Knowing when AI automation isn't right for your insurance brokerage

The conversation around Artificial Intelligence (AI) and Robot Process Automation (RPA) is becoming more and more prevalent within the insurance industry. This is because AI and RPA offer a lot of advantages to businesses, including time-saving, reduced repetitive tasks, streamlined processes and improved client experiences. However, it's important to keep in mind that every insurance brokerage is different, and these technologies are not a one-size-fits-all solution.

Five reasons to forgo an AI Investment

So, how do you know if AI and RPA are not the right solution for your insurance brokerage? Here is a breakdown of when it might be best to forgo AI implementation in your business:

1. You have optimal staffing levels

An adequately staffed team capable of managing current workloads effectively diminishes the immediate necessity for AI and RPA integration. While AI can enhance operational capabilities, its implementation should ideally complement, rather than replace, existing human resources. If your team is proficiently managing tasks without strain or overtime, investing in AI may not yield substantial returns in the short term.

However, if you find that you are facing staffing challenges and your team is overwhelmed and working overtime, then it may be time for you to consider freeing up human resources and lightening their workload with AI automation.

2. Long-term growth isn't a top priority

AI and RPA can be highly beneficial for insurance brokerages that aim to grow efficiently without compromising the quality of the client experience, and without overburdening their staff with a mounting workload. However, if your brokerage has no formal plans for long-term growth or is not actively pursuing growth opportunities, then AI may not be a priority if your current workload is manageable and is not expected to increase.

3. Employees time is not used for repetitive work

AI is great at automating tasks that are repetitive and follow a set of rules, which saves valuable human resources for more important tasks. But if your brokerage's workload is mainly made up of complex and non-repetitive tasks that require human judgment and expertise, the benefits of AI may not be as significant.

If your staff is unable to devote their time to work that requires human interaction, such as building client relationships, AI can be used to free them up from repetitive tasks. This allows them to focus on more valuable and important work, maximizing the effectiveness of human talent.

4. Costs outweigh the benefits

Conducting a thorough cost-benefit analysis is essential to assess the potential return on investment (ROI) of AI adoption. If the projected benefits do not outweigh the associated costs within a reasonable timeframe, it may be wise to delay AI adoption until a more favorable moment from a financial perspective.

However, AI implementation can also lead to a very high ROI in a short time. For instance, Quandri's Renewal Reviews capability automates the repetitive tasks of multiple individuals for a fraction of the cost.

5. Your organization is resistant to change

Introducing AI and RPA into the workplace often requires change management initiatives. Resistance to change and lack of buy-in from stakeholders can impede the successful adoption of AI technologies. If your brokerage's organizational culture is not ready to embrace technological innovations or lacks the willingness to change, you may want to delay AI implementation until a culture of innovation and adaptability is cultivated.

Assessing your brokerage's AI-readiness

The potential benefits of adopting AI in insurance brokerages are immense. However, it is crucial to assess your business requirements and make an informed decision about its implementation to ensure that it aligns with your strategic objectives. To do so, take into account factors such as staffing levels, growth projections, the type of work that consumes employee's time, and the expected return on investment. By carefully considering these factors, insurance professionals can make a well-informed decision about whether or not to adopt AI in their operations.