By Matthew Goss, Senior Vice President & General Manager, Asia Pacific Japan & Greater China, SAP Concur | 28 February 2022
In this digital age where data is the new game changer, artificial intelligence (AI) and machine learning (ML) play pivotal roles in transforming enterprises across industries.
While the transformational process has been going on for years, it was only during the recent pandemic that organisations’ attitude towards these cutting-edge technologies took a dramatic turn. These firms had to contend with large swaths of the workforce working from home, and digitalisation became a natural priority for business continuity.
According to The Economist Group, reducing the drag of manual business processes and finding process improvement opportunities remains a top priority with 89% of executives. They said that deploying advanced technologies is key to their business resilience. Some 86% of the executives also found that Covid-19 forced their companies to embrace operational agility and become more open to experimentation. Their firms also pivoted their strategy to adapt to the new environment.
Businesses can get great ROI from rethinking how they use data. IDC, for instance, estimated that the annual generation of digital data will experience a 23% compound annual growth rate over the 2022-2025 forecast period, and business leaders can harness the large volume of data generated to help them make key finance and business decisions.
As we negotiate the Great Resignation, creating better employee experience is also vital. Organisations’ expectations about productivity will only increase. At the same time, employees are living through the most stressful and anxiety-filled period in recent history. Organisations should give people tools like predictive analytics that make it easier to carry out their tasks, while at the same time encouraging a better work-life balance. According to Forrester Research, within two years, 80% of organisations’ HR strategies will focus on employee experience as a top priority.
The Fast Path to Intelligent Technologies
The good news is that the intensive development of AI and ML in the past few years has made the technologies quite mature for deployment in enterprise environments.
In more and more organisations, AI and ML are becoming tools for IT, finance, accounts payable teams, security, travel managers, and all kinds of business decision-makers. Intelligent technologies are streamlining processes, assisting employees, and freeing people from manual tasks. Both small and large businesses either already leverage intelligent technology in their operations, or they want to.
AI and ML driven predictive analytics play a pivotal role in enterprises today, giving insights into the following:
- Risk Mitigation and Compliance in Employee Spend
- Many firms struggle with risk and compliance issues for employee spend such as expenses, travel, and invoices. With a diverse group of employees across the organisation that may not be familiar with the intricacies of the company’s spend policy, it is easy to make mistakes and violate the policies set. AI and ML can streamline the entire process and introduce enforcement rules to the workflow, flag risk and compliance issues, and automate various manual work that may increase a company’s exposure to fines and reputational risks.
- Auditing
- It’s one thing to spot mistakes and potential fraud, but it’s even more important to identify spending patterns that may have been happening for years. In fact, according to the Association for Certified Fraud Examiners, typical expense misuse isn’t identified until 24 months after it started. To catch patterns in spend that indicate misuse, organisations have to look at everything but that isn’t humanly possible. AI and ML can dutifully go through every line item and offer insights that may influence key business decisions.
- Managing Taxes
- Businesses often need to deal with a slew of taxes such as Goods and Services Tax (GST), Harmonized Sales Tax (HST), and Value Added Taxes (VAT), each with ever-changing rules, which makes it highly prone to human error in terms of management. Intelligent technologies can digitalise the entire process, eliminating risky manual processes and streamlining compliance. IT can also provide insights into substantial tax reclaim opportunities on purchases made.
Businesses today operate globally in complex regulatory environments. Keeping policies up to date and in compliance with regulations in one country is already a full-time job. As organisations operate across borders, this task only becomes less manageable. According to a 2021 analysis by Deloitte, there are 220 regulatory revisions across the world each day. The job of staying compliant is complex. The cost for non-compliance is also high in terms of fines or money left on the table when organisations fail to reclaim taxes owed to them.
All in all, AI and ML make humans more human by allowing us to do the things we are really good at. Enterprises should use such work enhancing technologies more widely, deploying them intelligently and in lockstep with other transformations in their business ecosystem.
