As compliance demands intensify, artificial intelligence is stepping in, transforming complex obligations into engines of opportunity. With predictive analytics and adaptive automation, AI is continuing to reshape the regulatory landscape, helping firms to thrive – can it turn regulatory burdens into advantages?
Jon Elvin, strategic risk advisor at Saifr, believes that advancing both AI and technology in general can reshape the role of compliance teams in several ways. The first thing that comes to mind for Elvin is the breath, depth and context insights it can bring to extremely large data sets.
He said, “Humans cannot possibly see, ingest and evaluate billions of pieces of information with the precision machines can. AI can also do this repeatedly and consistently. Let it be your eyes, ears and digital labourer.”
Furthermore, Elvin stressed that the capabilities and output from AI can then be used by compliance professionals as a task and scale accelerator to help much as computer assisted audit techniques did for the accounting and professional services industry previously.
Elvin explained, “For instance, business process automation when combined with highly structured and repeatable outcomes can be automated for many tasks, reducing complacency and variability of staff/decisions thus saving time and improving the quality of throughput. For instance, why run an audit test or compliance health check once a year, when AI can do it 24/7 with real-time insight or defect identification?”
Whilst machines and advanced algorithms shouldn’t be used for all decisions without compliance-level discretion, experience and oversight, Elvin remarks, it can certainly do the heavy lifting, draw inferences, collate facts and summarize results at scale. “It is your compliance and digital copilot and labourer saving time and driving confident, consistent results,” he said.
The strategic risk advisor also raised another task – one he described as ‘distinct and cumbersome’ where AI is able to provide immediate relief is the identification of new rules, laws and regulatory guidance that then triggers adjustments and rewriting of policies, procedures and job aides to reflect changes.
He commented, “While these are basic in concept, and like the importance of detecting word-match anomalies that are inconsistent with some compliance rules associated with marketing materials that take time, flips the advantage to more complex tasks for employees to focus on.”
In what ways can AI reshape the role of the compliance team? On this point, Elvin labours that AI is likely to shift the ‘effort curve’, decision-making sequence and even lead to greater employee experiences by reimaging the inefficiency in traditional 80% hunting and gathering, 10% collating with only about 10% time spent on interpreting and making decisions.
He added, “New advances and applications should let AI spend the 90% of time on those, so called level one tasks and find hidden insight and connections and now allow the employee to spend a greater percentage of time on those truly more important decisions and complex tasks that require judgment.”
“AI will clearly reshape team makeup,” Elvin explained. “We are already seeing adjustments to design, skill mix, ratios and tasks to match effort curve priorities. While the manual nature will be reduced, the ability of compliance professional to completely understand what the AI is trying to solve, basics of how it does that, the why you should be confident it is doing what it does, and then the ability to communicate the explainability of it will be one of the new important job responsibilities.”
Efficency gains, cost reduction and effectiveness are three areas for Elvin that will drive the expectations and pace of adoption. “At the same time misses or mistakes that have disparate impact or are not effective in results will then trigger a return, in some cases to not trusting machines and too much time on checkers, checking checkers in the redundant nature of monitoring,” he said.
Elvin also highlighted that he often gets asked of how compliance and AI can produce strategic insights. On this, one of the largest areas of compliance program evolution, growth and cost has been AML and fraud.
He said, “A few specific and simple answers where AI and compliance insights can be turned into strategic insights is illustrated by both sides of the coin from monitoring customer transactions. The business and anti-financial crime sides look for the head and tail of data with different uses. AML professionals look for the true anomaly where a customer may be circumventing or facilitating criminal activity, like large presence of cash, wire activity or geographic concentrations.”
If something is suspicious, it is investigated and dealt with. Analysing the same data, Elvin stated, a customer’s activity may not truly be criminal, yet that would be valuable from a sales perspective and cross sell opportunity.
He explained, “Maybe the customer’s business is expanding with key growth, maybe they inherited new wealth, or have new operating needs. Recall large movements in cash and wire lead to selling cash management services, treasury management payment capabilities and investment leads. Same data, two difference use cases where AI and compliance have mutual value. The key is unlocking insights and turning them into actions for multiple stakeholders.”
Rapidly expanding possibilities
Compliance has come a long way in enabling organizations to align their controls, policies and procedures with their regulatory responsibilities and strategic objectives in a world of rapidly evolving threats and increasingly unstable market, believes co-founder and COO of 4crisk.ai Supra Appikonda.
He continued, “Now we are seeing AI technologies introduce breakthrough value that is rapidly expanding possibilities for compliance teams to consolidate information, centralize and organize controls, and dramatically reduce or even eliminate manual efforts. Most importantly, compliance teams are beginning to unlock a level of agility that gives organizations a strategic and competitive edge. This is because AI is particularly suited for instant and deep data analysis, identifying patterns and correlating information from widely disparate data sets and sources far more effectively than humans can alone.”
In the mind of Appikonda, with AI, compliance teams can find and diagnose problems quickly and with a much higher level of context and accuracy. “Advanced algorithms and machine learning can assist organizations in identifying patterns that elude more traditional compliance processes and methods. For example, AI can crunch through massive amounts unstructured and structured data to quickly assess the implications of external changes on policies, procedures and controls,” he said.
He added that AI tools can be instrumental in helping organizations validate, rationalize and map policies, controls and procedures across distinct organizational and third-party domains. The robust analytical capabilities that AI brings to the table result in comprehensive and continuous compliance assessments across the organization, pointing to how gaps may be closed and compliance optimized.
He added, “AI tools give compliance teams an advantage in defining their organization’s compliance posture. They enable teams to connect information, draw conclusions, and take confident action in addressing uncertainty. By leveraging the power of AI in compliance and risk, organizations can streamline their compliance efforts, ensuring a more secure and stable future.”
In order for firms to turn compliance data into a strategic insight, Appikonda responded by highlighting that the dynamic nature of the economic landscape, coupled with ever-evolving cyber and regulatory requirements, is driving organizations to focus more and more on getting compliance their data right, to reduce risk exposure throughout the organization.
He said, “Constant change makes the job of compliance teams in interpreting, harmonizing, and implementing controls difficult. Knowing what needs to change, in priority sequence, and then to actually make the right changes quickly, is table stakes for staying in compliance.
“Deep insights served up by AI-powered compliance data help prioritize what to do to remain in compliance. Getting insights that allow teams to quickly triage and act on new requirements can mean the difference between being in headlines, or reading about your competitors, who have mis-stepped.”
The role of compliance teams can be reshaped through AI, and in this area, Appikonda emphasised that compliance teams have long been seen as the bedrock on which an organization’s long-term well-being is constructed – harmonizing policies, controls, business data, regulations, and organizational strategy in a sustainable and cost-effective way.
He said, “Regulatory frameworks, controls, and rulebooks are used by many activities across the organization, supporting governance, risk, ESG, legal, compliance, IT, security and privacy programs. As these teams reconcile risks and obligations across operations, compliance professionals sometimes feel like they are trudging through quicksand.
“All these challenges create a formidable mountain of variables that compliance teams must navigate. Often, they find themselves playing catch-up. Organizations may resort to common-sense controls, tribal knowledge, and contextual exceptions to meet compliance requirements. While these methods are not inherently problematic, an overreliance on them can lead to blind spots where vulnerabilities can emerge that put the organization at risk.”
For Appikonda, AI is pushing the boundaries of what compliance teams are able to achieve as they strive to align policies, procedures, controls and standards to regulatory and business obligations.
Furthermore, he stressed that process and control validation and rationalization are critical steps within the compliance process, demanding a meticulous alignment of regulatory guidelines, updates, and documents with organizational goals, obligations and strategy. AI, he added, slashes these time-consuming processes by rapidly mapping and connecting relevant regulatory data to processes and controls to identifying gaps and discrepancies, allowing organizations to fortify their control mechanisms.
Appikonda concluded, “Compliance leaders that use AI data analysis, process mapping and correlation to deliver deep insights, can focus their efforts on responding with agility to the compliance risks that emerge as their markets and organizations evolve. Leveraging AI-driven compliance can mean the difference between thriving in a world of change, meeting business objectives, or becoming overwhelmed and ultimately, ineffective.”
No longer optional
Muinmos CTO Emil Kongelys believes that in today’s landscape, adopting AI is no longer optional – with those who fail to do it risk falling behind. Despite this, successful integration in his mind requires careful strategy, and the compliance leaders who make informed decisions and guide thoughtful AI adoption will win tomorrow.
“AI is a powerful tool that, when applied effectively, can streamline even the most complex workloads,” said Kongelys. “The rise of specialized AI agents – each tailored to specific tasks – enables accurate, data-driven outcomes with minimal risk of hallucination. This significantly reduces the time required for tasks like document review and research. For compliance teams, such tools enhance regulatory alignment, minimize manual errors, and help anticipate potential risks.”
How may businesses turn compliance data into strategic insight? According to Kongelys, data is a strategic asset, and AI excels at rapidly processing and analyzing large datasets. He added, “This capability helps identify inefficiencies, such as redundant tasks or process bottlenecks, and can reveal training gaps through breach analysis. Additionally, AI-driven insights can highlight regions or products with higher regulatory risk, providing valuable metrics to guide business expansion and strategic decisions.”
Muinmos views compliance as a strategic sales enabler. In the view of Kongelys, by leveraging AI to manage end-to-end client onboarding across jurisdictions, the company ensures regulatory compliance whilst accelerating client acquisition.
He finished, “This reflects a broader vision of compliance – not as a constraint, but as a catalyst for growth. With the right AI tools, compliance teams can move beyond oversight to actively drive business value, whether through onboarding or internal governance.”
The hybrid approach
For Gion-Andri Büsser, co-CEO of IMTF, AI’s true potential in compliance lies in its combination with automation.
He explained, “Together, it enables both the significant reduction of manual work as well as a better assessment on risk, priority and criticality through AIs ability to combine multiple datasets, client context and new, untapped information siloes. By automating routine tasks and enhancing human judgment, AI empowers compliance teams to focus on higher-value decisions.
“This combination not only ensures regulatory compliance but also allows organizations to leverage compliance data to improve operational efficiency, enhance customer experience, and drive proactive risk management.”
Büsser additionally raised a third important pillar – human expertise and oversight. While AI and automation handle data analysis and decision-making at scale, Büsser believes human oversight ensures transparency and trustworthiness through explainable AI, allowing compliance teams to maintain control and ensure that decisions align with organizational goals.
“At IMTF, we believe in applying a hybrid AI approach to achieve the best results, combining AI, rule-based systems, automation, and human-in-the-loop decision-making,” he said. “This ensures the highest accuracy and efficiency, empowering organizations to tackle complex compliance challenges with precision and confidence.”
For RelyComply, a key burden of compliance – particularly in AML – lies not just in meeting regulatory thresholds but consistently and cost-effectively across complex data sets. AI, they said, enables this by automating repetitive checks, reducing false positives, and highlighting anomalous behaviour that may evade static rules.
They concluded, “What turns this into a strategic advantage is real-time adaptability. With increasingly heterogeneous financial ecosystems, institutions need systems that can interpret evolving patterns and adjust without constant manual tuning. This is where machine learning and dynamic rule systems excel, provided their outputs can be explained and validated. Proper implementation also requires training, governance, and oversight investment to ensure that AI systems are aligned with regulatory expectations and operational realities.”
Smoothing workflows
An area where AI has undoubtedly already shown to have huge efficiency and optimisation benefits is in the area of workflows. For Baran Ozkan, CEO of Flagright, AI shines by taking over repetitive tasks, think transaction scans and filing reports, so fincrime teams can focus on big-picture strategy.
He added, “When you mine your compliance data with machine learning you can uncover new revenue opportunities, discover underserved customer segments or spot cost leaks. Compliance pros evolve into insight analysts and model governors rather than data jockeys. The real winners marry AI smoothly into their workflows, back it up with clear governance and show tangible returns on their investment.”
Keep up with all the latest RegTech news here
Copyright © 2025 RegTech Analyst
Copyright © 2018 RegTech Analyst
