The outcome: Deepened expertise and expansive use cases of generative AI
Over the few months since its adoption, Insight was able to fine-tune its generative AI solution from employee feedback. The investment in this accelerated adoption proved to be worth the risk — the organization has carved out efficiencies across the enterprise, with additional use cases being identified from teammate experimentation along the way. For example, in HR, the tool was used to analyze internal feedback surveys and aggregate the data in new ways, saving the team one to two weeks. Additionally, a sales team was able to leverage InsightGPT to categorize and sort a large set of data, saving more than 100 hours across the team. Another team in warehouse distribution used the private instance to automate a manual set of tasks, eliminating human error in the process while accelerating time to completion. The use cases didn’t end there and continue to be developed, from contract summarization to SOW creation that's reducing time and associated costs by 50%.
The work toward an enterprise generative AI tool also drove the development of Insight’s platform for generative AI use cases. Depending on an employee’s role, they may need access to different specialized models of the technology, such as for resume sorting that HR might leverage or email generation for sales. With this platform, decision-makers can determine who needs each interface and give them the ability to leverage those specially trained versions of the privately instanced generative AI.
The platform has been enhanced over the course of the rollout and has reached maturity to be leveraged by clients. Insight has also identified future projects to inject generative AI, including chatbots, contract writing and copilots for developers and other roles. By combining additional capabilities and integrations that have been released by Microsoft and other partners, Insight is rapidly expanding its generative AI footprint and expertise.