The landscape of corporate compliance is undergoing a profound transformation, with a significant portion of compliance leaders anticipating a shift from traditional oversight to strategic advisory roles. Recent surveys reveal a growing expectation among compliance professionals to influence company strategy, driven by the accelerating integration of technology and artificial intelligence (AI) across business operations. This evolution signifies a move towards proactive risk management and value creation, moving beyond mere regulatory adherence.
The Evolving Compliance Function: From Gatekeeper to Strategist
A comprehensive survey conducted by MCO (MyComplianceOffice) involving 370 director-level and C-suite compliance leaders indicates a strong trend towards strategic influence. The findings reveal that 37% of respondents expect the Chief Compliance Officer (CCO) role to expand significantly into providing strategic advice. Currently, a substantial 42% of those surveyed report that the CCO role remains primarily focused on engaging with regulators and interpreting policy. However, the desire for broader impact is evident, with 36% envisioning their roles evolving to encompass data-driven compliance strategies and 32% forecasting increased utilization of technology in their processes.
This anticipated strategic pivot is underpinned by a robust increase in compliance budgets, with an overwhelming 93% of those surveyed expecting their budgets to grow. This budgetary expansion is largely fueled by a projected 89% increase in investment in compliance technology. Among the key areas slated for significant investment are Know Your Customer (KYC) and Anti-Money Laundering (AML) solutions, prioritized by 44% of respondents. Artificial intelligence (AI) tools are also a major focus, with 39% anticipating greater investment, followed by data management solutions at 35%. These investments underscore a strategic commitment to leveraging technology for more efficient and effective compliance.
The current technological infrastructure within organizations reflects a complex ecosystem. The MCO survey highlights that organizations typically utilize an average of 13.8 compliance systems, often comprising a mix of vendor-provided technology, in-house developed systems, and ongoing manual processes. This hybrid approach suggests a transitional phase, where organizations are integrating new technologies while still relying on established methods. The anticipated surge in investment in AI and data management tools indicates a move towards greater automation and data-informed decision-making, potentially streamlining these complex systems in the future.
AI Integration Accelerates Within Boardrooms, Sparking Both Efficiency and Security Concerns
The adoption of AI within the highest echelons of corporate governance is experiencing a dramatic surge, according to a separate survey by OnBoard. The study, which polled 531 directors, administrators, and enterprise leaders, found that the use of AI by directors has escalated to over 90%, a remarkable increase from 69% in 2025. This rapid adoption signifies a growing reliance on AI tools to enhance board effectiveness and streamline operational tasks.
The most common applications of AI reported by directors include summarizing board books, reports, and documents (54%), and assisting in the writing or refinement of meeting minutes (53%). Nearly half of respondents (49%) are leveraging AI to draft or format meeting agendas, while 40% utilize it for research and data analysis. Other significant uses include the creation of presentations and executive reports (35%) and the proactive anticipation of board questions and preparation of responses (33%). This widespread adoption suggests that AI is becoming an indispensable tool for directors in managing their responsibilities more efficiently.
Despite the widespread adoption, a significant gap exists in formal AI policy implementation for directors. The OnBoard survey reveals that 38% of organizations lack a formal AI use policy for their directors. An additional 25% are in the process of developing such guidelines, while 27% have basic or shared formal rules in place. Critically, only a mere 6% of organizations enforce formal AI policies on their directors. This disparity raises potential governance and risk management concerns, as the rapid integration of AI may outpace the establishment of clear guidelines and controls.
The increasing reliance on AI has coincided with a notable decline in security confidence among boards. The survey indicates a 15 percentage point drop in confidence in board security, from 61% in 2025 to 46% in 2026. This figure is even lower than the 54% recorded in 2024, suggesting a growing unease regarding the security implications of AI integration. Among the most cited negative impacts of AI are data privacy, confidentiality, and data usage concerns, flagged by 38% of respondents. This trend highlights the critical need for robust cybersecurity measures and comprehensive data governance frameworks to mitigate the risks associated with AI adoption.
Furthermore, the OnBoard survey touched upon board composition and effectiveness, with 87% of respondents stating that their board has at least one ineffective member. This observation, while not directly linked to AI, suggests a broader context of challenges within board oversight that AI adoption might either exacerbate or help to address.
Mission-Driven Organizations Prioritize Financial Stability Amidst Emerging Risks
For nonprofit and public sector organizations, financial outlooks represent the most pressing concern, according to a survey by Diligent. More than half of these mission-driven entities (53%) identify an economic or funding downturn as their primary organizational risk. This highlights the precarious financial environment in which these organizations often operate, where external economic factors can have a profound impact on their ability to fulfill their mandates.
Beyond financial stability, legislative and regulatory changes are also a significant concern for 34% of respondents. This underscores the dynamic and often complex regulatory landscape that these organizations must navigate. Other identified top risks include large-scale cybersecurity breaches (21%), a breakdown in culture, ethics, or staff voice (18%), and disruptions from AI or new technologies (17%). The latter point, along with misinformation and disinformation affecting stakeholder perception (also at 17%), signals a growing awareness of the multifaceted challenges posed by the rapidly evolving technological and informational environment. Notably, 11% of respondents expressed concern about confidential information being leaked from unsanctioned AI events, a specific risk stemming from the increasing use of AI.
To improve board risk oversight, a significant portion of respondents (38%) believe that more frequent and structured risk discussions at the full-board level are essential. Other suggested improvements include a clearer linkage between risk and strategy (28%), a clearer definition of roles (24%), deeper integration of risk into committee agendas (20%), and improved management reporting (20%). These suggestions point towards a desire for more integrated and strategic approaches to risk management, moving beyond siloed discussions.
The Diligent survey also shed light on desired changes in board meeting structures. Almost half of respondents (49%) called for more time dedicated to strategic planning. Additionally, 37% expressed a need for better tools and processes for managing agendas and board materials, and 31% indicated a preference for fewer presentation-heavy meetings. These feedback points suggest a desire for more efficient, strategic, and engaging board sessions.
Cyber Threats Top Concerns for 2027, with AI Emergence Close Behind
As organizations look towards 2027, cyber threats are identified as the most significant risk, according to a joint survey by Protiviti and North Carolina State University’s Enterprise Risk Management Initiative. The study, which surveyed 1,330 global board members and C-suite executives, asked participants to rate potential risks on a scale of one (no impact) to five (extensive impact). Cyber threats received the highest average score of 3.58, underscoring their pervasive nature and the ongoing efforts required to mitigate them.
Close on the heels of cyber threats is the emergence of new risks stemming from the implementation of AI, which garnered a score of 3.45. This highlights the dual nature of AI – offering significant opportunities for efficiency and innovation, while simultaneously introducing novel and complex risks. Economic conditions and regulatory concerns followed, ranking third and fourth with scores of 3.41 and 3.37, respectively. The rapid pace of disruptive innovations, driven by emerging technologies or other market forces, was ranked fifth with a score of 3.36.
These immediate concerns are mirrored in the long-term challenges identified by respondents. Over two-fifths (41%) cited security and privacy as a long-term challenge, while 40% pointed to AI deployment and 38% identified markets and economies as enduring challenges. This indicates a sustained focus on these areas as critical factors influencing organizational resilience and growth over the coming years.
Banking Sector Expresses Caution Regarding AI in Lending and Underwriting
Within the financial services sector, a notable proportion of professionals are expressing reservations about the integration of agentic AI in lending and underwriting workflows. A survey by Wolters Kluwer found that one in three financial services professionals (33%) consider the use of agentic AI in these critical areas as a top risk. Similar concerns are voiced regarding collections and recovery, where 30% of respondents anticipate the most significant risks from agentic AI.
The operational aspects of AI deployment also present challenges. Nearly 38% of respondents indicated that they are least prepared for regulatory reporting of an AI failure, suggesting a need for enhanced reporting frameworks and capabilities. Furthermore, 34% reported that model kill-switch protocols are not yet in place, highlighting a potential vulnerability in the ability to swiftly halt or contain AI systems in case of malfunctions or unintended consequences.
The survey also identified specific risks related to AI safety frameworks. A substantial 34% of respondents pointed to automation bias as the greatest risk to their AI safety framework. Automation bias occurs when individuals place undue trust in automated systems, potentially overlooking critical information or making suboptimal decisions. Another 27% identified the misalignment of incentives as the top risk for AI safety, suggesting that the goals of AI systems may not always align with human or organizational objectives. These findings underscore the critical importance of robust governance and ethical considerations in the deployment of AI within the sensitive domain of financial services.
