these capabilities help organizations move from manual control program execution to a more scalable, technology-enabled governance model.

Sustaining Confidence with AI-powered GRC

The introduction of AI-Powered GRC signals that governance technology has entered a more advanced phase. Automation and embedded intelligence have moved from experimental to operational.

The differentiator is not whether AI is adopted, but whether it’s guided with precision.

Citrin Cooperman’s Digital and Cloud Services Practice has supported numerous control environments across industries and maturity levels with Workiva Solutions. Working alongside AI-powered capabilities, our firm applies practical insight to ensure AI-generated outputs translate into audit-ready documentation, durable control structures, and sustainable governance value.

If your business is evaluating whether your GRC environment is positioned for this next era, request a meeting with Scott Freinberg and the dedicated GRC Workiva Solutions team at Citrin Cooperman.