In navigating the current world that is ever-changing, evolving constantly with various technological advancements that almost always force their way in to day-to-day routines of organisations, it is a no-brainer that the Finance function has shifted its focus on artificial intelligence for some time now.
Incorporating AI into the processes of the Finance department has been an imperative for companies to keep up with the required digital transformation.
This time, finance leaders will take a closer look on how software solutions can seamlessly integrate AI into organisations to empower their companies to achieve their goals, enhance overall efficiency, and more.
Charlie Cheah, managing director, Esker Asia, believes that CFOs and in a bigger context, the Office of the CFO in Asia, face several challenges when integrating AI into financial systems, given the region's diverse technological landscape.
"In an age of disruptions, agility and futureproofing demand a partnership between humans and AI," says Cheah. "This technology drives human-centric transformation, fortifies an organisation's ecosystem position, enhances employee relationships, and builds resilience for future economic shifts."
Challenges on technological readiness
To be able to succeed and drive value, finance leaders are faced with the enormous challenge of handling tasks that were once beyond their mere job description: technology.
This is why questions on technological readiness, which was magnified during the COVID-19 pandemic, have been hanging over organisations and sometimes, answers to these challenges were proven to be dependent not only on the usual tech guys of the company, but also to the C-suite.
Given that Asia has varying levels of technological readiness, Cheah suggests that finance heads look into the following:
Diverse Digital Maturity: While tech-savvy markets are leading the way in AI adoption, many emerging APAC economies, still grapple with outdated systems, multiple systems and limited digital infrastructure. This disparity can delay or complicate the integration of AI solutions across the Finance and IT ecosystem.
Data Complexity: AI relies heavily on clean and high-quality data to automate and optimise finance processes. However, data silos, inconsistencies and privacy regulations across APAC nations can create barriers to AI adoption. E-invoicing mandate and ESG compliance add further complexity dimensions to the priorities and challenges faced by the Office of the CFO.
Regulatory Variations: APAC’s regulatory environment for AI is still evolving. Office of the CFO must navigate these varying regulations and ensure that AI solutions comply with local laws to avoid non-compliance and potential penalties. E-invoicing mandate and ESG
Reporting add further complexity dimensions to the priorities and challenges faced by the Office of the CFO.
Implementation Budget and Costs: The investment (budget and resources) for implementing AI in finance, including technology refreshment, change management towards best practices and training, can be challenging for businesses in APAC, especially for small and mid-market companies. Despite all potential cost benefits in transforming Finance, CFOs may struggle to justify the business case for integrating cutting-edge AI solutions in locations or countries with less robust financial and digital infrastructure.
Cultural differences
Aside from the fact that the region has varying levels of readiness in the technological side of business, Asia admittedly grapples with challenges surrounding cultural differences.
Cheah says these differences across Asia impact AI adoption, particularly in finance and Accounts Payable (AP).
"In more technologically advanced countries, businesses are quicker to integrate AI due to a culture of innovation and high technological readiness. However, in markets with more traditional practices, risk aversion, and lower digital literacy create resistance and slow down adoption." Charlie Cheah
To manage these differences, Cheah recommends that the Office of the CFOs should prioritise localised AI strategies, tailoring the implementation of AI solutions to match regional cultures and readiness levels.
"A gradual, agile phased approach with pilot programs and clear communication on the objectives and goals of the mission and initiative is a critical success factor."
He adds that offering training and upskilling programs to ensure teams are equipped to manage AI tools will help bridge the gap between deploying the technology in ways that augment human performance as the key driver versus replacing it.
Adequately training for AI
To be ahead of the game, Cheah suggests that the Office of the CFO ensure their teams are adequately trained by implementing comprehensive AI tools training programs that are both role-specific and scalable across the organisation.
"Partnering with AI solution providers that offer tailored training resources and workshops, as well as providing access to on-demand learning platforms, will support continuous learning and upskilling."
He believes that creating a culture of continuous improvement and incentivising team members to experiment and learn will further ensure AI tools are used effectively across not only finance functions but also business units and processes across the organisation.
For this, AI technologies can be implemented to streamline AP processes. These include Machine Learning (ML), Natural Language Processing (NLP), and Robotic Process Automation (RPA), which can significantly streamline AP processes.
"ML helps automate invoice matching and data extraction, reducing human errors. NLP can be used to scan and extract key information from unstructured documents, such as invoices. RPA streamlines repetitive tasks such as invoice approvals and processing, improving overall speed and reducing operational costs," Cheah explains.
"These technologies can help AP teams become more efficient, allowing them to focus on higher-value activities. At Esker, we refer to this as Esker Synergy AI - a suite of cutting-edge, ever-evolving AI technologies that are embedded within and power of our solutions in the Source-to-Pay (S2P) and Invoice-to-Cash (I2C) cycles." Charlie Cheah
Driving collaboration
As finance leaders take on the reign on technology, it is part of their job to understand how AI can drive collaboration between AP and other departments, such as procurement and finance, to enhance overall efficiency.
Cheah notes that AI fosters collaboration across departments by creating integrated workflows and improving data transparency.
"For example, AI-powered systems can link AP with Procurement by automating Purchase Requisitions and Purchase Orders, the match between purchase orders, invoices, and receipts, reducing discrepancies in the Source-To-Pay (S2P) cycle. Real-time data sharing enables the finance department to make more informed decisions, leading to better cash flow management andforecasting."
The Esker Asia managing director also says that AI tools can create collaborative dashboards that provide all departments with visibility into their workflows, promoting alignment and efficiency across the organisation.
Moreover, Cheah says predictive analytics uses historical data and Machine Learning (ML) to forecast cash flow, identify trends in payment delays, and predict future spending patterns.
"This helps AP teams manage working capital more effectively by enabling them to prioritise payments, ensure optimal vendor relationships, and forecast cash shortages or surpluses," Cheah explains. "For example, AI can predict when certain vendors will be paid, allowing businesses to better time their payments and avoid liquidity issues."
These insights, Cheah believes, also empower Office of the CFO and AP teams to make proactive decisions that ensure financial health.
AI in AP also drives significant economic cost benefits by automating manual tasks, reducing human errors, improving processing speeds, and cutting down on manpower costs.
"Savings vary by economy, with more developed markets seeing faster returns due to higher technology adoption rates. In emerging markets, the savings may take longer to materialise but can still offer significant value over time, especially in labour-intensive processes and operations." Charlie Cheah
Best practices and risk management
Cheah highlights that data security is crucial when implementing AI in AP processes. Best practices include:
Data Encryption: Ensuring all financial data processed by AI systems is encrypted at rest and during transmission to prevent unauthorised access.
Secured platform: Redundant firewalls to protect the platform and systematic antivirus checks of all documents
Secured accesses: Several layers of authentication security to guarantee that only authorised users can access your environment
Secured data: Confidentiality, integrity and availability of your data are guaranteed at all times once your documents have reached the platform
Regarding potential risks that come along with relying on AI for fraud detection in AP processes and the way organisations can mitigate these risks effectively, Cheah concedes that AI technologies used in fraud detection are not foolproof.
"They can sometimes generate false positives or fail to detect sophisticated fraud schemes. Organisations can mitigate these risks by continually training AI models with updated fraud data and ensuring human oversight in the fraud detection process."
He believes that combining AI with traditional manual checks provides a hybrid approach that improves detection accuracy and reduces reliance on one system alone. "It's also essential to have a comprehensive audit trail for all AI decisions to ensure transparency and accountability," Cheah adds.
Food for thought
As AI adoption accelerates in Asia, Cheah says the Office of the CFO must carefully navigate cultural differences, invest in training, and implement robust technologies that enhance efficiency across the AP and finance functions.
He suggests that CFOs let AI handle the heavy lifting, and combine advanced technologies to elevate your team's skills, augmenting human capabilities to the next level and driving positive sum growth.
"By embracing these strategies, CFOs can position their organisation for long-term success in 2025 and beyond."
