Generative AI and large-language models (LLMs) are a powerful driving force in intelligent automation across Government. Combining rapid analysis with area-specific data, generative AI is able to create novel, relevant content at unmatched speed. The rise of generative AI marks a significant shift in the use cases for AI. Once limited to answering pre-defined prompts, AI can now be a creative partner, augmenting human workers as we solve problems, streamline workflows, and address mission challenges.

Use Cases for Generative AI

TechTrend has long been a leader in enterprise IT solutions for the Government Contracting space. Relentlessly agile and future-focused in methodology. And with strong Microsoft partnership capabilities, we’re proud to be at the forefront of generative AI GovCon applications.

The business cases for generative AI are myriad and offer endless opportunities to automate routine tasks, simplify workflows, and consolidate large amounts of information. The U.S. Federal Government website currently lists more than 700 possible AI applications – which TechTrend is amply suited to support.

In the near term, top use cases for generative AI include:

• Expedite compliance assessments and documentation creation. A multi-layered LLM can process large volumes of unstructured data, analyze compliance, and build out complex technical documentation. Human agents can review the resulting documentation or provide expert input across key sections rather than spend valuable time preparing lower-level documentation. For example, the Utah Department of Transportation uses generative AI to automate purchasing rights of way.
• Analyze large volumes of documentation. LLMs can process large volumes of documentation by using AI completions to summarize and highlight key points. Human agents can then synthesize the resulting information, drawing conclusions and making recommendations. For example, the Social Security Administration is using generative AI to process medical taxonomies against claims, improving the decision-making process and reducing fraud.
• Improve overall team efficiency. Teams trained in generative AI model training and prompting can work quickly and independently to solve problems, challenge responses, and identify gaps or opportunities. Sentiment analysis can also be applied to team communications to gauge overall performance and cohesion. MIT Sloan suggests that skilled workers using Generative AI can perform 40% better than without it.
• Support resource allocation. Generative AI can support workforce management approaches as well as project resource allocation needs, analyzing historical data together with external trends to forecast possible scenarios. For example, generative AI might deliver insights from geospatial data by using AI vision to code tags to image data. This could prove invaluable in crisis response scenarios such as earthquake monitoring.

This list is in no way exhaustive, but themes emerge around large volumes of data, complex analysis, complex document creation, and administrative load. Essentially, wherever these factors intersect, there’s a case for generative AI – and TechTrend is positioned to support your organization to step forward into that challenge.

Get More from your Data with TechTrend

Whatever your organization’s area of expertise, there is room for generative AI to improve your overall efficiency, accuracy, and competitiveness. Any task that is routine, repetitive, and mundane is an opportunity for disruption using generative AI. At TechTrend, we have the computing power, expert team, and powerful tech partnerships needed to position your organization for success in the quickly moving world of generative AI. To race to the forefront of your field with a smart and secure generative AI solution at any scale, get in touch today.