Africa Risk-Reward Index
-
SearchLogin
AI in compliance is here. It's embedded in many organisations’ daily operations, from automated contract review to advanced anomaly detection. Regulators know that while AI can supercharge compliance functions by enhancing detection capabilities and automating resource-intensive tasks, it can also amplify risk. Organisations adopting AI-driven compliance tools for continuous monitoring, fraud detection and predictive analytics must deploy these tools responsibly and effectively.
The US Department of Justic (DOJ) has clarified that, to the extent that a business uses AI to achieve its business objectives, it expects that business to achieve its compliance requirements. DOJ’s guidance also underscores AI’s dual role as a compliance enhancer and a potential risk amplifier. For compliance officers, the path forward involves balancing innovation with accountability, transparency and a commitment to ethical design.
By proactively addressing AI’s key risk areas – bias, misuse and data privacy and cybersecurity vulnerabilities – compliance programmes can mitigate pitfalls. Strong governance frameworks, continuous monitoring, and regular training ensure that AI-enabled compliance tools add value to a company’s compliance function. As technology evolves, compliance teams’ risk assessments, oversight mechanisms, and internal controls must adapt to keep pace.
To responsibly and effectively deploy AI resources, compliance leaders should consider and plan to mitigate three key risk areas.
Moreover, regulations like the EU’s and U.K.’s General Data Protection Regulations and the California Consumer Privacy Act impose strict rules for handling data and protecting individual privacy. AI-enabled compliance programmes must account for the treatment of sensitive data – both at rest in their systems of records and when used by the AI tools and the compliance team.
When used well, AI revolutionises compliance activities. Real-time transaction monitoring, predictive analytics for high-risk deals, and advanced analytics for third-party due diligence are all in practice today. AI excels at automating tedious tasks – like screening huge vendor datasets – freeing compliance teams to focus on more strategic tasks.
For this reason, decision-makers should resist deploying an AI solution for AI’s sake or to keep up with business leaders’ wish to follow the trend. Instead, they should insist on thoughtful, bottom-up implementation plan that aligns with specific compliance objectives.
AI tools cannot succeed without a robust governance framework. Cross-functional groups must oversee and build governance structures to guide AI strategy, model development and performance metrics. These governance structures should define:
In the event of a potential corporate compliance programme evaluation, a strong governance framework will answer questions that the recent US Department of Justice (DOJ) guidance directs prosecutors to ask, including each of the following:
Regulators and stakeholders—many of whom are not AI experts – will ask for explanations of AI-driven decisions. “Black box” models – where data scientists and AI experts struggle to explain how a model reached a conclusion – will not fare well under scrutiny during an external investigation.
Balancing the power of sophisticated AI capabilities and the need for transparency demands the attention of compliance leaders. Simpler, more interpretable models will often enhance compliance without sacrificing accountability.
By design, AI evolves rapidly. Today’s well-tuned model could be tomorrow’s added risk vector if underlying datasets or business processes change. Compliance teams must include AI risk assessments in their existing ERM processes. These assessments will quickly identify and mitigate new vulnerabilities – like shifts in data sources or biased outputs.
Compliance officers, in-house counsel, finance team members and information security teams need a foundational understanding of AI’s capabilities and limitations. A high-level overview is not enough.
Team members – including executives – must know which systems rely on AI. They must have enough technical fluency to spot red flags and know how to escalate their concerns appropriately within the organisation. Board members and C-suite leaders must appreciate the value and risks of AI and balance the resources allocated to manage risk with the resources allocated to realize business value.
As AI matures, regulations change in its wake. Though regulations struggle to keep pace with AI, global regulators are already implementing AI-specific legislation. New rules will shape how AI systems must be designed, monitored or disclosed.
Multinational companies must track changes across the global enforcement ecosystem and update their compliance programs accordingly. Regulators’ current emphasis on privacy, transparency, and auditability will not likely change. Consequently, forward-thinking organisations can build or buy AI tools that can support future regulatory shifts that require greater, or different, disclosures or protections.
AI will move more to the forefront of compliance programmes over the next five years. It will offer deeper insights and foster faster response times. Acting now to align AI with legal and regulatory standards will position organisations to harness this technology’s potential while safeguarding them from emerging risks.
The hype that often surrounds new tech can cloud judgement. Rather than racing to not be left behind, professionals must manage these adoption steps sensibly. By staying vigilant, flexible and informed, compliance leaders can integrate AI tools while fostering a culture of integrity and trust – today and into the future.