Matt Hillary, CISO, Drata, says organizations that successfully navigate the evolving GRC landscape will be better positioned not just to comply with regulations but to gain a competitive edge in an increasingly complex business environment.
As organizations face growing regulatory complexities and heightened security demands, the Governance, Risk and Compliance (GRC) landscape is rapidly evolving. The confluence of new technologies, such as AI alongside shifting regulatory frameworks is reshaping how businesses approach risk management and compliance. In this dynamic environment, organizations that adapt quickly and effectively will be best positioned to succeed in 2025 and beyond.
The Key Drivers of Change in GRC
The GRC landscape is being transformed by several key factors:
AI and Automation: These technologies are streamlining GRC processes and reducing the burdens on professionals.
Increasing Regulatory Complexity: Organizations must navigate an ever-changing and expanding web of compliance requirements.
Evolving Risk Management Needs: Businesses need more sophisticated, data-driven strategies to stay ahead of potential threats.
As organizations grapple with these challenges, they must embrace the tools and strategies that will help them manage their risk profiles and ensure compliance in the years ahead.
AI’s role in GRC is poised for significant growth, with the ultimate goal being the development of agentic AI – autonomous systems that can independently manage key GRC tasks. In the coming years, AI is expected to drive improvements in several areas:
Risk Assessment: AI will enable more accurate and dynamic assessments of risks, transitioning from subjective evaluations to objective, data-driven predictions. By analyzing historical data, AI models can predict risks before they materialize – helping businesses address potential threats proactively.
Evidence Collection and Auditing: AI will automate the evidence collection process for audits, significantly reducing the manual effort required. Well-trained AI will streamline compliance monitoring, offering real-time insights and even conducting internal audits autonomously.
Despite these advancements, organizations will need to remain vigilant about the ethical and privacy implications of AI. Ensuring that AI systems remain unbiased and transparent will require ongoing human oversight.
Shifting Risk Management Winds
The integration of AI and other advanced technologies will usher in a new era of quantitative risk analysis. Here are some key shifts in risk management expected in the coming years:
Data-Driven Risk Assessments: More organizations will adopt quantitative approaches, allowing for better risk prioritization based on real-time data and business context. This will help organizations address both controllable and uncontrollable risks more effectively.
Integration of External Data: Risk assessments will increasingly incorporate diverse data sources – such as threat intelligence, economic indicators, and geopolitical events – providing a more comprehensive view of potential risks.
Dynamic Risk Adjustments: With real-time data, organizations will be able to continuously adjust their risk strategies, enabling them to respond more quickly to shifting conditions.
As organizations balance the pursuit of innovation with risk management, AI’s ability to quantify and prioritize risks will help guide decision-making. Businesses will have to ask whether it’s more beneficial to invest in risk mitigation or seize opportunities for growth.
A More Holistic Approach to Risk Management
As security, compliance and privacy functions become more intertwined, organizations will need to adopt a more holistic approach to risk management. This convergence is driven by shared objectives – reducing risk across multiple domains – and heightened regulatory pressures. The siloed approach to these disciplines will become less effective, and organizations will need to foster greater collaboration among teams.
To meet these challenges, businesses must invest in technology, training, and cross-functional collaboration. By breaking down barriers between security, privacy, and compliance functions, organizations can create more robust and efficient risk management strategies.
The Evolution of Third-Party Risk Management
AI is already helping organizations streamline third-party risk management processes, such as vendor evaluations and compliance assessments. In the future, AI will further enhance this area by enabling:
Faster Vendor Assessments: AI will automate and expedite the vetting of third-party organizations, improving risk assessments and reducing reliance on manual reviews.
Dynamic Risk Monitoring: Organizations will be able to monitor third-party risks in real time, making adjustments as needed based on evolving conditions.
The ultimate goal is to integrate third-party risk management into broader GRC platforms, using AI to create a more seamless and efficient process.
Preparing for the GRC Future: A Strategic Approach
As we enter 2025, it’s clear that GRC will undergo a major transformation. Organizations must be proactive in embracing automation, investing in AI capabilities and fostering a culture of continuous adaptation. By focusing on data-driven decision-making, collaboration, and technology adoption, businesses will be better equipped to meet the challenges ahead.
Those organizations that successfully navigate the evolving GRC landscape will be better positioned not just to comply with regulations but to gain a competitive edge in an increasingly complex business environment.
