The proportion of effort an enterprise allocates to Governance, Risk, and Compliance (GRC) across all functions varies by industry, regulatory demands, and risk exposure.

Generally, for enterprise-level businesses, GRC operations are distributed in the following proportions:

These percentages vary based on factors like industry (e.g., heavily regulated sectors like finance or healthcare spend more on compliance), company size, and digital transformation levels. For example, Legal and Compliance operations for main sectors like banking/finance or healthcare can proportionate up to 25 -30%.

With businesses scaling globally, regularity compliances are also becoming more and more complex due to an increase in highly fragmented and industry-specific regulatory compliances nowadays such as the Health Insurance Portability and Accountability Act (HIPAA), North American Electric Reliability Corporation’s Critical Infrastructure Protection (NERC-CIP), Payment Card Industry (PCI) Security Standard, among others.

As the operational workloads have increased due to global business expansion, the traditional approach by businesses to compliance management—reliance on manual tracking, self-interpretation of dense legal documents, along with delayed and labor-intensive reporting—is proving to be error-prone, cumbersome, and highly human resource-intensive.

Different departments within a company maintain separate compliance records, leading to data inconsistencies and miscommunications, increasing the chances of fault compliances. Adding to this, compliance professionals also often struggle to track new regulations, interpret them, and implement the necessary internal controls.

The direct consequences of non-compliance are severe, ranging from:

• hefty financial penalties
• reputational damage
• operational disruptions
• legal ramifications

As regulatory compliances continue to evolve in complexity, businesses need to adopt newer efficient means, such as Gen AI, to reduce human dependency and risk management.

With advanced capabilities, Gen AI holds huge potential to revolutionize the whole compliance management by:

• Automate regulatory monitoring by continuously aggregating legal data from multiple sources.
• Interpret complex legal texts using advanced NLP models.
• Predict compliance risks with higher accuracy using historical data and machine learning.
• Integrate with legacy enterprise systems to streamline compliance workflows.

This article offers insights into how Gen AI can transform regulatory compliance practices, along with key implementation challenges. Let’s dive into it.

How Gen AI Can Transform Regulatory Compliance

AI-driven regulatory Data Aggregation

“AI-driven regulatory Data Aggregation” means using AI to automatically gather, organize, and systematically analyze large volumes of regulatory data from diverse sources. We usually perform these tasks using “Web Scraping”.

Gen AI systems ingest regulatory data from multiple sources using automated web crawlers, such as specific government APIs, and legal document repositories.

This scrapped data can further be processed by Transformer-based NLP models (e.g., BERT, GPT, and T5) to extract relevant legal changes and categorize them based on industry relevance. “Vector-Based Document Representation” plays a crucial role here in transforming unstructured legal text into structured embeddings.

Lastly, with the power of ontology mapping, hierarchical relationships between regulatory clauses are identified, enabling automated cross-referencing between laws and internal policies.

Document Analysis and Interpretation

Regulatory compliance documentation is often lengthy, confusing, and in a legal luminary tone making manual interpretation slow, inefficient, and resource-intensive.

We can use Gen AI solutions powered with Natural Language Processing (NLP) and Natural Langauge Understanding (NLU) models to parse and summarize complex legal texts.

For example, Gen AI’s Named Entity Recognition (NER) is an NLP technique that identifies and classifies named entities in text. Basically, it can extract key legal terms such as obligations, penalties, and exemptions, automating the process of finding relevant entities in lengthy documents.

For example, NER can extract key compliance elements such as:

• Obligations (e.g., "All financial transactions above $10,000 must be reported").
• Penalties (e.g., "Failure to report will result in a $250,000 fine").
• Deadlines (e.g., "Regulation goes into effect on July 1, 2025").

Further, these “Summarization Models” can be used to generate concise and actionable summaries of industry-specific dense legal documents. One very beneficial use case of Gen AI is when its NLP is integrated with OCR (Optical Character Recognition) to process scanned regulatory documents into machine-readable formats. We can transform these processed documents into semantic formats, which in turn will help for searching specific information extensively in legal compliance documents.

All these abilities of Gen AI can be used to further develop compliance chatbots for compliance professionals to quickly ask regulatory questions, such as:

• “What are the AML reporting requirements in the EU?”
• “Which new FDA regulations affect drug approvals?”

Risk Assessment and Predictive Analytics

With the help of bulk data analysis and the predictive modeling of Gen AI, we can identify potential compliance issues before they occur.

We can avoid repetitive compliance issues, with built-in “Risk Models” where Gen AI automatically classifies risks based on historical compliance violations and logged enforcement actions.

Rule-based “Anomaly Detection” helps in identifying unusual activities, such as irregular transactions, unauthorized data sharing, or deviations from standard operating procedures (SOPs), that may occur indicating non-compliance (e.g., fraudulent transactions). AI promptly alerts the compliance teams to investigate potential issues before lawful regulators take hold of compliance regulations.

Along with this, Gen AI’s “Predictive Analytics” uses time-series models to forecast any future compliance risks based on regulatory trends and key risk indicators, lowering the risk profile of businesses.

These predictive models are trained on past internal enforcement actions, company-specific compliance records, and industry penalties.

Workflow Integration

Workflow integration is an approach for adding Gen AI in the pre-existing system itself, to automate defined business processes.

From a regulatory compliance view, Gen AI can be integrated into current workflows for compliance professions in the following ways:

• With Robotic Process Automation (RPA) for Compliance Tasks, where we can automate:
  • Compliance form submissions (e.g., regulatory filings).
  • Audit documentation (e.g., generating risk assessment reports).
  • Policy enforcement tracking (e.g., ensuring correct data retention procedures).
• Gen AI-powered Chatbots for Instant Regulatory Guidance
  • Employees can ask AI about compliance rules in real-time (e.g., "Can I share this client data under GDPR?").
  • Further, AI assistants can provide context-aware answers, reducing compliance queries to legal teams.

Also, having logged records for compliance runs is crucial for businesses to maintain transparency and comprehensive regulatory oversight. Gen AI is highly capable of creating automated “Audit Trails & Compliance Reports” dashboards in real-time for continuous monitoring and to get a bigger overview of performed compliance audits.

Use Case: Gen AI in the Construction Industry

In the following sections, we can look at the role of Agentic & Bionic use cases.

Problem:

The construction industry, being one of the most heavily regulated sectors, requires companies to comply with multiple complex regulations, such as:

• Zoning Regulations
• Building Codes
• Permit requirements (across states and counties)
• Permits and Inspection Scheduling
• Environmental Impact Assessment
• Energy Efficiency Standards
• Natural Disaster Preparedness
• On-site and Occupant Safety
• Soil and Foundation Requirements
• Accessibility Standards
• Electrical and Plumbing Codes

As mentioned earlier, there are several key challenges faced by compliance professionals:

Fragmented Regulations

Building codes and design standards often differ significantly between states, counties, and municipalities based on the jurisdictions.

Evolving Regulations

Regulations frequently change due to new safety mandates, climate policies, and technological advancements. Thus, it gets harder for compliance authorities to keep an active track of continuous regulatory updates.

Manual Compliance Processes

Many construction managers and legal teams still prefer the old way of doing things by manually tracking and interpreting compliance requirem

Thus, there is always a high tendency for human error and misinterpretation, leading to permit rejections, project delays, and legal liabilities.

These challenges are common in the construction industry and a single faulty compliance can have serious consequences such as;

• Project Delay,
• Financial Penalties,
• and Reputational Damage.

Solution:

A bionic AI system powered by Generative AI, Machine Learning (ML), and Natural Language Processing (NLP) can automate detect, flag risks, and assist project managers with complete transparency to compliance standards.

• Real-time Updates
  

  Since there are multiple sources of construction industry-related compliances, it would be otherwise hard for regulators to manually track and keep a record of all updated changes.

  An AI-driven built-in with automated web crawlers and APIs can pull compliance updates from legitimate sources like the International Building Code (IBC), National Fire Protection Association (NFPA), and Occupational Safety and Health Administration (OSHA), including specific local zoning laws.

  Any new notification from State and county permit offices for any zoning restrictions, safety requirements, and environmental impact assessments can be tracked and updated in real-time on the AI dashboard along with email triggers for compliance professionals, raising priority tasks to validate the updates in compliance.

• AI-Powered Regulatory Insights
  

  After real-time tracking, with advanced algorithms such as NLP-based text analysis, this AI system can be automatically used to summarize and interpret compliance updates.

  Also, as discussed earlier, the Semantic Search & Chatbots functionality will come in real handy here, allowing compliance managers to quickly query AI for specific compliance answers, such as:

  • “Does this project require seismic reinforcement under California law?”
  • “What are the ADA (Americans with Disabilities Act) accessibility requirements for commercial buildings in Texas?”
• Predictive Risk Assessment & Compliance Flagging
  

  The bionic AI system is designed to analyze risks and flag them based on priority for ongoing project plans and regulatory standards before submission. The risk models are also trained on past compliance violations to predict risks for new projects.

  For example, automated permit “Pre-Checks” can ensure all documentation meets regulatory criteria before filing. It would promote transparency and avoid any delays in the project approval due to faulty compliance.

• Integration with Construction Project Management Tools

  Gen AI within Construction Project Management Tools such as Autodesk BIM 360, Procore, and SAP can be integrated together to automate compliance management.

  For example, integration of Gen AI with project tools can be used for:

  • Blueprint approvals and design validations
  • Material procurement (ensuring environmentally compliant materials are used)
  • Safety assessments (ensuring OSHA compliance)

Overall, the system will achieve improved accuracy and efficiency with fewer chances of compliance issues while avoiding miscommunications. This will also lead to cost savings and promote business scalability options due to reduced errors and faster approvals.

Benefits of Gen AI for Regulatory Compliance Across Industries

Improved Accuracy

With a legal tone and a dense volume of texts, there are always chances of misinterpretations and ambiguity in regulatory compliance documentation. These dense and complex regulatory texts can be managed with Natural Language Processing (NLP) and Named Entity Recognition (NER) models to automatically extract and identify key terms like "must comply”, "penalties”, or “deadlines".

Also, Chatbot-based compliance assistance can enable employees to receive instant, AI-verified compliance guidance.

This automated approach will help reduce human errors due to wrongful interpretations and missed information, ultimately improving the accuracy of compliance management.

Time and Cost Savings:

Since, Gen AI is capable of web scrapping information automatically from the internet, along with summarizing a huge bulk of regularity text, it will highly save on time and manual efforts by compliance officers, reducing overall operation costs. Additionally, Gen AI can automate permit applications, reporting, and audit documentation, freeing legal teams from administrative burdens.

Scalability

Large enterprises need to follow compliance guidelines with country-specific regulations such as GDPR in Europe, HIPAA in the US, or PDPA in Singapore. With Gen AI models, we can accurately translate and interpret multilingual foreign regulations. This is helpful in reducing knowledge and communication gaps if a company wants to expand to new countries.

Legal compliance NLP models trained on localized regulatory datasets provide uniform regulatory adherence specific to region-based regulatory laws. Not to mention, AI also continuously learns and adapts to new regulatory changes and updates compliance protocols dynamically.

Proactive Risk Management

Gen AI analyzes historical datasets of past compliance violations to predict potential regulatory breaches in advance. Whereas, active anomaly detection allows the systems to flag any irregular transactions, data privacy risks, and policy gaps even before they escalate. The additional real-time dashboards with active alert notifications allow compliance managers to actively work on flagged issues, before sending for audit.

Challenges and Considerations

Gen AI offers significant advantages for regulatory compliance, including enhanced efficiency and risk predictions, but its implementation comes with specific challenges that require thoughtful consideration before active rollout.

Data Privacy and Security

AI models need to be trained and handle sensitive data such as legal, health, and financial data, requiring strict data encryption, access control, and GDPR compliance.

Strict data governance and regulations must be in place to ensure any misuse of the company’s data. For this, a federated learning approach can be used to train AI models without exposing sensitive datasets.

Continuous Learning

One major issue of Gen AI is to feed it with high-quality regulated data for continuous learning. Gen AI’s effectiveness in performing compliance automation depends on its continuous training and access to high-quality. Since compliance systems have been working in silos, gathering quality data could pose a challenge for AI models.

Bias and Fairness

The current issue with most of the Gen AI models is that they are trained on historical data, which could have some factor of unintentional biases that can influence AI-generated outcomes. This potentially builds up to biased or unjust decisions.

Additionally, Gen AI models are known to occasionally produce “hallucinations”. They occur when an AI model produces incorrect or misleading output that is factually incorrect but looks reasonable without fact-checking.

This needs to be taken care of, especially in workflows requiring compliance regulations where accuracy is paramount.

Another very crucial thing in compliance management is transparency. Unexplained AI outputs (i.e. black boxes) that don’t explain the decision-making process of an AI model, bringing transparency issues while defending to regulators.

To avoid this, some form of human oversight is necessary to validate AI outputs and ensure compliance accuracy.

Integration with Legacy Compliance Systems

Legacy compliance systems—such as ERP (Enterprise Resource Planning), GRC (Governance, Risk, and Compliance) platforms, document management systems, and custom-built regulatory tools—have been the backbone of compliance operations for decades globally.

Integration of Gen AI in legacy compliance systems involves some key challenges companies need to address, such as:

• Since the whole system will be rebuilt, integrating Gen AI in the pre-defined workflows and within existing infrastructure is going to be expensive, time-consuming, and disruptive to business operations. Also, the transition to Gen AI workflow needs to be smooth, requiring enough employee training beforehand.
• As businesses use multiple systems (e.g., policy management tools, legal databases, risk assessment platforms) for compliance management, the regulatory data is often isolated within teams. Thus, AI integration must unify disparate compliance datasets into a centralized and intelligent compliance framework. Again, since many industries are used to undergoing compliances manually (due to high human dependency), the legacy systems lack data-sharing ability due to the absence of digital API infrastructure.
• Also, data needs to be regulated and governed before feeding it to the training of the models for legacy system integration.
• AI models need to be explainable and auditable since many lawful authorities are mandating digital records for compliance audits, ensuring regulators can verify how compliance decisions are made.

Scaling generative AI for enterprise-wide compliance initiatives is often resource-intensive. Apart from this, a well-structured change management approach is also necessary to overgo a transition to Gen AI-powered systems for employees. It includes comprehensive technical training, and active employee engagement, to facilitate a smooth AI adoption process within compliance teams.

By proactively addressing these challenges, our company's Gen AI solutions are designed to help businesses across industries, to revolutionize the way the compliance industry works. We provide tools that ensure accuracy, enhance scalability, and promote predictive risk management.

Request a free demo with our experienced Gen AI specialists today, and get insights on how we can streamline your compliance processes and drive operational excellence.