Tag: GenAI

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How Generative AI is Transforming Business and Compliance in 2025

One thing I have learned from the digital age is that to stay ahead, we must stay informed and proactive about how new technologies impact corporate governance, ethics, and operational compliance. In this context, generative AI (Gen AI) is no longer a futuristic concept; it is embedded deeply in our everyday activities. Marc Zao-Sanders’ article in Harvard Business Review (HBR), “How People Are Really Using Gen AI in 2025,” presents an excellent opportunity to reflect on how these developments impact compliance, governance, and risk management.

Zao-Sanders highlights a critical shift in how generative AI is utilized: from purely technical assistance towards significantly more personal and emotive applications. With “Therapy/Companionship,” “Organizing my life,” and “Finding purpose” emerging as the top three use cases, it’s clear that users seek emotional and organizational support, demonstrating Gen AI’s versatility beyond traditional technological roles.

Compliance professionals must recognize that as AI increasingly becomes integral to both professional services and personal well-being, the accompanying risk and compliance implications magnify exponentially. The nature of these interactions, often intimate or deeply personal, demands robust data privacy protections and stringent ethical governance frameworks. Businesses integrating these technologies need precise, transparent policies and effective oversight mechanisms to mitigate new compliance risks.

Implications for Compliance Professionals

Enhanced Data Privacy and Ethical Considerations

Zao-Sanders emphasizes the rising prominence of personal and professional support through Gen AI, especially in areas such as AI-based therapy, emotional companionship, and life organization. As users entrust AI with highly sensitive personal data, compliance professionals face increased responsibilities regarding data privacy, security, and the ethical use of data. This scenario elevates the stakes considerably. He notes, “data safety is not a concern when your health is deteriorating,” highlighting users’ willingness to sacrifice privacy for crucial emotional or medical support. Such conditions can quickly lead to ethical and compliance vulnerabilities if businesses fail to manage and protect sensitive user data rigorously.

Organizations must reinforce their compliance strategies to manage ethical risks inherent in AI-human interactions. As Zao-Sanders indicates, professional services, including medical, legal, and financial advisement, are increasingly relying on generative AI, pushing regulatory boundaries. Notably, EY’s deployment of 150 AI agents specifically for tax-related tasks highlights the profound impact of generative AI on professional services, adding layers of complexity to compliance strategies.

Regulatory Response and Enforcement Trends

The article briefly touches on the growing regulatory scrutiny that Gen AI is attracting globally, noting explicitly that governments are “taking more emphatic and explicit positions” due to heightened stakes surrounding AI technology. For compliance professionals, this should serve as a clarion call: regulatory oversight is intensifying. Preparing for audits, demonstrating compliance, and actively engaging with regulatory developments will be essential. The rapid pace of AI adoption necessitates an agile and proactive approach to compliance management that anticipates, rather than merely reacts to, regulatory shifts.

Balancing AI Dependence with Human Oversight

A striking tension highlighted in the article is the debate over the impact of generative AI on human cognitive abilities, decision-making, and ethical judgment. Users express genuine concern about becoming overly reliant on AI, which could erode their ability to think critically and make independent, ethical decisions.

This reliance poses significant implications for compliance officers charged with safeguarding ethical decision-making. Effective compliance programs must emphasize human oversight, cultivating a culture where AI supports rather than supplants human judgment. Investing in AI literacy among employees can mitigate potential over-reliance, fostering an environment where staff understand both the capabilities and limitations of AI.

Compliance in AI-Driven Professional Services

Zao-Sanders illustrates how AI integration into professional tasks is increasingly sophisticated. For instance, the transformation underway at EY, training employees extensively in generative AI, reflects broader industry trends. Compliance officers must respond to these developments by establishing clear standards and compliance checkpoints. It is crucial to determine whether AI outputs meet professional standards, remain unbiased, and do not inadvertently violate regulatory obligations.

Given AI’s pervasive integration into professional judgments (such as tax preparation, legal advice, and medical diagnosis), the accuracy and regulatory compliance of AI-driven outputs become paramount. Compliance programs must integrate AI auditability, accountability, and transparency deeply into corporate governance frameworks.

Practical Compliance Steps in the Gen AI Era

1. Proactive Policy Development and Training

Develop clear policies that outline the acceptable use of generative AI, including specific guidelines on data handling, ethical considerations, and regulatory obligations. Embed these policies into your organization’s culture through rigorous training and communication strategies.

2. Rigorous Risk Assessment and Ongoing Monitoring

Gen AI compliance must adopt continuous monitoring. Regular risk assessments and periodic audits of AI systems will promptly detect and rectify issues. Compliance officers should remain actively involved in assessing new AI technologies for ethical, privacy, and regulatory considerations before full-scale implementation.

3. Transparent Data Practices

Given the heightened public sensitivity to data privacy concerns, as noted by Zao-Sanders’ mention of users’ concerns around data privacy and their cynicism toward Big Tech, companies must prioritize transparent data practices. Clear communication about data usage, consent, and protection measures will foster trust and reduce compliance risks.

4. Ethical AI Governance Frameworks

Design and deploy ethical AI governance frameworks that address algorithmic fairness, transparency, and accountability, ensuring responsible use of AI. These frameworks ensure generative AI tools are deployed responsibly and ethically, aligning with stakeholder expectations and regulatory standards.

5. Encourage Human-AI Collaboration

Foster a balanced approach between AI-driven solutions and human judgment. Reinforce the importance of human oversight to ensure compliance, accuracy, and ethical decision-making, thus minimizing over-dependence on AI.

Looking Ahead—The Compliance Imperative in the Gen AI Landscape

As we approach a future increasingly defined by AI integration, compliance professionals have a unique opportunity to lead their organizations proactively. Understanding and managing the compliance and ethical dimensions of Gen AI is now critical, not optional. The risks and opportunities outlined in Zao-Sanders’ article underscore the urgent need for a strategic, well-informed approach to integrating generative AI into corporate compliance frameworks.

Compliance professionals should view this moment as an opportunity to demonstrate thought leadership, to guide ethical AI adoption, and to establish robust frameworks that enable businesses to thrive responsibly. By proactively addressing the compliance and moral challenges presented by generative AI, we not only fulfill our professional obligations but also position our organizations as ethical, forward-thinking leaders in the digital age. The compliance journey ahead is demanding, but equally, it offers profound opportunities to influence and shape a responsible, compliant, and ethically robust AI-driven future.

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AI and the Future of Compliance Education: Why the Future is Now

For too long, compliance training has been seen as little more than a necessary evil, a one-size-fits-all exercise in checking a regulatory box. Employees shuffled through mandatory seminars, PowerPoint decks, and click-through e-learning modules, treating them as hurdles to clear, not learning opportunities. That world is dead. Buried. In 2025, compliance education is radically transforming, and AI is leading the way.

The future of compliance education is personal, immediate, engaging, and embedded. It’s about delivering the right knowledge to the right employee at the right time, i.e.,. Before a violation occurs. Compliance is no longer a periodic event; it’s a continuous experience. How can AI, microlearning, gamification, and VR completely change the game, and what lessons must compliance professionals learn today to build a better tomorrow?

Lesson 1: Traditional Training is Outdated—AI is Leading the Way

First, yesterday’s training models cannot keep up with the proper pace of modern regulatory risk. Static, annual training modules don’t resonate with today’s workforce or dangers. Enter AI. Smart compliance platforms now personalize training based on individual employee roles, learning styles, risk exposure, and past behavior. Employees are no longer passive listeners but active participants in scenario-based simulations that mirror real-world dilemmas. Imagine practicing an FCPA dilemma in a gamified environment rather than skimming through a bullet-point list.

Even better, AI does not simply deliver content; it measures how employees engage with it. Advanced analytics track progress, flag disengagement, and allow compliance teams to adjust real-time training strategies. The result? A proactive, continuously evolving compliance culture.

If you’re still relying on static training in a dynamic risk environment, you are not only behind; you are exposed.

Lesson 2: Customization is Key—One Size Fits Nobody

Let’s be blunt: Generic compliance training wastes everyone’s time. Different employees face different risks. Your sales team in Latin America needs training that is different from your engineering team in Berlin. A one-size-fits-all approach is not simply ineffective; it can indeed be counterproductive.

AI-driven compliance platforms address this head-on by customizing content at the individual level. They analyze roles, responsibilities, risk profiles, and even upcoming activities. Imagine this: An employee traveling to a high-risk country automatically receives reminders about anti-bribery policies, gift-giving guidelines, and applicable trade sanctions before they step on the plane.

This proactive, role-specific approach exceeds DOJ expectations around tailored training (first articulated in the 2017 Evaluation of Corporate Compliance Programs and reinforced in the 2024 ECCP). It embeds compliance into employees’ day-to-day decision-making.

Customization drives engagement. Engagement drives behavior change. Behavior change protects the organization. It is that simple.

Lesson 3: Real-Time Compliance Training is Proactive, Not Reactive

Historically, compliance teams operated in a reactive mode. Violations occurred, investigations followed, and training was assigned as a remedial slap on the wrist—no more. With AI, compliance training can now be real-time and predictive. Imagine an AI system that monitors workflow data and employee behavior, delivering just-in-time reminders before a decision is made, not after a violation occurs.

Picture this: An employee processing an unusual third-party payment receives an instant alert reminding them of anti-corruption controls. Another employee about to click a suspicious email gets a real-time warning about phishing attacks. AI can even draw insights from external events. If a major competitor is penalized in China for export control violations, your employees operating in that region can immediately receive a warning and updated guidance.

Real-time training transforms compliance from a “policing” function into a “partnering” function, guiding employees to make better decisions in the moment. That’s the future we should be building toward.

Lesson 4: Gamification and Microlearning Supercharge Retention

We’ve known for years that traditional long-form compliance training doesn’t stick. Most employees forget 70% of what they learned within a week. Why? Because brains aren’t wired to retain dense information delivered in passive, hour-long blocks. Gamification and microlearning flip the script.

Microlearning delivers bite-sized, focused modules that employees can absorb quickly, perfectly tailored to today’s fast-paced work environments. Gamification adds points, badges, competitions, and rewards to incentivize engagement. Together, they create training experiences that are not only more effective but also fun. And the results aren’t theoretical. Studies show that microlearning can improve knowledge retention by up to 75%. Walmart’s use of VR compliance training led to a reported 30% decrease in policy violations.

When employees are immersed in gamified simulations where decisions have consequences and feel the real-world weight of ethical challenges, they build the muscle memory to act correctly under pressure. Compliance becomes instinct, not obligation.

If you are serious about building a culture of compliance, gamification and microlearning must be part of your toolkit.

Lesson 5: AI is the Ultimate Training Effectiveness Engine

Finally, AI does not just deliver better training; it measures and improves it.

Modern AI-powered compliance platforms track every interaction. They identify which employees are struggling, which departments face higher risks, and which topics aren’t sticking. They can predict which employees are most likely to face ethical dilemmas—and target interventions accordingly. This feedback loop is transformative. Instead of guessing whether training “worked,” compliance professionals can know and take swift action when needed. AI-driven insights allow for dynamic course corrections, ensuring compliance education stays aligned with emerging risks, regulatory updates, and organizational changes.

By embedding continuous improvement into training, AI moves compliance education from a static obligation to a living, breathing strategy for risk management and corporate resilience.

Conclusion: The Future Is Now—Are You Ready?

The transformation of compliance education isn’t a “someday” concept. It is happening right now. Leading companies are already embedding AI, gamification, microlearning, real-time alerts, and VR simulations into their compliance ecosystems—and they’re seeing measurable results. Compliance training is no longer a boring box to check. It’s a dynamic, personal, data-driven force multiplier for ethics, integrity, and business performance.

The real question for compliance professionals today isn’t whether AI will reshape compliance education. It’s whether your organization will be a leader or a laggard in embracing change. The future of compliance education is here. It is immersive, predictive, personal, and powered by AI.

Are you ready to lead the way?

In short, the future of whistleblower programs is here—and it’s intelligent.

The above is from my latest book, Upping Your Game: How Compliance and Risk Management Move to 2030 and Beyond, available from Amazon.com.

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FCPA Compliance Report

FCPA Compliance Report – From Compliance to Commercial Value: Removing Friction with AI

Welcome to the award-winning FCPA Compliance Report, the longest-running compliance podcast. In this episode, Tom welcomes back Jag Lamba, CEO at Certa, to discuss the use of GenAI in compliance tools.

Lamba advocates for the transformative power of artificial intelligence in revolutionizing third-party risk management. Lamba believes businesses can streamline processes, reduce friction, and enhance decision-making throughout various phases of third-party interactions by leveraging AI, particularly generative AI and natural language processing tools. He emphasizes that AI can simplify complex tasks like analyzing extensive reports and identifying specific risks, thus improving compliance reporting and operational efficiency. Lamba envisions a future where AI seamlessly integrates into core business operations, making compliance management an inherent and valuable aspect of organizational workflows, particularly benefiting smaller and mid-sized companies.

Key highlights:

  • Automating Third-Party Risk Management with AI
  • AI-powered Tools Enhancing Third Party Risk Management
  • AI-driven Automation for Enhanced Compliance Reporting
  • Automating Compliance Tasks to Boost Operational Efficiency

Resources:

Jag Lamba on Linkedin

Certa AI

Tom Fox

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For more information on the use of AI in Compliance programs, see my new book, Upping Your Game. You can purchase a copy of the book on Amazon.com

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Compliance Tip of the Day

Compliance Tip of the Day – The Future of Continuous Monitoring

Welcome to “Compliance Tip of the Day,” the podcast where we bring you daily insights and practical advice on navigating the ever-evolving landscape of compliance and regulatory requirements. Whether you’re a seasoned compliance professional or just starting your journey, we aim to provide bite-sized, actionable tips to help you stay on top of your compliance game. Join us as we explore the latest industry trends, share best practices, and demystify complex compliance issues to keep your organization on the right side of the law. Tune in daily for your dose of compliance wisdom, and let’s make compliance a little less daunting, one tip at a time.

Today, we consider why continuous monitoring is here to stay and how to use it in your compliance program.

For more on embedded compliance, check out my new book, Upping Your Game: How Compliance and Risk Management Move to 2030 and Beyond, available from Amazon.com.

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The Future of Continuous Monitoring: AI-Driven Compliance is Here to Stay

The compliance function has officially crossed the Rubicon. Artificial intelligence is no longer an experimental technology on the compliance periphery; it is at the center of forward-thinking compliance programs. We are witnessing a seismic shift in managing risk, detecting misconduct, and maintaining corporate integrity. AI enables real-time monitoring, uncovering subtle anomalies, and delivering the kind of automated oversight previously confined to PowerPoint dreams. As we enter 2025, the question is not whether your compliance function should adopt AI but how quickly you can make it central to your operations.

This blog post explores how compliance professionals can use AI to power a future-ready, continuously monitored compliance program. Today, we will explore five powerful lessons supported by real-world case examples and framed within current regulatory expectations. As Andrew McBride described, we are entering the “Holy Grail” era of compliance, where due diligence, internal and external data, and communications can be monitored holistically through AI agents trained to detect abnormalities and investigate unethical behavior.

Lesson 1: AI Enhances Risk Detection

AI doesn’t just speed up compliance; it sharpens it. Traditional compliance teams have long struggled to keep up with massive amounts of structured and unstructured data. From financial transactions to email threads, vendor records, and chat logs, there are risk indicators that no human team could feasibly monitor in real-time. Enter AI and machine learning.

With natural language processing (NLP), AI systems can read between the lines. They detect shifts in sentiment, keyword patterns, and coded language that may indicate bribery, fraud, or circumvented controls. Matt Galvan emphasizes this as a game-changer, especially when GenAI tools synthesize background due diligence with transactional anomalies to flag red flags early before misconduct manifests.

Better still, AI eliminates the “needle in a haystack” problem. It builds outliers into profiles, detects slush fund behavior, and creates actionable summaries with supporting documentation. You are not simply faster, and you are smarter. But here’s the kicker: the quality of AI outputs depends on the quality of your inputs—poor data = poor detection. AI must be trained on clean, complete, and bias-aware datasets. And AI should never operate in a vacuum. Human judgment remains essential to interpret findings and assess the business context.

The bottom line is that AI transforms compliance from reactive to proactive. It is no longer about catching up; it is about staying ahead.

Lesson 2: Regulators Expect AI-Driven Compliance

If you need a business case for AI, start with the Department of Justice (DOJ) and its 2024 Evaluation of Corporate Compliance Programs (2024 ECCP). The DOJ has moved beyond encouragement and now expects companies to adopt real-time, AI-powered compliance monitoring. Failing to implement these tools could soon be seen as a failure to meet basic compliance standards.

This isn’t just about the DOJ. The SEC, FinCEN, OCC, Federal Reserve Board, and the Financial Action Task Force (FATF) are pushing toward a future where real-time compliance tools are a baseline requirement, not a nice-to-have. What’s more, regulators are now asking companies to explain their AI. What data powers your algorithms? How are decisions made? Can you justify why one transaction was flagged and another was not? Transparency and audibility are no longer optional; they are regulatory imperatives.

Regulators understand that AI can reduce legal risk and enhance oversight. They expect you to understand it, too.

Lesson 3: AI Identifies Emerging Geopolitical Risks

Welcome to the volatility vortex of 2025. What was a low-risk jurisdiction on Friday can be a sanctioned country by Monday. Supply chains bend and sometimes break under the weight of sanctions, tariffs, and political upheaval.

Traditional compliance programs cannot react fast enough. This is where AI earns its keep. AI flags emerging geopolitical risks before they bite by ingesting thousands of data points from news, regulatory alerts, trade databases, and internal procurement systems. Andrew McBride’s example of a virtual bill of materials is especially prescient: imagine knowing exactly where a conflict mineral is buried in your supply chain and being alerted when a regulatory status changes.

AI makes it possible. Galvan pointed out that the same data sets used to optimize supply chains can be re-leveraged for compliance risk analysis. In other words, compliance teams should not operate with less information than procurement or logistics. If you are waiting for geopolitical risk to reach your front door, sadly, you are already behind. AI enables a proactive posture to protect your business from international surprises.

Lesson 4: Automating Compliance Reduces Costs and Increases Efficiency

Efficiency is often an underappreciated outcome of effective compliance. But let’s be clear: automation isn’t just about doing things faster; it is about doing them better and cheaper. AI automates transaction monitoring, scans for real-time anomalies, and triages cases for deeper review. No more relying on random audits or static checklists. AI helps compliance programs scale, especially for global companies managing thousands of vendors and counterparties.

Consider regulatory reporting: AI can automate data collection and reporting preparation, ensuring timely submissions and reducing the burden on internal teams. These efficiencies translate directly into cost savings while improving quality.

McBride’s point about AI-driven NLP catching potential bribery schemes in real-time is a glimpse into what’s already possible. Emails, Teams messages, and Slack conversations are goldmines of risk insight when monitored responsibly and legally. Just-in-time risk flags make compliance not only real-time but also real-impact.

AI is your accelerator if you want a leaner, faster, and smarter compliance function.

Lesson 5: Early Adoption of AI Is a Competitive and Ethical Advantage

Finally, we come to the business case. Early adopters of AI-driven compliance are already reaping the rewards. Not just in regulatory peace of mind but in market leadership.

AI enables transparency, consistency, and accountability. It allows organizations to demonstrate good governance, not just say they care about it. That builds trust with investors, customers, and regulators alike. It also helps embed a culture of integrity. By quickly catching issues and addressing them, AI empowers ethics to be lived, not laminated on a wall. And companies that bake ethics into their business model outperform over the long term.

The inverse is also true: those who delay AI adoption will soon find themselves scrambling to catch up, facing increased regulatory scrutiny and higher costs. The future of compliance is not five years away. It’s now. Organizations that embrace AI today will be tomorrow’s industry leaders in ethics, governance, and profitability.

AI is not simply a tool; rather, it is transformational. It allows compliance professionals to do more, do it faster, and do it better. But success requires more than just buying technology. It requires thoughtful integration, rigorous oversight, and a strategic mindset. Continuous monitoring is the future, and the future has arrived. Together, let us build compliance programs that are not only compliant but also resilient, efficient, and ethical.

The above is from my latest book, Upping Your Game: How Compliance and Risk Management Move to 2030 and Beyond, available from Amazon.com.

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Compliance Tip of the Day

Compliance Tip of the Day – Leveraging AI for Real-Time Third-Party Risk Management

Welcome to “Compliance Tip of the Day,” the podcast where we bring you daily insights and practical advice on navigating the ever-evolving landscape of compliance and regulatory requirements. Whether you’re a seasoned compliance professional or just starting your journey, we aim to provide bite-sized, actionable tips to help you stay on top of your compliance game. Join us as we explore the latest industry trends, share best practices, and demystify complex compliance issues to keep your organization on the right side of the law. Tune in daily for your dose of compliance wisdom, and let’s make compliance a little less daunting, one tip at a time.

Today, Tom Fox considers the advantages of using AI for third-party risk management.

For more on embedded compliance, check out my new book, Upping Your Game: How Compliance and Risk Management Move to 2030 and Beyond, available from Amazon.com

 

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Predictive. Proactive. Protected: Leveraging AI for Real-Time Third-Party Risk Management

Even in 2025, third-party risk management remains one of the thorniest challenges for compliance professionals. Whether you oversee distributors in the Middle East, suppliers in Southeast Asia, or data processors in Eastern Europe, the risks, including bribery, sanctions violations, labor abuses, and fraud, remain ever-present. Traditionally, compliance teams fought these battles using static tools: onboarding questionnaires, annual reviews, and spreadsheet trackers. But those blunt instruments are no longer enough in today’s real-time risk environment.

Enter AI, specifically Generative AI (GenAI), predictive analytics, and blockchain, which is revolutionizing third-party oversight and giving compliance professionals the power to act proactively, not reactively. As Jag Lamba, CEO of Certa, astutely notes, GenAI brings three significant value buckets: reduced risk, commercial ROI, and reduced legal costs. Today, I will unpack what that means for compliance and how we can move from the “check-the-box” era to one of integrated, continuous monitoring and risk mitigation.

Compliance in Real Time: The Shift to Predictive Tools

Historically, the compliance approach to third-party risk was episodic. We conducted due diligence at onboarding, maybe revisited it every few years, and crossed our fingers in between. However, the gaps between assessments were dangerous blind spots, exposing companies to risks that regulators like the DOJ and SFO are increasingly unwilling to tolerate.

That’s where predictive analytics steps in. To forecast potential violations, these systems analyze structured and unstructured data, from financial records to adverse media to geopolitical trends. AI flags early risk indicators, such as an unusual payment pattern or a politically exposed person. That allows compliance to intervene before a deal closes, a bribe is paid, and reputational damage is done.

Machine learning (ML) models also allow dynamic anomaly detection. This is especially useful in sifting through transactional data and flagging high-risk behavior patterns like duplicate invoices, mismatched documentation, or sudden changes in third-party ownership.

Blockchain brings an additional layer of trust. Immutable audit trails secure contracts, payments, and due diligence documentation, ensuring the record is tamper-proof and regulator-ready. Smart contracts can enforce compliance obligations automatically, stopping payments, triggering alerts, or suspending activity when a vendor falls out of bounds.

Three Buckets of Value: What GenAI Delivers

Jag Lamba, CEO of Certa, outlined three distinct areas where GenAI delivers:

  1. Risk Reduction – Compliance risk, data privacy risk, ESG risk, reputational risk—the list goes on. AI helps companies avoid working with third parties that introduce these risks into the business ecosystem. This is more than good practice; it is a lifeline for organizations operating under Deferred Prosecution Agreements (DPAs) or with heightened scrutiny from regulators.
  2. Commercial Value – Faster onboarding of sales agents, vendors, or channel partners means faster revenue. Reducing a six-week onboarding timeline to two days can translate into hundreds of millions in new revenue, especially in fast-moving sectors.
  3. Legal Savings – Avoiding regulatory missteps means avoiding costly enforcement actions. In today’s aggressive enforcement climate, those savings are not simply theoretical; they are very real and very substantial.

Compliance should not be a handbrake on business; it should be a business enabler. By embedding GenAI into core operations, organizations create less friction and fewer dual processes, improving business agility without sacrificing oversight.

Five Takeaways for Compliance Professionals

  • Predictive Compliance Is the New Norm

The days of “wait and see” are over. AI lets us anticipate risk, not just react to it. Predictive tools shift compliance from being an internal auditor to a strategic partner in risk mitigation. Companies like Certa use automated third-party master data enrichment to reduce false positives and streamline screening, creating cleaner data for faster, smarter decisions.

  • AI Supercharges Due Diligence

Natural language processing (NLP) and machine learning enable deep due diligence at scale. To flag red flags, AI can scan global watchlists, sanctions databases, court records, and newsfeeds. It can uncover hidden connections, shell entities, familial relationships, and obscure affiliates that human reviewers often miss.

Even better, AI does not sleep. It continually updates third-party risk profiles in real time, offering dynamic monitoring that aligns with today’s fast-changing regulatory landscape.

  • Real-Time Supply Chain Monitoring Is a Must

Supply chains are now under a microscope. From human rights to trade sanctions, regulators demand evidence that companies are proactively managing supply chain risks. AI tools monitor supplier behaviors and flag real-time ESG risks, such as forced labor or environmental non-compliance.

Blockchain ensures that supply chain data remains unaltered and provides traceability across multiple tiers of suppliers. With AI-integrated blockchain systems, compliance professionals can quickly identify issues, trace them to their source, and take corrective action.

  • AI + Blockchain = Fraud and Corruption Prevention

Fraud detection meant following static rules, like transaction thresholds or vendor location mismatches. AI adds nuance. It can detect bribery patterns or fraudulent shell entities by learning from thousands of real-world cases. Meanwhile, blockchain creates an unchangeable record of each transaction, making it harder for corrupt actors to falsify invoices or backdate payments. This two-pronged approach, predictive analytics plus immutable records, offers a potent defense against FCPA and UKBA violations.

  • Third-Party Risk Must Be Continuous, Not Episodic

Third-party due diligence cannot be a one-and-done exercise. Predictive analytics enables a live risk-scoring environment where third parties are constantly evaluated. AI can even detect patterns that suggest “compliance-sensitive” activity, like vendors interacting with government officials or operating in high-risk jurisdictions, flagging them for further review.

One multinational recently implemented a no-code solution that monitors purchase requisitions for signs of regulatory engagement, triggering automated validation questions. This kind of innovation is only possible when compliance works in tandem with IT, legal, and procurement.

Compliance at a Crossroads: Innovate or Fall Behind

After the Trump Administration’s Executive Order suspending FCPA investigation and enforcement, compliance professionals face a fundamental choice: evolve or be eclipsed. But in 2025, manual reviews and siloed spreadsheets. Business leaders expect real-time monitoring, cross-functional integration, and data-backed decision-making to create greater business value. That means compliance must step into a new leadership role that embraces technology, champions cross-department collaboration, and drives value across the enterprise.

It is time for compliance teams to stop seeing AI as a future concept and start seeing it as a present-day imperative. The organizations that embrace this shift will thrive in the next wave of regulatory scrutiny and be best equipped to meet the moment.

As the saying goes, “The best way to predict the future is to invent it.” For compliance professionals, that future is AI-driven, real-time, and risk-resilient.

This article was based on my new book, Upping Your Game. You can purchase a copy of the book on Amazon.com.

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Embedded Compliance – The Future is Integrated

For compliance professionals, it is time we discussed the groundbreaking shift happening right beneath our feet: embedded compliance. Traditionally, compliance has been viewed as a separate, distinct entity within organizations, performing manual, reactive tasks often separate from the pulse of daily business. The DOJ tried to fight this siloed approach beginning in the 2020 Update to the Evaluation of Corporate Compliance Programs (ECCP) and running through to the 2024 ECCP. A siloed approach caused inefficiencies and frequently resulted in gaps in oversight that organizations cannot afford in our hyper-regulated, fast-moving world.

Embedded compliance flips this traditional script, creating a framework where compliance checks, regulatory adherence, and risk controls are woven directly into the operational workflows. Leveraging the powerful combination of API-driven solutions, artificial intelligence (AI), and RegTech tools, embedded compliance promises seamless integration, greater agility, and significantly fewer errors. Today, I want to articulate why embedded compliance matters, how organizations integrate it into their workflows, and the practical steps compliance professionals can take to champion and lead this transformation.

From Reactive Compliance to Real-Time Integration

Historically, compliance functions often resembled firefighters, who were called upon to extinguish compliance breaches after they were already ablaze. The traditional process was linear, reactionary, and manual: compliance teams would wait for business operations to complete, then audit and identify breaches, correcting mistakes long after they occurred. Such methods left organizations vulnerable, inefficient, and frequently scrambling due to regulatory breaches.

Embedded compliance fundamentally shifts this paradigm. It brings compliance checks into the real-time business flow, using automated systems to instantly flag, halt, or address potential issues before they can materialize into full-blown compliance problems. As Andrew McBride succinctly noted, compliance is no longer separate—it’s seamlessly integrated into business processes facilitated by API-driven technology.

The Power of APIs and AI: Automating Compliance Checks

How exactly does embedded compliance work? It relies heavily on Application Programming Interfaces (APIs) and AI-driven tools integrated within existing systems to enforce real-time compliance. Let’s consider some prime examples:

1. Automated Policy Checks

A key element is embedding automated policy checks within workflows. Corporate policies and regulatory rules are encoded into a rules engine accessible via APIs. When an employee submits a transaction or expense request, the system instantly cross-checks against these policies. If an irregularity or breach is detected, such as exceeding spending limits or using unauthorized vendors, the system immediately flags or blocks it. Banks have adopted this method extensively, ensuring that products offered to customers comply with cross-border regulations at the point of sale. Embedding such checks drastically reduces the incidence of inadvertent breaches and the workload of compliance teams.

2. AI-Powered Contract Reviews

Another powerful implementation is in contract review processes. AI tools, integrated through APIs into contract management systems, scan contracts in real-time, flagging non-compliant language or omissions. Modern AI systems can instantly verify GDPR clauses, regulatory adherence, and internal policy compliance, offering corrections on the fly. Platforms like DocuSign use AI-assisted reviews to empower business users, ensuring regulatory and internal policy compliance even before a human legal team reviews the agreement, thus significantly speeding up the contracting process without adding compliance risk.

3. Real-Time Compliance Scoring

Companies today need continuous visibility into their compliance status. Real-time compliance scoring achieves this by dynamically assessing operations against regulatory standards or risk models. Cybersecurity platforms, for instance, can continuously update an organization’s compliance status against benchmarks like PCI DSS or ISO 27001. Likewise, financial institutions apply this approach to anti-money laundering (AML), using automated systems that score transactions against risk models and halt those flagged as high-risk, ensuring AML compliance on the fly.

4. Policy Review and Continuous Update

Embedded compliance also transforms how compliance policies are developed, reviewed, and refined. AI-driven solutions synthesize real-time feedback and employee queries into valuable insights, ensuring policies remain current and relevant. Automated tracking and analysis allow compliance professionals to swiftly identify problem areas, triggering targeted updates, training, and internal communications that foster a robust compliance culture.

Practical Lessons for Compliance Professionals

As compliance shifts from a manual, reactive function into a proactive, integrated approach, the role of compliance officers is undergoing a profound evolution. Here are five practical lessons compliance professionals must embrace to champion embedded compliance successfully:

Lesson 1: Embrace Technology as an Enabler, Not a Replacement

AI and automation are critical tools that free compliance professionals from repetitive, manual tasks. However, these technologies augment rather than replace human judgment. Professionals should retain oversight, interpret AI-generated alerts, tune automated models, and handle nuanced decisions that technology alone cannot navigate effectively.

Lesson 2: Design Compliance into Processes from the Start

Compliance must not be a postscript; it needs to be embedded from the inception of any business process. By collaborating closely with product development, operations, and IT teams, compliance professionals ensure regulatory and policy compliance is integral from the outset, preventing costly and disruptive corrective actions later.

Lesson 3: Leverage APIs and Automation to Reduce Manual Work

Compliance teams should proactively identify manual, repetitive compliance tasks suitable for automation via APIs or Robotic Process Automation (RPA). By automating these routine tasks, compliance officers can focus on higher-value activities such as strategic oversight, risk assessment, and complex investigations, maximizing efficiency and accuracy.

Lesson 4: Maintain Data Quality and Tackle Silos

Embedded compliance effectiveness depends critically on data quality. Compliance professionals must champion initiatives to improve data accuracy, consistency, and integration, ensuring that automated checks and AI-driven analyses rely on trusted data sources. Breaking down data silos is essential; an integrated data landscape strengthens the effectiveness and reliability of compliance efforts.

Lesson 5: Champion a Culture of Compliance and Train for Adoption

Finally, embedding compliance successfully requires widespread adoption and cultural buy-in. Compliance professionals should take active roles as educators, clearly communicating the benefits and functions of embedded compliance systems. Regular training, openness to feedback, and continuous improvement ensure frontline employees adopt and value embedded compliance, making compliance everyone’s responsibility and elevating the organizational compliance culture.

Shaping the Future of Compliance

Embedded compliance marks a significant departure from traditional compliance methods. It presents an exciting opportunity for compliance professionals to become proactive, strategic architects of integrated, real-time compliance solutions.

In this brave new world, compliance officers no longer merely enforce rules; they actively shape business processes, data integrity, and technological innovations to safeguard their organizations. By embracing APIs, AI-driven solutions, and the principles of compliance by design, compliance teams can help their organizations navigate regulatory landscapes with unprecedented agility, effectiveness, and efficiency. The future of compliance is integrated, proactive, and embedded. Are you ready to lead your organization into this transformative era?

This is taken from the new book Upping Your Game: How Compliance and Risk Management Move to 2030 and Beyond, available from Amazon.com.

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Blog

Upping Your Game – Compliance Moves into the 2030s

On February 10, 2025, the Trump Administration suspended investigations under and enforcement of the Foreign Corrupt Practices Act via Executive Order. Many compliance professionals have since wondered what this will mean for corporate compliance programs. Hui Chen, in a blog post entitled Pause in FCPA Enforcement: Crisis or Opportunity?, said, “Many in the compliance world have expressed lament, concerns, and anger. Understandably so. This may feel like an existential crisis for an industry so dependent on enforcement as its raison d’être. Yet, in every crisis, there is an opportunity. This is no exception.” She stated, “We will have the opportunity to find out which companies do not believe they need to engage in bribery to be competitive. But we will also see companies recalibrate their risk tolerance not because the door to foreign bribery has been wedged open, but because their past fear-driven strategy resulted in a sometimes overly narrow view of corporate risk and responsibility in this space.” She listed three key areas to start, the third being “it’s time to up your game.”

I agreed wholeheartedly with Chen. Inspired by Chen, I wanted to write a book for compliance professionals about how they could think through ‘Upping Their Game’ using currently existing Generative AI (GenAI) tools to improve their compliance programs dramatically. It all starts with the precept from Carl Hahn, “To me, the animating reason for our compliance program was to deliver business value. And that was my proposition on day one. It is a positive business-forward proposition based on returning on investment, returning value to the business, being part of the business strategy, enabling the achievement of strategic goals, and enabling the company to successfully deliver to its customers, investors, stakeholders, and employees.” As compliance professionals, it is critical to recognize that this moment is not merely about incremental improvements. The Trump Executive Order brings to the compliance profession a rare inflection point where revolutionary technological advancements, if harnessed strategically, can elevate our profession to a new level of effectiveness, efficiency, and organizational value.

Once reliant on manual oversight, reactive reporting, and periodic audits, compliance monitoring is evolving into a proactive, real-time capability empowered by sophisticated AI technologies. Compliance professionals historically functioned as gatekeepers, viewed as necessary but inconvenient barriers to business velocity. But now, driven by AI, compliance stands poised to shed that restrictive image, embedding directly into core operational workflows and thus shifting from gatekeeper to integral business partner.

Today, the cutting edge of compliance is driven by two primary strands of AI: predictive analytics, leveraging machine learning, and GenAI. Each has distinct capabilities, but combined, they represent a powerhouse able to address the vast majority of traditional compliance challenges and emerging risks. At its core, compliance seeks to identify, manage, and mitigate risks. Traditionally, this has meant looking backward, investigating past issues, and reacting to problems after they occur. AI fundamentally shifts compliance from this rearview mirror perspective to a forward-looking, predictive posture. Machine learning technologies empower compliance officers to train AI models on vast quantities of historical data, teaching systems to recognize patterns and indicators that suggest elevated risk in real-time.

Today, a compliance officer can use predictive analytics to tag transactional data by risk category, identifying potential bribes, improper payments, fraud, conflicts of interest, and sanctions violations. With these capabilities, compliance teams can proactively identify, isolate, and remediate issues before they escalate, significantly reducing organizational exposure and regulatory risk.

This shift from reactive to proactive risk management also enhances compliance agility. Organizations equipped with AI-powered monitoring can swiftly pivot to address new regulatory developments or emerging business risks. Because AI can integrate and analyze data in real-time from diverse sources, such as financial records, employee communications, operational metrics, and third-party data, the organization is positioned to respond to regulatory inquiries swiftly, accurately, and effectively, thus greatly enhancing compliance resilience.

AI offers a transformative capacity to integrate compliance directly into essential business processes by embedding compliance directly into an organization’s operations. Andrew McBride’s approach is termed the “Holy Grail” for compliance professionals who seek to seamlessly embed compliance responsibilities within operational workflows, enabling employees to carry out compliance tasks without interrupting their regular business activities.

For all these reasons and more, I am thrilled to announce the publication of my latest book, Upping Your Game: How Compliance and Risk Management Move to 2030 and Beyond. The compliance function is uniquely situated to lead the management of risk going forward, and in this book, I provide every compliance professional with key tactics, concepts, and strategies to move forward with GenAI today to answer the call to Up Your Game. Each chapter is dedicated to one area of a compliance program: risk management, third parties, training, chatbots, and embedded compliance. I provide key lessons for compliance professionals in each chapter and a case study on how one or more companies have created GenAI tools that can be adapted for compliance. Each one of these strategies meets Hahn’s precept to enhance business value.

I  interviewed some of the top thinkers on GenAI in the compliance field for this book. Contributors included Vincent Walden, CEO of konaAI, a global, AI-driven technology company focused on anti-fraud, anti-corruption, and compliance risks. Matt Galvin, co-founder of Gentic Global Advisors. Carl Hanh, co-founder of Gentic Global Advisors. Dr. Hemma Lomax, Deputy General Counsel, Vice President, Global Head of Ethics and Compliance at Docusign. Jag Lamba is the founder and CEO of Certa. Eric Sydell is a co-founder and CEO of Vero AI.

I hope you check out the book and use it as a basis for Upping Your Game going forward. KonaAI, a leading data analytics firm, sponsored this book.

You can purchase a copy of the book on Amazon.com.

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Compliance and AI

Compliance and AI: Harnessing Generative AI for Compliance: An Interview with Eric Sydell

What is the role of Artificial Intelligence in compliance? What about Machine Learning? Are you using ChatGPT? These are but three questions we will explore in this cutting-edge podcast series, Compliance and AI, hosted by Tom Fox, the award-winning Voice of Compliance. In this episode, Tom is joined by Eric Sydell, co-founder and CEO of Vero AI, to discuss the intersection of AI and compliance.

Eric shares his unique journey from industrial psychology to HR technology and ultimately to the realm of compliance through AI. They explore how Vero AI utilizes generative AI to analyze and interpret vast amounts of unstructured data at scale, such as text, video, and imagery. Eric emphasizes that AI provides a scalable solution for compliance processes, reducing manual labor and increasing efficiency.

Eric discusses the importance of AI governance in compliance, particularly in light of emerging standards like ISO 42001 and the EU AI Act. He introduces the Vero AI’s Violet Impact Model, which provides a comprehensive framework for evaluating the impact of algorithms and complex systems. The conversation covers practical applications of Vero AI in corporate procurement and risk management, highlighting how the tool can assist compliance officers in continuously monitoring and improving their compliance programs. Eric concludes by explaining how businesses can reach out to learn more about implementing these advanced AI-driven solutions.

Key highlights:

  • Generative AI and Unstructured Data
  • AI in Compliance and Predictive Models
  • AI Governance and Monitoring
  • The Violet Impact Model
  • Vero AI in Risk Management and Procurement

Resources:

Eric Sydell on Linkedin

Vero AI

Tom Fox

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