Discussions around artificial intelligence (AI) have become ubiquitous over the past year, yet the technology is still shrouded in mystery and hype for many business leaders. Without enough education about how it works and what to expect, AI tools can easily become a costly flop.
While the potential benefits of AI are tremendous for finance functions, realizing those benefits requires a thoughtful strategy—one that all businesses can and should start to develop. The first step? Understanding AI fundamentals.
How AI Works in Finance: Basic Concepts
It’s easy to confuse common terms or use them interchangeably when talking about intelligent technology. Knowing the difference helps leaders understand the levels of maturity and nuance that are available through these tools.
AI is an umbrella term that refers broadly to machines mimicking human intelligence. AI excels at analyzing large datasets to uncover patterns that humans cannot easily detect on their own. In accounting and finance, it can automate tedious tasks like transaction processing while also augmenting human analysis.
Within AI, however, are more specific capabilities:
- Machine learning algorithms “learn” by detecting patterns from internal and external data sources. As they train on more data, the algorithms become better at making predictions and identifying insights. This technology may be used to flag anomalies in transactions, assist in financial modeling and more.
- Deep learning is a type of machine learning that’s modeled after the neural networks of the human brain. The “deep” in deep learning refers to the multiple layers of information processing, which allows this technology to identify even more sophisticated insights from larger sets of data.
- Natural language processing (NLP) focuses on analyzing and generating human language. NLP powers abilities like sentiment analysis, text summarization and language translation. For finance teams, NLP enables extracting key data from documents like contracts and emails. It also includes chatbots that can understand and respond to customers.
What Businesses Often Get Wrong About AI
Many businesses distrust or reject AI due to common misconceptions, which include chalking up AI to luxury or believing that it’s a replacement for human intelligence. But there are several truths about AI that will help set you up for success:
- Your competition is likely already investing in AI.
- Biased data produces biased results, which means AI is not completely objective. It relies heavily on healthy data inputs and human intervention.
- AI continues to evolve in assisting with high-level decision-making. Though many see its greatest impact on transactional tasks, AI will impact all facets of the finance function.
- AI needs human intervention and human judgment to be successful.
- It’s not just for major enterprises.
Broadening Skills is Key to Successful AI Integration
To use AI effectively, businesses need human expertise, not just technical wizardry. Finance and accounting professionals should learn about AI basic concepts and best practices, like how training data impacts algorithms. And they should be a part of the process—as much as the data scientists they rely on.
Understanding AI’s abilities and limitations combats unrealistic expectations and mistrust. Equipped with this knowledge, finance professionals can better collaborate with data scientists on developing truly useful AI tools.
Accountants and finance professionals should also consider other ways they can develop their skill sets to promote success in working with AI. Along with their domain expertise, understanding how to integrate different data sources will be key. Some statistics knowledge is also essential to further understand how these models work.
AI is not a concealed system. How it works is transparent and explainable, and its recommendations and insights can and should be scrutinized.
Education on AI Fundamentals Should Be Ongoing
AI changes fast. Leaders must make continual learning about AI fundamentals and emerging best practices a priority across the organization. Send team members to classes, workshops and conferences. Foster a culture of openness about what’s working and what’s not as you experiment.
AI literacy will evolve as the technology does. With patience, humility and learning, you can make AI a trusted partner. Build an AI strategy for your business that’s grounded in practicality and knowledge.