AI in Accounting: The Three Waves of AI

Artificial intelligence (AI) has become a transformative force in the modern world, revolutionizing various industries and reshaping the way we live, work, and interact.  At present, most of the tools and platforms we use, whether it be for work, play, or anything in between have already kept up with the times — offering various ways on how you can integrate AI for a better user experience. 

A Quick Look Back: Before AI Became Mainstream  

 
Before AI became this widely used technology, it first went through significant changes. In fact, while Generative AI only became a buzz word around 2023, OpenAI (the biggest company investing in AI development to date) was actually first founded in 2016, already making great strides in designing AI programs that can help us in our everyday lives. The continuous development of AI from then to now paved the way for groundbreaking technologies and applications – especially in high-risk industries such as finance and accounting. 
 
To better understand the evolution of AI and how it came to be such a vital tool for finance and accounting professions to deliver quality support, it is important to take a step back and look into the key waves of AI development that shaped this technology to what it is now.  

The Evolution of AI  

Before the advent of AI, various tasks that required human intelligence were slow, cumbersome and prone to errors. For instance, data analysis, language translation and voice recognition were challenging and time-consuming. This often led to bottlenecks in workflows, delayed decision-making and reduced productivity.  

However, in 1950, Alan Turing posed a question in his paper "Computing Machinery and Intelligence," which marked the beginning of the development of artificial technology. 

Today, AI has opened new opportunities for progress in every field. Despite the enormous strides made in AI, experts have failed to agree on a single universally accepted definition of what artificial intelligence is.  

For the purpose of this discussion, we define AI as the ability of a system to perform tasks that would typically require human intelligence, such as data analysis, learning, planning and generalization.  

AI is not only limited to corporations, scientists or tech companies, but is also present in many everyday devices such as smartphones, watches, television sets and vehicles, enabling features that simplify tasks, automate processes and provide intelligent solutions.  

AI in Accounting 

Before AI’s widespread integration into known accounting software like QuickBooks and Xero, AI was first introduced to the field of accounting through earlier technologies such as Robotic Process Automation (RPA) and Machine Learning.  

With basic automation capabilities that help ease the workload of accounting professionals, they were able to mimic human capabilities but without the unique insights of human intelligence. Some of the earlier uses of AI in accounting include:  

• Data entry automation – reducing manual input errors by extracting and recording information from invoices, receipts, and bank statements. 

• Transaction categorization – automatically classifying expenses and revenues into the right accounts. 

• Bank reconciliation – matching transactions from bank feeds with accounting records for faster, more accurate reconciliations. 

• Invoice processing – scanning, capturing, and routing invoices for approval without manual handling. 

Read: The Impact of AI on Standard Bookkeeping Practices 
 

With the advent of Generative AI, the integration of AI into various accounting processes took on a more central role. Now, AI’s impact on accounting actively helps accounting professionals provide insights and analytics to help with financial forecasting and risk management.  

The Three Waves of AI 

According to John Launchbury, former Innovation Information’s director of the United States’ Defense Advanced Research Projects Agency (DARPA), the development of AI comes in three waves: 

First Wave AI (Handcrafted Knowledge)  

The first wave of AI, also known as Handcrafted Knowledge, is a technology that simplifies complex problems by mapping out the best possible outcomes or steps that can be taken. It relies on human expertise to provide the system with the necessary facts and rules of the process that it aims to improve.  

First wave AI is effective at handling narrowly defined problems, and it is proven to be useful in various applications such as scheduling logistics, automating tax software and virtual board games. This type of AI technology works through all possible outputs to generate the best recommendations for a given problem.  

However, one of the limitations of first wave AI is its lack of learning capability, which means it cannot adapt to uncertainties or changes in facts or rules without human input. Nevertheless, it still has a significant impact on improving processes, product testing and identifying potential threats and opportunities.  

Overall, while the first wave AI is a powerful tool, it has its limitations, and it is crucial to understand its capabilities before applying it in different fields. As AI technology advances, it is expected that newer and more sophisticated AI models will emerge, capable of addressing the current limitations of the first wave AI.  

RELATED: How Tech Leaders See the Future of Artificial Intelligence  

Second Wave AI (Statistical Learning)  

The second wave of AI called Statistical Learning is the AI technology that makes visual recognition, speech recognition and other perceptive technologies possible. This wave in AI development works through complex algorithms to sort through big data and identify data from one another. Second wave data is powerful in going through vast amounts of data in a matter of seconds and classifying them according to the output intended.  

Additionally, second wave AI, owing to its nature as a perceptive technology, can also be programmed to learn and adapt from the new data that it receives. This enables the second wave AI to present reliable predictions by identifying patterns in large data sets.  

While second wave data is excellent in perception and its predictive capacity, this AI development is not without caveat. Second wave AI can make calculations through perception, but it cannot perceive the context of the object being presented to it. This vulnerability can easily distort the system’s learning and perceptive capability.  

These two waves of AI development fall under on what is classified as narrow AI. Narrow AI helps with the improvement of basic and complex human activities. This technology enables the conduct of fast, accurate and highly specialized analysis, calculations, predictions and recommendations. All current deployment and implementation of AI fall under this classification.  

Third Wave AI is (Artificial General Intelligence)  

On the other hand, the third and future wave of artificial intelligence is classified as Artificial General Intelligence (AGI).  

AGI refers to the concept of AI that can match the full cognitive capacity of human intelligence. This technology would allow AI to perceive real-world phenomenon with the proper context. With this development, AI will be able to address the limitations of the first and second waves of AI development and perform tasks similar, or even superior, to any human being.  

The increased interest in artificial intelligence research and development by leading countries, tech corporations and academic institutions brings the third wave of AI closer to reality. Once AGI becomes a reality, it is expected to revolutionize various industries, including the finance industry.  

Read: Should My Firm be Worried About AI and Audit?  

Where the Third Wave Might Take Us  

The third wave of AI in the finance industry is expected to bring about significant changes and advancements that could revolutionize the way we conduct financial transactions, manage risks and make investment decisions. This wave is characterized by the development and application of more sophisticated algorithms, increased computational power and vast amounts of data.  

Before going into the advanced integrations that we are seeing at present and projected to see in the future within the accounting industry, let’s first look into how our daily lives would be affected by the current wave:  

Real-life General Applications of the Third Wave AI  

• Risk Management: One of the major areas where the third wave of AI is expected to have a significant impact is in financial risk management. By leveraging these algorithms, it can analyze vast amounts of data and help in detecting anomalies and identifying patterns that can indicate potential risks that may lead to costly financial repercussions.  
• Customer Service: Another area where the third wave of AI is expected to bring about significant changes is customer service. By leveraging natural language processing (NLP) and machine learning algorithms, financial institutions can create more personalized and engaging experiences for their customers. Chatbots and virtual assistants, for example, can provide customers with instant access to information and assistance, helping to improve customer satisfaction.  
• Fraud Detection: Financial Institutions can also take advantage of advanced machine learning algorithms and data analytics to better detect and prevent fraudulent activities. These algorithms can analyze vast amounts of data, including transactional data and user behavior data, to identify potentially fraudulent activities in real-time.   

As AGI makes our everyday lives and personal transactions more secure, it brings current accounting processes one step forward. Today, AI plays a more active role in securing financial data and information while also helping with compliance, projections, and continuity of an entity’s operations.  
 

Business Use Cases of the Third Wave of AI in Accounting 
 

• Advanced Audit Support: AGI has the ability to comprehensively understand a specific topic or function. Because of this, they can now go beyond basic record-keeping as they analyze entire datasets of financial transactions. Their complex capabilities aid auditors in detecting anomalies, irregularities, and patterns that may indicate a lack of process compliance when it comes to your company’s accounting processes.  

• Predictive Financial Forecasting: By using this new learning model of AI, finance professionals can now forecast revenue, expenses and cash flow with greater precision as AGI has the capability to analyze historical data alongside the real-life data of your company, your clients and even your competition. 

• Rigorous Tax Compliance: These advanced AI systems can autonomously adapt to evolving tax laws and regulations, ensuring filings remain accurate and compliant. Beyond automation, third-wave AI can anticipate risks in tax strategies and provide real-time recommendations, ensuring that your company does not face compliance issues.  

• Real-time Financial Analysis: Instead of waiting for end-of-period reporting, AI can provide continuous financial monitoring. This gives management access to up-to-date insights on profitability, liquidity, and performance indicators at any given time. 

• Ethics & Bias Monitoring: With third-wave AI’s ability to self-learn, it can be applied to monitor accounting processes for potential biases or ethical breaches, ensuring fairness and transparency in financial decision-making. 

 
As AI continues to evolve, industries (including finance and accounting) also need to evolve with it. As we welcome these advancements and create ways to seamlessly integrate them to our current processes, it is important to consider the overall benefits that it will have on the company – will it really streamline and optimize your operations or would it just add unnecessary steps for your employees to follow without adding any real value? 
 
If your answer is that you definitely see the benefits of AI in accounting and integrating it into your accounting processes, then it is best to approach the integration with caution. Starting with automating a few tasks first, ensuring company-wide orientation and training and seeing its initial impact before adopting a company-wide integration program. 

Read Next: Embracing the Inevitable: The Integration of AI and Accounting 

The Bottom Line  

Overall, AI is expected to bring about significant changes in the finance industry, enabling financial institutions to better manage risks, provide more personalized customer experiences, prevent fraud and make more informed investment decisions. As AI technology continues to evolve, we can expect to see even more exciting advancements in the years to come.   

Struggling to keep up with the latest AI trends? Let D&V Philippines guide you! Contact us today!  You can also download our whitepaper, "Finding the Right Talents: D&V Philippines' Solutions to Modern Accounting Firms," to learn more about our services and solutions.