New tech investments need to be evaluated based real results and CFOs can cut through the hype with these practical steps.
As CFOs begin a new year, many still feel a mix of caution and optimism. Businesses have shifted away from the “revenue at any cost” mentality that is prevalent in a high-growth market, and CFOs are challenged to make every dollar count and find ways to do more with less.
While technology innovations like artificial intelligence (AI) including generative AI and machine learning (ML) are top of mind for many businesses, new investments must be evaluated based on potential results that can help increase productivity, reduce costs, and improve overall business efficiency.
So, how can CFOs cut through the hype and make the right investments for their business needs? Below are some tips to get started.
Automate the Financial Fundamentals
Before diving into advanced technologies like AI, start with the simple automation of manual processes across accounting and finance functions. As finance teams face ongoing accountant talent shortages, automating time consuming manual processes can improve overall business productivity and help to attract and retain employees.
The automation of financial processes can help reduce manual errors and improve business visibility with more frequent reporting. Some areas ripe for automation include billing and payment processes. For example, an accounts payable (AP) automation application can leverage AI to help automate bill capture and match each bill to purchase orders and delivery receipts. When connected to an integrated enterprise resource planning (ERP) system, payments can also be sent out faster for approval and remittance. While accounts payable processes are traditionally time consuming and error prone, automation can help AP teams improve efficiencies that can help better manage cash flow, control costs, and maintain strong relationships with vendors.
By having visibility into real-time billing and account reconciliations, CFOs can make data-driven decisions based on cash flow and spend more time analyzing results. As automation helps improve the speed and accuracy of reporting processes, the resulting data will also be influential in training models and helping AI thrive.
Centralize Data and Train Your Own AI Models
Data is the foundation of automation and AI success. However, often times data resides in many different point solutions across a business. For example, a business may have individual systems for accounting, point of sale transactions, supply chain processes, ecommerce, and more. The complexity of managing a variety of systems can hinder both business visibility and productivity.
To maximize the value of data, businesses should consider an integrated solution like a cloud ERP system that can unify data and provide a single source of truth. This will help save time on manual data integrations, create greater data visibility and control across the business, and help ensure that your AI can be as effective as possible.
While large language models have generated tremendous buzz, models based on publicly available data have clear limitations when it comes to understanding the nuances of an individual business. For this reason, a business should leverage its own data to train AI models for internal use. In many cases, this will require the help of an AI vendor or a company that integrates AI into its systems. When evaluating options for investments, CFOs should work closely with CIOs and technical experts to ensure the security of the business’ proprietary data that is used to refine AI models.
Start Small and Encourage AI Experimentation
If a business is not yet ready to start training its own AI models, it can start small with generative AI embedded in applications. For example, a business can experiment with AI capabilities built into existing software such as a cloud ERP system. Functionality can allow businesses to gain AI-backed insights for intelligent risk predictions based on supply chain trends or intelligent item recommendations based on CRM activity. By leveraging one integrated system with existing AI features, businesses can increase operational productivity and personalize customer experiences.
A cloud data warehouse solution with advanced analytics powered by prebuilt AI models is another investment that can help finance teams gain strategic insights and drive growth. By automating analysis based on historical trends, businesses can leverage these solutions to find ways to improve operational efficiency, optimize forecasting, and identify new revenue streams.
While the number of possibilities for AI implementation may seem overwhelming, taking small actions now to experiment and test applications will set the foundation for bigger changes down the line. Even results that drive small efficiencies can create a competitive edge and help drive long-term change in the future.
Prioritize Employee Training and Skill Building
While investing and testing technology features can help experiment with AI, real value is limited if employees don’t know how to use it. To make the most of technology investments, CFOs should work with department leaders to understand the gaps between the capabilities of existing systems and how employees use them. Since AI is still an emerging technology and vendors continue to add new functionality, it’s important to prioritize training and skill building programs.
To build successful training programs, designate team leads who can partner with a vendor’s system experts and internal system owners to develop training initiatives for broader teams. Programs should focus on building awareness of system functionalities, role-based skills training, and new ways to leverage automation and advanced functionality such as AI.
Automation and AI have strong potential to help improve business efficiency and drive growth. While new technology may be intimidating, even small steps and implementations can help grow a business’ top and bottom lines. In the year ahead, CFOs should prioritize collaboration and education across their business to help maximize technology investments.
Sam Levy is senior vice president of growth and operations, Oracle NetSuite