Why AI and Automation Are Critical for Compliance Success in 2025

Introduction

Compliance leaders are facing unprecedented regulatory complexity, stringent enforcement requirements, and a flood of new rules in areas like cybersecurity, digital assets, and environment, social and governance (ESG). Manual processes for tracking, interpreting, and change implementation cannot keep pace with the rapidly evolving regulatory ecosystem. The future of Regulatory Change Management (RCM) lies in AI and automation that can drive its transformation from a reactive, manual process into a proactive, intelligence-driven one.

This was the key theme explored in our recent webinar I moderated with Anand Narayanan, Head of Regulatory Change Management and Business Program Oversight, SMBC Americas, and Shreyank Kamath, Senior Director, Product Management, MetricStream.

Outlined below are the key insights from our discussion.

Watch the full webinar

Compliance Complexity Is Becoming a Business Risk

The regulatory landscape is accelerating at an unprecedented pace with regulatory bodies across the globe rushing to keep pace with economic volatility, emerging cyber threats, and escalating geopolitical tensions. New trends like cryptocurrency and digital assets call for constant adaptation of regulations with a focus on cyber security. Compliance teams are now finding it difficult to manually filter and respond to relevant updates. Large organizations with operations across geographies have the additional challenge of continuously monitoring and adapting to multiple local laws. As a result, almost 77 percent of executives surveyed by PwC said that their company had been negatively impacted by compliance complexity across several high growth areas.

Smarter Tools for a Smarter Regulatory Future

• The sheer speed and volume of regulatory change means that companies need smarter tools to process, filter, and respond effectively. 52 percent of organizations are already using basic AI compliance tools while 9 percent have already implemented more advanced solutions for automated regulatory intelligence. And 71 percent of companies are tapping into generative AI to improve at least one part of their operations including risk and compliance.

But it is important to remember that AI cannot replace humans completely, its key role is to support and aid teams in two ways:

• Automation - Transform repetitive rule-based tasks like parsing alerts, matching to internal policies, updating repositories. It can also be used to summarizing lengthy regulatory updates and contextualizing them to an organization’s products and services. Automating these low-level tasks can free up teams and enable them to focus on more strategic matters.
• Augmentation – Generate insights, summaries or recommendations to keep a “human in loop”. In other words, leverage AI for quick intelligent insights that people can validate and subsequently act on.

Here’s how companies are using AI for RCM:

• Alert Filtering – Automatically sift through hundreds of regulatory alerts to select only the ones relevant for the organization.
• Accurate Summaries- Quickly create concise, context-specific summaries aligned with the company’s products and services.
• Applicability Analysis – Quickly identify whether a regulation or an update applies to the specific enterprise.
• Policy Mapping - Link an update to specific internal policies, controls, or risk framework
• Drafting – Draft policies or recommend text updates that can be reviewed by a compliance manager.
• Easy Scalability – Seamlessly handle increase in regulatory activity

We are already witnessing the emergence of even more advanced AI models like agentic AI that can automate and augment RCM processes further. MetricStream’s agentic RCM agent acts as an autonomous assistant that can independently:

• Read a regulatory change
• Analyze impacted policies, controls, and risks
• Propose updated text for policy sections
• Initiate tabletop risk assessments if needed

MetricStream’s agentic RCM agent can automate 18 out of 21 steps in a best practice RCM process, allowing teams to focus on more strategic functions

Powerful Ally with Potential Risk

AI’s greatest strength lies in its ability to process vast volumes of data in record time. But this strength is also cause for concern as data security, and privacy are strict regulatory requirements. Cyber criminals are also increasingly using AI powered strategies to launch sophisticated attacks on enterprises that are hard to detect or mitigate.

Organizations have to ensure robust cybersecurity practices to safeguard their data. Additionally, they have to ensure that their use of AI systems adheres to laws like GDPR, and the EU AI Act. Many countries are in the process of introducing new regulations on the use and disclosure of AI, and businesses must keep track and abide by these as and when they come into force.

There is also some concern around the lack of explainable AI, or tools to justify why an AI system made a certain recommendation. For example, companies want to know why a regulation is flagged inapplicable for their business, or why particular risk was prioritised for the team to assess.

Many organizations are also worried that their workforce is not completely ready for AI. There are lingering concerns about AI replacing jobs and some teams may perceive it to be a threat rather than a partner. It is important to reiterate that AI cannot be effective without ample human oversight and discretion.

Practical Guardrails for Responsible Use of AI

Governance, accuracy, transparency, and training are essential for successfully and securely managing AI deployments as well as for building trust. Many solution providers are working with customers and partners to build some practical guardrails around the use of AI in RCM and GRC processes.

• Confidence Scores- This can be derived by matching words used in the regulation vs the organization profile, or aligning the regulatory text with the products and services offered. A low confidence score acts as a prompt for users to dig deeper to understand the reasons and then refine the datasets used by the tool. Over time, this constant feedback will help the model improve its recommendations.
• Deviation Range and Evaluation Metrics- Organizations must also define the acceptable deviation range for any AI generated results and establish clear evaluation parameters for assessing the tool’s productivity effectiveness.
• Bias Mitigation - AI models reflect the data they are trained on. If the data has any bias, the same will undoubtedly impact the tool’s outputs. There must be measures in place to ensure unbiased outputs:
  • Strong governance practices
  • Monitoring, and testing of AI results against organizational standards
  • Feedback and human oversight- This is critical for quickly detecting skewed results and feedback can help refine models over time, reducing systemic bias.

Regulators are pushing for responsible AI adoption and may soon require companies to show their bias mitigation practices.

Scaling Into an AI-Enabled Compliance Value Chain

Companies interested in exploring AI powered compliance strategies should consider a phased implementation approach. They can start with high impact use cases like summarization or impact assessment to test the waters. This can then be followed by pilot projects or proof of concept where they test models, refine outputs, and get comfortable and confident with the technology. Once they successfully conclude the POC stage, they should gradually scale up by connecting targeted use cases into an AI enabled compliance value chain. They must also establish relevant metrics and track productivity at every stage. These insights will also help them reduce risk through the process.

AI adoption is at a critical inflection point where its moving from theory to mass adoption. The focus now must be on scaling AI across business lines to drive productivity and efficiency within RCM practices. But perhaps equally importantly, enterprises must focus on strengthening GRC processes to govern AI itself to ensure compliant, secure, and ethical use of this transformative technology.

Empower Your Compliance Team with MetricStream

At MetricStream, we empower compliance teams to confidently navigate today’s fast changing regulatory landscape with AI-powered intelligence, automation, and robust governance frameworks. Our AI-first Regulatory Change Management and Compliance Management products streamline compliance processes, reduce manual effort, and provide actionable insights, enabling your teams to stay ahead of evolving rules while ensuring accountability and transparency.

Watch the webinar

Request a demo to find out how MetricStream can empower your organization to strengthen resilience, reduce risk, and build trust.