The Role of AI in Transforming GRC Practices

Key Takeaways

• AI is transforming GRC: Automation of audits, risk assessments, and third-party reviews is enabling a shift from reactive to proactive risk management.
• Certa’s AI agents streamline operations: Data, Risk, and Adjudicate agents reduce manual workloads, identify hidden risks, and adjudicate low-risk cases to free up strategic capacity.
• Data governance is critical: Poor-quality or biased data can undermine AI accuracy and create ethical or compliance risks without proper controls.
• Generative AI is a double-edged sword: While enabling plain-language insights, it also introduces risks like bias, flawed recommendations, and privacy breaches.
• Regulatory pressure is growing: Emerging laws like the EU AI Act require organizations to build explainable, transparent, and compliant AI systems.

Deep Dive

As the world becomes more interconnected and regulatory frameworks grow in complexity, organizations are under increasing pressure to manage risks effectively while remaining compliant. The role of artificial intelligence (AI) in Governance, Risk, and Compliance (GRC) is evolving rapidly, offering promising solutions to enhance decision-making, automate repetitive tasks, and ensure compliance across various business functions. While the integration of AI into GRC tools provides unprecedented efficiency, it also introduces challenges that organizations must carefully navigate.

Over the past decade, AI has emerged as a powerful tool within GRC, transforming how organizations approach risk and compliance management. This is largely attributed to AI’s ability to automate complex and repetitive tasks, such as compliance audits, risk assessments, and data processing.

One of the most recent examples would be platforms like Certa’s new integrated AI-driven agents designed to streamline and automate third-party risk management workflows. These Data, Risk, and Adjudicate agents are designed to reduce the time spent on manual, resource-intensive tasks. By automating the intake of information, identifying risks hidden within documents, and adjudicating low-risk cases autonomously, these AI agents allow GRC professionals to focus on more strategic, high-level decision-making.

However, AI’s potential extends beyond merely automating tasks. The ability of AI to analyze vast amounts of data, uncover hidden patterns, and make real-time decisions is helping organizations move from reactive to proactive risk management. This shift not only improves operational efficiency but also enhances the ability to anticipate risks before they materialize. AI agents, such as Certa’s, further support this shift towards proactive risk management by automating critical workflows, like the adjudication of low-risk cases, which frees up resources for more strategic decision-making. These agents are also designed to adapt and learn, continually improving their efficiency as they process more data and interactions.

The Promise of AI: Efficiency, Accuracy, and Scalability

AI-driven GRC systems promise to streamline operations in ways that were previously unimaginable. As organizations scale, the volume of data they must process grows exponentially, making traditional risk management methods increasingly inefficient and outdated. AI provides an effective solution to this problem by automating data entry, conducting continuous monitoring, and performing deep analysis. AI-driven tools like Certa’s Risk and Adjudicate agents are at the forefront of this transformation. By automating tasks such as compliance assessments and third-party risk evaluations, these tools help organizations scale their operations while maintaining accuracy and ensuring that high-risk areas are quickly identified and addressed.

One significant benefit of AI in GRC is the efficiency gains it offers. According to McKinsey, up to 70% of an employee’s time can be spent on tasks that could be automated with AI. By removing the need for employees to perform routine administrative tasks, AI allows teams to focus on more critical, value-added activities. AI tools like can automate data entry, pulling from internal policies, contracts, and third-party documents. This not only reduces human error but also accelerates the intake process, allowing GRC teams to act more quickly.

Furthermore, AI-powered systems enable 360° visibility of all third-party relationships in real time, providing comprehensive insights into risk profiles, compliance status, and contract engagements. This visibility is crucial for organizations to stay on top of regulatory changes, track third-party performance, and make timely, informed decisions.

The Ethical and Legal Considerations: Ensuring Responsible AI Use

Despite the clear advantages, the adoption of AI in GRC comes with inherent risks. As AI systems increasingly influence decision-making, businesses must remain vigilant about the ethical and legal implications of their use. One major concern is data quality and governance. AI systems are only as reliable as the data they consume. Poor or biased data can lead to inaccurate insights, which may result in misidentifying risks, favoring certain third parties, or missing key compliance issues.

Risk Agents, which analyzes contracts and documents for potential risks, relies on comprehensive data sources to function effectively. If the data provided to this agent is incomplete or biased, the AI may make incorrect recommendations, which could have significant compliance and reputational consequences. To mitigate this risk, businesses must implement strong data governance practices, ensuring that the data used for training AI systems is accurate, complete, and free from biases.

Another critical issue is data privacy. AI tools require large datasets to function effectively, and many of these datasets contain sensitive information, such as contracts, third-party communications, and transaction data. If these AI systems are not properly secured, there is a risk that this confidential data could be exposed or misused, resulting in significant compliance breaches and cybersecurity threats.

Generative AI: A Double-Edged Sword

The emergence of generative AI, like GPT models, presents another exciting opportunity and challenge in GRC. With the ability to generate content and analyze data through Natural Language Processing (NLP), generative AI allows GRC professionals to interact with systems using plain language. Businesses can query their AI tools, asking questions like, “What social media content resonates most with our target demographic?” or “Which third parties pose the highest risk based on our latest contracts?”

While these capabilities offer significant potential for increased productivity, they also carry risks. AI has the potential to automate tasks that currently consume an employee’s time, but improper use of generative AI could lead to inaccurate decision-making, flawed recommendations, or exposure of sensitive data. Without proper safeguards, generative AI could unintentionally perpetuate biases, process faulty data, or create privacy concerns.

Moreover, businesses must adopt measures to ensure AI explainability. As AI continues to take on more decision-making responsibilities, it’s essential for organizations to maintain transparency in the processes by which AI systems generate insights. Ensuring that AI systems are auditable and their decisions are easily explainable will be crucial for fostering trust and maintaining regulatory compliance.

AI Regulation: Preparing for an Evolving Legal Landscape

The regulatory landscape surrounding AI is still in development, but it’s clear that AI adoption will need to be carefully managed to comply with both existing and forthcoming regulations. The EU’s Artificial Intelligence Act is one of the first regulatory frameworks that categorizes AI systems based on their risk levels. AI applications deemed high-risk, such as those used in critical infrastructure or employment, are subject to more stringent requirements, including risk assessments, transparency obligations, and robust data governance practices.

As AI adoption in GRC continues to grow, compliance officers will need to collaborate with senior management and IT departments to ensure that their AI tools comply with current and future laws. Proactively engaging with regulatory bodies and maintaining strong internal controls will be essential for navigating the evolving legal landscape.

The key to successful AI adoption in GRC will be collaboration. AI will handle the routine and repetitive, but humans will still steer the ship, ensuring ethical considerations, regulatory compliance, and strategic decision-making are at the heart of risk management.

For businesses to maximize the benefits of AI while mitigating the risks, they must prioritize data governance, AI transparency, and ethical considerations. By doing so, organizations can ensure that AI becomes a tool for not just improved efficiency, but also more robust, agile, and ethical risk management.

In the end, the integration of AI in GRC is about enhancing human capabilities. The businesses that can strike the right balance between AI innovation and human oversight will be best positioned to thrive in the increasingly complex world of governance, risk, and compliance.

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