Practical ways to use AI to improve your organization’s finances
Sponsored by Ramp
AI has played a starring role in most functions over the past year, with countless products hitting the market promising to revolutionize how things are done. The finance department is no different; from automated fraud detection to intelligent chatbots providing real-time spend analysis, the technology certainly has the potential to relieve repetitive tasks from personnel.
However, while AI certainly has promise in finance teams, so far, the tangible impact of these products has been minimal. Eric Glyman, the co-founder and CEO of Ramp, told Bloomberg: “I think far more companies are marketing the use of AI, how their chatbot’s going to revolutionize the industry, than are truly trying to solve problems.
“I’ve never met a customer who said, ‘I just wish I could chat with my bank account, I would ask it questions and learn things.’ Instead, they tend to ask things like, ‘I’d like to pay less for this service I’m paying for, I’d like to automate my accounting and close my books quicker.’
“I think, often, if you see companies claiming AI but you can’t find real customers behind it, they’re not talking about how they’re integrating AI truly into the workflow, their software is probably ‘AI washing’.”
AI products that don’t solve actual pain points are examples of AI washing. In these solutions, automation might be too complex to set up or not fit for purpose, so accounting teams remain bogged down by basic operational tasks like chasing employees for receipts and coding transactions manually, while finance leaders are still tethered to stale data for important business decisions.
Many companies market AI without genuinely integrating it into their products’ workflows, and finance leaders may not become aware of this until after investing in it. As a result, they become skeptical over whether they’ll actually see any payback from their investment. In 2020, a BCG and MIT study found that only 10 percent of organizations saw “significant financial benefits” through increased revenue or cost savings after implementing an AI solution.
So how can finance teams select AI that’s actually worth their while? Before investing in a new AI-powered solution, it is wise to audit the organization’s needs. This way, decision-makers can be sure that the solution aligns with actual pain points and workflow requirements, preventing costly missteps and disappointment.
Auditing AI software for your finance team
- Will it speed up work?
A good place to start is thinking about how it can speed up work. AI has the potential to take on demand/revenue forecasting, anomaly and error detection, and financial reporting, to name just a few of its abilities. As a result, finance professionals can shift their focus to more value-added activities, such as strategic analysis and decision-making.
Mark D. McDonald, senior director of research at the Gartner Finance Practice, said: “Forecasting is a popular use case in finance departments because legacy processes are manually intensive and notoriously unreliable. AI excels at automation and improving accuracy.
“Many pre-configured software packages address common finance processes such as accounts receivable and accounts payable but be aware that use cases which address unique business needs, such as forecasting, will require some internal skills to build.”
Reporting is another common time-consuming area for finance teams. Generic chatbots can be marginally useful, but those actually trained on a company’s data can perform deeper analysis to provide valuable and actionable insights. Access to such insights will also be accelerated if the bot responds to natural language commands.
- Will it increase accuracy?
As Mr McDonald highlighted, another aspect to look out for in AI-enhanced finance products is how it can make things more accurate. Machine learning algorithms can identify and organize data from various sources in a single place, reducing the scope for human errors. In finance, this encompasses coding expenses, checking for inconsistencies in financial statements, and ensuring compliance with regulations. However, as before, a product that offers these features will only be a worthwhile investment if it aligns with the organization’s specific needs and challenges.
For example, if finance teams are suffering from long close processes, look for finance software that offers accounting AI. These days, expense coding can be automated with an algorithm trained on coding data from tens of thousands of accountants. Human errors in expense reporting could be eliminated with AI-scanned receipts that are instantly matched to transactions and suggested memos from each receipt’s context.
“Automating back-office workflows is a key to achieving efficiency gains across a number of areas, including accounts payable, accounts receivable, and internal IT services, such as helpdesk support,” said Randeep Rathindran, vice president of research in the Gartner Finance Practice. “In a cash-constrained environment, where margins are under pressure, the urgency to improve productivity in these areas is heightened.”
- Will it save money?
Finally, when auditing the company’s needs for an AI-enhanced solution, business leaders must consider where it could save money. Productivity increases could present savings indirectly, but there are potential direct benefits to be accrued, too.
AI has the potential to make vendor price comparisons for accounts teams, for example. Ramp’s finance AI offers price intelligence that helps finance leaders get the best deal by bringing the wisdom of the crowd to software pricing. Finance teams can upload software contracts and, powered by GPT-4, Ramp extracts pricing details and benchmarks them against millions of Ramp transactions. This provides visibility into software pricing down to individual SKUs and cost per seat, so finance teams instantly understand whether they’re getting a fair price.
AI can also catch out-of-policy spending by analyzing expenses against established guidelines and alerting finance teams in real-time, potentially saving the organization from resource-intensive compliance issues.
The demand for well-integrated, useful products in accounting and finance is there. A report from Accenture found that 84 percent of C-suite executives believe they must leverage AI to achieve their growth objectives. Ramp’s finance platform has been built with AI as a core component from day one to ensure that all its features address real challenges for finance professionals and help organizations scale successfully. To explore the AI capabilities of Ramp and witness the impact it can make on your business, schedule a demo with the team today.
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