Essay by Sarah Lorraine Gwaltney, CDFM, Aviation Chapter

The taxicab industry in New York City has existed since 1897 and for most of that time, its traditional business model operated unchallenged and unchanged. In 2014, Uber came to NYC, was resisted by lawsuits which it overcame, and by 2017 Uber had surpassed the cab industry. Now they’re in business together and you can order a taxi from the Uber app. This is an example of thinking differently about the essence of the business. Uber owns no vehicles. Likewise, AirBnB, the world’s largest accommodation provider, owns no real estate. The distinct paradigm shift is that society is starting to see requirements differently.

Financial modernization has a similar story. For 110 years, there was relatively no change in the way we did finance. We constructed financial statements annually and management ran various departments. Then came the rise of modern Enterprise Resource Planning (ERP) which integrated all aspects of a business into a centralized system. The early 2000s saw the rise of data warehousing technologies. Then Data analytic solutions emerged and in 3-10 years grew from 100M customers to 2B. Within 5 days of launching, ChatGPT gained 1M users which grew to 1.15B users in 1 year.

Now we are seeing companies like [24]7.ai which leverage machine learning to provide targeted customer service. Breakthroughs in Generative AI and cloud-based solutions mean lots of data, lots of storage, and cheap computing. Opportunity has never been richer than it is now if we take advantage of the tools available to us.

The role Artificial Intelligence plays in the future of financial management is that of a useful tool, just like a calculator, a search-engine, or a macro are useful tools. With this tool comes endless possibilities for application within Defense Financial Management. The trick is stopping to think.

For example, traditional financial statements – they are outdated the moment they are created. Why do we do that? Aren’t financial statements essentially a glimpse at what’s going on within a business? Instead, if we already know our obligations and expenditures, we could be managing a continuous dashboard on our finances from live data i.e. like we do with Project Management Resource Tools (PMRT). The same concept could be applied to continuous auditing and FIAR compliance. Traditional audit is reactive. AI, machine learning, and data analytic tools make it possible to be proactive.

We could also be proactive with error detection within our datasets. Instead of an analyst hunting and pecking for single issues, predictive analytics could report the 25,000 transactions within a dataset that it deems to be incorrect. This would be useful for discrepancies in Government Purchase Cards (GPC), or in Air Force Foreign Military Sales Progress/Payment Disbursed Undelivered (PPDU’s), or overcommitments (OCOMS).

AI could also be applied to workforce planning using historical information. i.e. We know how many pilots the DoD employed in the past by date, missions flown, flight hours, etc. We can leverage this data to predict how many pilot billets the DoD will need 50 years in the future. Internally, we could leverage our current workforce’s annual appraisals and Individual Development Plans (IDPs) to identify candidates with desired skillsets and offer them strategic career opportunities which would benefit both the candidate and the DoD by getting the right person in the right job at the right time.

We need to liberate data so we can leverage it and take the steps necessary to centralize, standardize, and federalize data. Pivot and accelerate or we will be left behind. All tech companies are leveraging big data and using AI. The DoD should be no different.

Innovation is doing something differently, which is not always easy to embrace. The main barrier to AI adoption is culture. We have Frankenstein’ed together antiquated systems because it’s easier in the short term, and we have glossed over the crucial step of training our people to use these powerful tools.

People are at the center of business transformation. AI is not going to replace people, but people using AI are going to replace people who are not using AI. Therefore, we need to provide our workforce with early exposure and practical uses of AI tools for them to get familiar and gain experience. With this and further training we can upskill our workforce to better understand these tools and to recognize AI applications within their respective organizations and processes from the ground up. Then we would start seeing AI applications from all corners of the DoD and innovative solutions that would ultimately better support the warfighter and the mission of the DoD.

This essay was awarded the Meritorious Honor for the Essay Contest.

See all 2024 SDFM Award Honorees.

About the Author:

Sarah Gwaltney has a background in journalism and has prior enlisted military service as Security Forces for the U.S. Navy. She joined the Air Force civilian service in Nov 2021 and has since worked in AFLCMC’s Foreign Military Sales and now as a Cost Estimator for the Agile Combat Support Directorate.  She is a certified CDFM, SAPR facilitator, and was named the 2023 Trainee of the year for both AFLCMC and ASMC National.