One of the areas of business that has embraced GenAI is information management. GenAI feeds directly into the knowledge work automation movement, and many software tools have incorporated GenAI into as many functions as possible. In this blog, we’ll go over some applications of GenAI in information management, cover some challenges that GenAI poses in this area, and provide a few steps to take for companies interested in applying GenAI to their information management processes.

6 Applications of GenAI in Information Management 

Because GenAI is such a new technology, many of its applications and capabilities are yet to be discovered. Still, GenAI has already been extensively incorporated into information management. Here are the six main applications of GenAI in information management (so far!):

• Data capture: GenAI can capture data from meetings, emails, and videos in unique ways. With powerful speech-to-text abilities, it has virtually eliminated the need for manual transcription of videos (for closed captioning purposes, for example) or notes summarizing online meetings. This transcription capability lets businesses create searchable databases of verbal communications and notes, complete with automatically generated summaries of each meeting.
• Content creation: This may be the most widely publicized use of GenAI across the world. Tools like ChatGPT, Microsoft Copilot, and more can generate images, words, and even “voice” recordings. All of these outputs can be used for marketing purposes (remember to have a real person look over all marketing products before you publish them, though!).
• Information search: One of the most important applications of GenAI in information management is the enhanced search capabilities it enables. AI search engines (often found in document management software) allow users to search with their natural language—even in multiple languages! —instead of having to remember the exact title of the document. AI search systems can even suggest related content that the user may also need to reference.
• Document summary: Along with search capabilities, many document management systems now include GenAI tools that can summarize a long document and pull out specific information. For example, a user could ask AI about specific terms of a vendor contract instead of reading through pages of dense “legalese.” These summaries can save employees hours of pointless scanning through lengthy documents.
• Market research: One thing GenAI undoubtedly excels at is taking vast amounts of information and uncovering patterns and insights that would take large quantities of time to uncover manually. GenAI can analyze user behavior, customer preferences, market trends, and more, providing crucial insights to a company—both internally and externally.
• User experience: Lastly, GenAI can enhance employee experience, especially within document management software solutions. It does this by accelerating knowledge work automation efforts, eliminating tedious manual tasks, and putting relevant information right at your employees’ fingertips. By freeing up hours of time, GenAI allows employees to spend their time on higher-order, more fulfilling creative tasks.

 As you can see, GenAI is revolutionizing many aspects of information management; it will certainly continue to do so as the technology develops further.

3 Challenges for GenAI in Information Management 

While GenAI is a boon to information management for many reasons, it also comes with its own challenges. These challenges must be taken seriously—GenAI isn’t a magical solution to all of our problems! The problems with GenAI often have to do with the quality of data it’s implemented on. Here are a few forms of information that can cause problems when applying GenAI:

• Unconnected Information: In order for GenAI to be effective, it needs access to all relevant data within a business. This means, at bare minimum, that data silos must be broken down and software tools integrated. However, to maximize the use of GenAI, companies must create an information management plan that identifies data sources, flows, and governance rules. For example, connecting information may require implementing new software tools that collect data from across the organization.
• Chaotic Information: Even if data is connected across the entire company, GenAI can still fail if it’s fed chaotic information. Chaotic information can result from duplicate, outdated, disorganized, unclassified, or plain old erroneous data that still lingers in a business’s software systems. In order to get the most out of GenAI, companies must curate the content within their systems. This curation can include content audits, implementing metadata tagging, and creating content retention strategies. With a baseline of clean information, GenAI can automatically classify documents, extract metadata, and streamline filing processes.
• Confidential Information: One of the primary ethical debates surrounding GenAI is its use of confidential, copyrighted, or sensitive information. Without thoughtful strategy and solid safeguards around GenAI, it has the potential to create security breaches and publish sensitive information for all to see. Companies must implement strict access controls, permission structures, and data governance in order to ensure the security, privacy, and confidentiality of sensitive information.

GenAI can’t be applied to a company’s information management indiscriminately. For GenAI to be applied successfully, companies must carefully consider and curate the data that is fed into the AI tool.

How to Get Started with GenAI in Information Management 

So, once you’ve decided to use GenAI for information management, what’s next? Here are some steps that company leaders should take before and during the GenAI implementation process:

1. Assess current systems: One common mistake companies make when implementing AI of any kind is failing to assess what their employees actually need. The latest and greatest software won’t do any good if it doesn’t solve the problems that actually need to be solved. Begin your GenAI journey by documenting exactly what applications your company needs most.
2. Strategize: Once you’ve assessed the needs of your company, it’s important to start with the big picture: what are your goals for GenAI in your business? How will you measure success? What is your budget? How will you secure leadership and employee buy-in? What is the project timeline?
3. Outline data governance: As we mentioned above, it’s crucial for any business implementing GenAI to have a clear data governance plan. Consider what confidential information your company deals with and how it will be protected in the new system.
4. Create an action plan: Once you’ve considered the big picture, it’s time to choose the right GenAI-enabled software for your company’s unique needs. It’s also important to choose the right vendor or partner who can support you in the implementation process.
5. Train employees: Without employee buy-in and training, GenAI won’t help your business succeed. Schedule regular training sessions across all relevant departments and take employee concerns and questions seriously.
6. Implement ongoing testing: Be sure to test the system repeatedly (in a staging environment, for instance). Check on the measures of success you decided on earlier in the process. You may need to make adjustments as problems come to light during implementation.