Currently artificial intelligence (AI) and machine learning (ML) is having a major impact in our personal, professional and business lives. With the introduction of phone assistants, data analytics and deep-thinking AI and ML is gaining momentum.
In terms of accounting and finance, is AI & ML a gift or curse for us? The answer largely depends on two key variables:
- business efficiency
- business insights
It also depends on where you, your business, industry fits on the low & high spectrum of these variables.
What is business efficiency and insights?
Business efficiency is having defined, stable and scalable processes identified and measured. If you are high on this spectrum then you have solid business processes, internal controls and measurable & scaled systems.
Business insights is providing your team, business or industry key actionable insights or findings to help guide short- and long-term strategic planning and operational excellence. If your high on this spectrum you are viewed as a vital business partner that is helping guide and predict the future.
These two elements matter because AI & ML can be used to accelerate or have a multiplier effect on both variables.
What is the ideal balance?
The answer largely depends on resources, history and value perception of your accounting and finance team.
Having high business efficiency is vital to implementing AI & ML tools and technologies. When you have solid processes, internal controls and systems implementing AL or ML you’ll be able to focus resources on gathering insights & knowledge.
For instance, say your team has a solid collection or cash conversion process then you implement an AI technology that helps handle the tactical collection operations. Now, the people or other resources dedicated to the process can shift to providing business insights.
The goal of AI & ML is to shift your vital resources i.e. your people to high-value activities which are business insights, partnership and strategic planning.
Will AI & ML take my job?
I can’t tell you how many times during my public speaking, conferences, webinars, or podcasts where accounting and finance professionals ask me this question. My answer has always been consistent, which is, “If you are asking will AI or ML replace my job then you probably realize what you are doing is tactical, routine and doesn’t drive business efficiency or insights. So, yes it will.”
The real question smart and forward-thinking accounting & finance team should ask is, “How will AI & ML make my job easier so I can focus on producing higher business value?” This is the pivotal point that accounting & finance teams must realize about AI and ML. AI & ML will continue to help and take away the data analysis, data mining, tactical and other routine business processes.
How do I know if I am ready for AI & ML?
Step 1. Take a step back & put some deep thinking around where you, your team, business and industry fits on the business efficiency & insights spectrum.
Step 2. Identify those business areas that have high business efficiency. Then explore what AI or ML tools or technologies can help multiply your impact & value.
Step 3. Get business commitment and resources to invest in 1 or 2 of those technologies.
Step 4. Measure. Test. Validate. Learn. Repeat.
Step 5. Identify if these tools or technologies had an impact on increasing your business insights or helping shift resources.
Step 6. Continue to measure progress over time. Then move back to step 1.
The article was first published in Unit 4 Prevero Blog
Learn more about artificial intelligence and machine learning in FP&A
If you are interested to learn more about how artificial intelligence and machine learning are used in FP&A, please check out the insights from the AI / ML FP&A Committee.
The Global Artificial Intelligence / Machine Learning FP&A Committee was created in March 2018 with the aim to see how the latest developments in those technologies can influence modern financial planning and analysis (FP&A).
The Committee's members are senior finance practitioners who represent large organisations that already started experimenting with AI / ML in finance or implementing it. The core focus of the Committee is on the practical application of AI / ML e.g. leadership, people, roadblocks and change management focusing ultimately on benefits realization.