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:
- 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.
- 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.
- 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.
