AI has become a readily available tool for employers with a spectrum of high value use cases, including risk management. A recent poll showed that almost 50% of organizations are planning to introduce AI into their workplace incident investigations process within six months.
Consistent workplace investigations and case management can have a tremendous positive impact on your firm’s risk management. Inconsistent workplace investigations and case management can have the opposite effect, putting your organization at financial and legal risk. Inconsistencies can result in your company losing top-performing employees and candidates, earning a poor brand reputation for arbitrary discipline or policy enforcement, or having to allocate time, people, and cost to handle a lawsuit or EEOC complaint. That’s where AI comes in.
The advantage of case management software
Purpose-driven case management software adds consistency across cases to each workplace investigative step, including compliant intake, investigation management, and reporting. A centralized platform keeps all case information and documents in one place: Investigators can attach evidence files and supporting documentation to make sure nothing gets lost. Each case file also includes an audit trail of actions taken on the case, ensuring a team never misplaces information and can show proof of its process. Configurable forms and workflows keep team members on the same page, and form templates ensure documentation and reporting is treated the same way.
The software can also integrate reporting mechanisms and use email-to-case creation to help tackle reports quickly and uniformly. Users can set rules and track SLAs to ensure cases get actioned. Workflow assignment and automated notifications inform team members when they have an upcoming deadline. Auto-assigned tasks and reminder emails keep the team on track, reducing the risk of missed steps or bottlenecks.
How AI enhances the process
One ideal place to start using AI is case summarization. Robust, purpose-built, AI-assisted case management software lets workplace investigators streamline processes for more effective results and more insightful reports. This stage of a workplace investigation involves pulling together all the evidence, supporting documentation, and findings, then formatting to highlight the most critical details.
Gathering this information manually can be tedious, taking time away from other investigative tasks. Instead, an AI-driven assistant can spot organizational trends and help teams get ahead of risk, pulling the case information into a variety of formats. A preset template can be configured to include the case type, specific regulatory needs, stakeholder preferences , and the organization’s branding. A short or long-form summary can be generated in a rich text editor for easy review and editing as needed, such as any small additions or adjustments.
But the automated report isn’t just a case summary. It also includes relevant internal policies cited in the case, document attachments, and the date the report was generated. The process can be easily referenced in case of an audit or legal questions, and for long-term documentation.
Using an AI tool to summarize cases reduces several risks. It takes human error of the equation. Templates with built-in regulatory requirements decrease the chance of non-compliance fines. Even simply forgetting to include a case detail in the report is less likely to happen, as all sections of the file are included in the summary unless the investigator instructs the tool otherwise.
Keeping case data safe
The Number One question workplace investigators ask is “Will my case data be safe if I’m using AI?” Safety is critical in this role, given the sensitive nature of workplace investigations and the potential long-term risks associated with mismanaged information.
Deploying best practices can ensure AI is used in a way that protects sensitive information:
- Data storage and handling is done on secure, trusted infrastructure.
- Access controls for each case or piece of information carry over to the AI assistant.
- Data privacy requirements from HIPAA, GDPR, and other regulators are built in.
- Audit trails show who worked on a case, what they did, and when they did it, so everyone can see if a team member mishandled data.
- Data anonymization in the AI assistant protects individuals’ privacy.
These precautions ensure that data doesn’t fall into the wrong hands, and ultimately reduce an organization’s risk of a non-compliance penalty with data security regulators.
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