Using AI in entity management: where to begin
Artificial intelligence (AI) in entity management is changing how professionals oversee their entity frameworks. If you’re responsible for entity management, the key to successful AI adoption, isn’t adopting all types of AI at once. A better approach is to understand which type delivers value fastest so that you can build a strong foundation for what comes next.
There are many different types of AI emerging, from Generative AI (GenAI) to Autonomous AI. If you’re a first-time user of AI in entity management, here’s what type of AI you should use in entity management first.
The main types of AI in entity management
At a high level, the most relevant AI categories for entity management include:
Generative AI (GenAI): Creates and summarizes content (e.g. reports, filings, insights)
AI Agents: Executes predefines tasks and analyses end-to-end
Autonomous AI: Operates and learns independently
Each plays an important role, but not all are equal when you’re just starting out.
A simple framework: which AI to adopt first
If you’re new to AI in entity management:
Start with Generative AI. Then scale into AI agents.
Here’s why.
| AI type | What it does | Best for | When to adopt |
|---|---|---|---|
| Generative AI (GenAI) | Creates content, summarizes documents, answers questions | Improving productivity and data accessibility | Start here |
| AI Agents | Executes tasks across workflows with some autonomy and decision-making | Driving efficiency and reducing manual processes | Next step |
| Autonomous AI | Operates end-to-end processes with minimal human intervention | Fully automated entity management at scale | Longer-term goal |
While autonomous AI represents the future of fully self-managing systems, most organizations see the fastest adoption by starting with using generative AI and progressing towards using AI agents, where automation and decision-making begin to work together.
Why GenAI is the best place to start
Generative AI is the most accessible and impactful entry point for entity teams. It helps you unlock the value of your existing data without requiring major process change. Examples of GenAI include ChatGPT and Claude, and it’s generally used to create new content, images, or data insights. Find out more about the different types of AI.
1. Immediate productivity gains
Entity management teams handle large volumes of documentation such as board minutes, entity records, filings, and compliance reports.
GenAI can:
- Summarize complex documents in seconds
- Draft reports, updates and communications
- Extract key information from entity records
Using GenAI to help you with routine tasks dramatically reduces manual effort and frees up time for higher-value work.
2. Low barrier to entry
Unlike more advanced AI types, generative AI:
- Requires minimal training to use
- Fits naturally into existing workflows
- Doesn’t depend on complex integrations from day one
It’s a practical way to build confidence with AI across your team.
3. Improves data accessibility
One of the biggest challenges in entity management is fragmented data.
Generative AI can act as a natural interface to your entity data, allowing users to:
- Ask questions in plain language
- Quickly find what they need
- Gain insights without technical expertise
This supports better decision-making across legal, governance and compliance teams.
4. A foundation for more advanced AI
Starting with GenAI builds:
- Trust in AI outputs
- Clean, structured data practices
- Internal momentum for innovation
These are essential before moving into more autonomous capabilities.
The next step: why AI agents matter for entity management
Once GenAI is successfully adopted by an entity management team, learning how to use AI agents is the next major leap. While GenAI creates and interprets information, AI agents act on it.
What are AI agents?
AI agents are systems that can:
Execute tasks across workflows
Interact with multiple systems
Trigger actions based on data or rules
Why AI agents are powerful in entity management
Entity management is inherently process-driven, making it an ideal use case for AI agents.
An agent can act as your “assistant”, and help with the following tasks:
1. Automate compliance workflows
AI agents can:
- Track filing deadlines
- Trigger reminders or actions
- Ensure tasks are completed on time
- Reduce the risk of missed obligations
2. Streamline multi-jurisdictional operations
Managing entities across regions is complex and resource intensive.
AI agents:
- Coordinate processes across jurisdictions
- Standardize workflows
- Reduce reliance on manual intervention
3. Reduce operational risk
By automating tasks and enforcing rules, AI agents help:
- Minimize human error
- Maintain consistency
- Strengthen governance controls
4. Enable scalable growth
As your entity portfolio grows, AI agents allow your team to scale without increasing headcount at the same rate.
Where GEMS fits: AI built for entity management
AI is only as effective as the platform it’s embedded in.
Computershare’s Global Entity Management System, GEMS™, is designed to bring together your entity data, workflows and compliance in a single system, creating the ideal foundation for both generative AI and AI agents.
Because GEMS provides a centralized source of truth and streamlined processes, it naturally supports AI-driven capabilities that enhance efficiency, control and decision-making.
How AI enhances GEMS
GEMS AI offers various features, including both GenAI capabilities and the GEMS AI Insights Agent.
GenAI capabilities:
Translate documents with AI Translate
Summarize records and documentation with AI Summarize
Speed up document updates with AI Compare
Reduce manual data population risk with AI Autofill
Get relevant tag suggestions when adding new documents with AI Document Tag
Find information quickly with AI search
AI agent capabilities:
Uncover risks across your entity footprint, flagging compliance issues before they become a problem
Ensure data integrity by scanning entity records for inconsistencies
Analyze entities when regulatory changes occur to identify any risks or gaps in your compliance
By offering both GenAI capabilities and the AI Insights Agent, GEMS helps you enjoy a smarter, more proactive approach to entity management. You can also create custom Insights Agents to support specific analysis needs. Your system doesn’t just store data, but actively helps you manage more easily so you can get a better understanding of it.
Overview: start with GenAI in entity management
If you’re starting your AI journey in entity management, begin with generative AI to unlock productivity and improve data access, and then build towards using AI agents to automate workflows and scale operations. It’s helpful to ground everything in one platform like GEMS, which offers AI capabilities that are specifically built to support entity management professionals with their work.
See GEMS AI in action
AI in entity management helps your team work smarter, move faster and stay in control. With GEMS AI, you can transform the way you manage your entities to improve data accuracy, minimize risk, and reduce time spent on routine tasks, so that you can focus on the work that really matters.
Book a free GEMS demo today
To see how GEMS and its AI capabilities can help you transform your organization’s entity management, request a demo and explore how the platform helps create more structure, visibility, and consistency across your entity footprint. With a hands-on onboarding process led by experienced experts, Computershare helps set your team up for success from the start and long after implementation.