Harnessing AI in Finance - to unlock AI advancements, GBS and shared services teams need high quality data

Over the next year, two-thirds of Shared Services Centers are poised to debut AI-powered business intelligence and analytics and 70% have confirmed that working in collaboration with IT, they will be responsible for exploring the potential of generative AI solutions for the enterprise.

Shared services lead cost reduction efforts

Artificial Intelligence is a powerful technology for Shared Services Centers and can help them operate more efficiently. As pilot implementations and evaluations give way to adoption, Shared Services Centers have the opportunity to use AI to nail common use cases like improving service levels, ensuring process compliance, and reducing operating costs.

These debut AI deployments are arriving at a time when over 80% of shared services functions have become key support pillars in the enterprise’s core digital transformation agenda. Some 27% of shared services teams now occupy the company’s lead driver seat to reduce costs, according to the SSON.

Detecting duplicates: AI use cases in AP and AR

Let’s look at a couple of use cases for how shared services teams can succeed in the driver’s seat and use AI to boost efficiency and value creation in Accounts Payable and Accounts Receivable.

1. Detecting Duplicate Invoices in Accounts Payable

Traditional approaches to matching invoices can miss many types of duplicate invoices. Using AI solutions, shared services teams can detect both exact and “fuzzy” duplicate invoices to prevent duplicate payments to suppliers.

Read more: Catch duplicate invoices and streamline AP with the Duplicate Checker App

2. Safeguarding Against Duplicate Deductions in Accounts Receivable

To prevent revenue loss, detecting duplicate deductions is crucial. In this use case, AI algorithms can compare transaction data, invoices, and payment records to flag customers who have taken advantage of deductions more than once.
Discover more about what Process Intelligence can do for Accounts Receivable

Focus on processes first, work on AI second

Recognizing the AI opportunity isn’t the same as unlocking it, and many Shared Services Centers aren’t yet taking the necessary action on processes to make AI work for the enterprise.

When asked about the last time their department took active steps to optimize a procedure or process, finance and shared services leaders reveal process optimization is being widely neglected in their departments. Only 8% optimize processes on a continuous basis. Over three-fifths (62%) haven’t optimized a process in the last year, according to a 2023 global survey.

That means stalled progress for Shared Services Centers because the impact of AI is limited when it lacks a full understanding of how the business actually operates.

Feed AI the intelligence it needs with Process Intelligence

AI models inherit the limitations of the data they digest. So when shared services teams task AI with improving real-world scenarios, the technology will not go far if it doesn’t know how the business really operates. AI needs to speak the same language as the processes that power a business in order to generate knowledge and insights at scale.

Here’s how shared services can better harness AI. Business processes run through lots of systems — creating fragments of data at every step.By using process mining to pick up these breadcrumbs, shared services teams can visually reconstruct what’s happening in the process. Combining that information with other technologies – packaged up into Process Intelligence – AI has access to the data and the business context it needs to understand your processes end-to-end.

Find out more about making AI work for your enterprise here.

While still early in enterprise adoption, generative AI promises to play a significant role in how Shared Services Centers will operate and drive lasting value for the business. Taking advantage of the efficiency, accuracy, and scalability AI brings, Shared Services Centers can optimize routine tasks and enable better resource allocation for higher-value activities. AI is what it eats – now’s the time to start feeding it Process Intelligence.