Originally published in Forbes.

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According to the Bureau of Labor Statistics, the demand for actuaries is projected to increase 24% from 2020 to 2030 — much faster than the average profession. For insurers who are already strapped for actuarial resources, this statistic is a sure source of anxiety and raises a burning question: Who is going to fill those positions?

Simply put, demand for actuaries is growing — and the supply is not keeping up.

Increased visa restrictions and the emergence of equally attractive jobs in similar fields like data science and computer science mean that insurers are already struggling to find the actuaries they need to get the job done. With ongoing complex regulatory-driven projects and an increasing demand to generate better insights for the business, this issue is one that insurers must address as quickly and efficiently as possible.

Insurers must automate a significant amount of the actuarial workflow in order to keep up with demand, reduce their costs and properly leverage the actuarial resource they already have. Actuarial automation provides an opportunity for them to do so, starting with the highly manual and resource-intensive processes they're required to do like the experience study analysis or model migration.

There simply aren't enough actuaries — and this won't change.

The emergence and growth of lucrative, flexible careers in data science and computer science offer attractive alternatives to many who would traditionally have gone down the actuarial career path. According to the Bureau of Labor Statistics, average salaries for all three professions all sit within a similar bracket, with the starting salaries for both data and computer science jobs quickly gaining on those for starting actuaries. It doesn't hurt that both data science and computer science don't involve the nearly decade-long process required to become a qualified actuary.

This also doesn't include the increasing opportunity for new actuaries to take their talents down a more nontraditional route, either moving into more senior, versatile roles within insurtech companies or into entirely different fields like climate risk analysis or consulting.

These competing career paths, coupled with an estimated 24% demand increase for actuaries, are a serious problem for insurers, particularly within the life and health insurance industries.

Actuarial teams are already under significant strain.

Increasingly complex regulatory and compliance requirements, as well as the need to gain deeper data analytics and insights in order to compete in the market, mean existing actuarial teams are short-staffed as it is. Difficult and restrictive visa requirements in most mature markets mean it's getting harder and harder for insurers to bring in actuarial resources from abroad to address their existing shortage.

In addition to struggling to get the work done, junior actuaries spending less time in their roles forces senior actuaries to take on junior-level work. This costs insurers significantly as the higher-value, cross-functional work and insights they could otherwise provide are lost, and actuarial teams and data become increasingly siloed.

Insurers must prepare to automate the actuarial function as quickly as possible or risk falling behind.

It's no secret that one of the leading causes for the strain on insurers' actuarial resources is the legacy systems and processes commanding much of their time and attention. These legacy actuarial systems are typically over 20 years old and are native to on-premise infrastructure that is expensive and nonscalable. They are a source of technical debt and a handbrake to wider digital innovation. These processes, created around legacy systems, are manual and time-intensive and they leverage the bare minimum of the actuarial skillset — making them a prime target for automation.

Automation, however, requires careful preparation and intention for insurers to get it right and gain the maximum benefit. Before beginning the automation process, here are some things they must carefully consider.

• Where is the biggest drain on actuarial resources, and how complicated would it be to automate?

• Set clear intentions. What specifically does the team want to achieve through automation? How will success be measured?

• Automation can help remove data and information siloes. Are there ways to begin identifying and closing those gaps before automating?

• Once certain workflows are automated, how will the actuarial workload be redistributed?

• Once a path toward automation is identified, who needs to be involved in implementation? What resources do they need to work with the new platform or software?

• What's the most efficient way to approach automation? Is it through internal resources and capabilities or through a partnership or third party?

• Is there an opportunity to improve the processes in addition to automating it?

For insurers that prepare their teams, reduce data siloes and are clear about their intentions, automating resource-intensive workflows can deliver more value from these processes and the insights they deliver. Actuarial automation enables insurers to accomplish more in less time, at a lower cost, while simultaneously delivering better insights for the commercial side of the business. Properly implemented, it can also enable actuaries to contribute to higher-value, commercially focussed work that directly benefits company strategy and decision-making.