In the first two blogs in this series, we discussed why AI generates so much excitement and the basics of artificial intelligence. In this blog, we begin to drill down into the impact AI will have on the brokerage industry. Where can we expect artificial intelligence will make an impact? What should we look forward to? PlanYear was founded by a group of benefits consultants and technologists who had long struggled with the unique challenges of running a brokerage. Managing benefits programs for numerous employers presents considerable challenges. It entails a substantial workload, often characterized by tedious and manual tasks.
However, the recent advent of advanced AI technology has offered a transformative solution to this predicament. By harnessing AI capabilities, we can now address this multifaceted issue comprehensively.
The Manual Data Entry Problem
One of the core challenges in the brokerage industry lies in the extensive manual data entry required to run a benefits program. This process begins with the reception of insurance plans in PDF format from carriers, containing a multitude of data parameters. Human intervention is needed to review and subsequently input this data into spreadsheets repetitively.
Once the plan data resides within spreadsheets, various calculations and contribution models are applied. These results are then transferred to PowerPoint presentations for client review. Frequently, clients request adjustments, necessitating a return to the spreadsheet for recalculations, followed by another presentation update.
This labor-intensive and error-prone process not only frustrates those involved but also carries significant risks. A single data entry error can lead to extensive rework and potential client dissatisfaction. Furthermore, additional data entry is required for open enrollment presentations, benefits guides, and carrier sold confirmations, perpetuating the cycle of manual labor.
Compounding this challenge is the fact that approximately 60% of this workload converges around the January 1st deadline. Properly staffing for this surge is a delicate balancing act. Overstaffing for this period leads to excess resources during the remainder of the year, while understaffing results in an overburdened team prone to errors.
In the event of an error, client relationships and reputation are jeopardized, creating a lose-lose scenario. Despite the introduction of quoting tools, the primary issue remains the manual data entry process, characterized by its propensity for errors and inefficiency.
Historically, the only way technology could have solved the manual data entry problem required buy-in and deep integration with the carriers. However, expecting every carrier to develop and implement an API for seamless data exchange is a monumental challenge that has never been accomplished and therefore was not successful in solving the underlying problem.
AI: The End of Manual Data Entry
The advent of AI offers a solution to these problems. Through extensive training and the use of appropriate prompts, AI models, such as ChatGPT, have demonstrated remarkable proficiency in reading and interpreting insurance quotes accurately across various carriers. This capability eliminates the need for manual data entry.
Furthermore, AI can automate the calculation of contribution models and facilitate the transfer of data to benefits guides, open enrollment presentations, and carrier-sold confirmations without errors. This streamlined process simplifies data management and significantly reduces the likelihood of inaccuracies.
In essence, AI transforms the landscape of employee benefits brokerage, making data handling faster, more efficient, and less prone to errors. It effectively provides a cost-effective means of accessing advanced data processing capabilities, akin to having expert support within your marketing department for a nominal annual investment.
For those acquainted with the intricacies of the employee benefits brokerage industry, the promise of AI revolutionizing data entry processes is undoubtedly an exciting prospect. In Part 2 of this blog series, we will delve into how AI will reshape communication dynamics among employee benefits stakeholders.
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