The disadvantages of using AI, bots, and other tech over traditional finance methods

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AI, bots, and other tech over traditional finance methods are becoming increasingly popular for businesses. Companies like Microsoft are using these methods to keep their finance headcount flat, potentially reducing costs. However, some disadvantages exist when implementing these technologies within a business.

In this article, we’ll look at the potential drawbacks of using these technologies to manage finances compared to traditional methods.

Microsoft keeps its finance head count flat with AI, bots and other tech

Artificial intelligence, or AI, refers to how software methods, algorithms, and systems are created and used to mimic human-like intelligence. These systems have many applications, such as personalised banking services and automated decision making. In addition, AI technologies can be used in data mining and natural language processing.

Bots are computer programs that automate specific tasks and activities. They can be programmed to perform tasks ranging from completing small jobs to larger activities such as customer service or sales support. For example, bots use artificial intelligence (AI) to understand customer conversations and respond accordingly.

Other tech often used in transforming traditional finance methods include task automation software such as Robotic Process Automation (RPA), machine learning algorithms such as supervised/unsupervised learning , cloud computing technology for data processing, quantum computing for analysis of large datasets, blockchain technology for secure transactions, predictive analytics for forecasting future trends, natural language processing (NLP) for interpreting spoken words, computer vision for automated image analysis etc.. These technologies are working together to reduce costs and increase the efficiency of business processes.

Microsoft’s use of AI, bots, and other tech

Microsoft Corporation has been using Artificial Intelligence (AI), robotic process automation (RPA) and other technologies to reduce its finance headcount to remain cost-competitive. In February 2018, the company announced it had cut its finance headcount by 800 since the start of fiscal year 2016.

The technology that Microsoft has adopted sharply reduces the number of slow and labour-intensive manual processes. It also helps to avoid mistakes caused when employees carry out financial operations manually, minimising errors and wastes associated with them. In addition, AI, bots and other tech can process data quickly, eliminating delays in completing tasks when multiple people gather, organise, analyse and enter information into a system.

However, this shift brings certain drawbacks, including cost savings driven solely by employee reduction rather than the gains made from more efficient processes, which could lead to employee frustration as they may not be provided with better tools or enough training opportunities related to new technology. Moreover, millions of financial jobs – some of which have been shortchanged as previously needed specialists ceded their roles to automated AI will be gone forever as these systems become even more prevalent over time. Additionally, integrating new technologies with existing systems may be difficult due to technical incompatibilities between the two, making implementation difficult or impossible without significant modifications.


When businesses begin to replace traditional finance methods with Artificial Intelligence (AI), bots, and other technologies, there can be some drawbacks. Although AI, bots, and other tech can save businesses time and money, they still come with their unique set of disadvantages.

This article will explore the cons of using AI, bots, and other tech over more traditional finance methods, as evidenced by Microsoft’s decision to keep their finance headcount flat and let their automation do the work.

Loss of Human Interaction

As technology advances, more and more companies are replacing human interaction with automated processes and artificial intelligence (AI). For example, Microsoft can keep its finance headcount flat by relying on AI, bots and other technology. This brings efficiency to companies which saves them time and money. However, there are disadvantages associated with this type of strategy. The biggest disadvantage is that customer experience suffers when financial decisions become a matter of algorithms and programming instead of the input of a human being. People need assurance from having a human being look at their situation objectively to make the best decision for their finances.

Furthermore, when people need help understanding complex financial matters, having someone explain it to them is more helpful than an algorithm. Customers often feel that no one is listening or willing to understand their unique needs or situation without human engagement. Additionally, if something goes wrong with their account or they simply have questions, they will feel disconnected without an actual person explaining the problem or how it can be fixed.

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Thus, even though AI and bots can automate many processes within finance-related tasks such as data entry or risk analysis tasks—human contact still matters in providing long-term customer satisfaction and delivering value through trust-based relationships.

Risk of Errors

Using AI, bots, and other tech in Microsoft’s financial operations may reduce the number of finance staff needed, but it also introduces a higher risk of errors. Software is far from infallible and mistakes made in accounting can have catastrophic effects on a company’s bottom line. Additionally, since less people are involved in the process there is less oversight to catch and quickly fix any errors that do occur. As AI algorithms become increasingly complex it can be difficult to understand why a system chose one action over another or made the wrong decision. It can be impossible to effectively resolve the issue at hand without pinpointing it.

Another disadvantage is that automation of financial processes removes some forms of accountability that traditional methods provide such as deterring fraud or ensuring compliance with internal procedures and external regulations such as Sarbanes-Oxley (SOX). Since bots require no oversight from employees, some of these safeguards may be lost unless IT puts additional controls into place to maintain transparency and accountability for automated decision-making.

Overall Microsoft should weigh potential savings against risks when deciding whether or not to invest in AI for their financial operations.

Difficult to Adapt

Though implementing new tech such as AI, bots, and other automated solutions can have many advantages, businesses must also be aware of the potential drawbacks of the transition. One disadvantage is that they can be difficult to adapt. This is particularly true when transitioning from manual to automated ones, as employees must learn new skills or processes to work productively in the new system. Additionally, older software versions may need updating for newer technologies to work properly, which can cause further disruption.

Another disadvantage is related to cost. For example, automation has been cited as one of the primary reasons for lower head count within Microsoft’s finance department. This means that costs originally associated with human labour are now being allotted toward technical resources and continued development of automated systems instead. As a result, businesses must find ways to fund their tech investments and maintain their budgets even after implementation.

Finally, when relying heavily on automation and AI-driven solutions for finance decisions, it can be difficult for companies to adapt quickly if market trends or customer needs change rapidly. For example, suppose decision-making relies so heavily on data-driven models that do not account for certain external factors or have an understanding of customer feelings and behaviours in specific scenarios. In that case, businesses may struggle to meet changing market demands and maintain customers’ trust in their services.

Impact on Financial Services

Companies increasingly turn to Artificial Intelligence (AI), bots, machine learning, and other technologies to keep their finance headcount flat. This can have significant implications for the financial services industry, from cost savings to better accuracy, but it also presents certain drawbacks and risks.

Let’s look at the pros and cons of relying on AI, bots, and other tech rather than traditional finance methods.

Reduced Staffing Levels

As businesses adopt new technologies such as AI, bots, and other tech developments in their finance departments, the need for human labour diminishes. These emerging technologies can automate complex tasks and subtasks quickly and efficiently.

However, this growing adoption of artificial intelligence and automated solutions may adversely affect those employed in the traditional finance sector. Consequently, finance firms may experience decreased staffing levels due to replacing manual activities with automated solutions.

When Microsoft announced its intent to predominantly use AI and bots to reduce its head count in its finance team, it highlighted how automation can be leveraged to benefit businesses’ bottom line by reducing labour costs. While this might suggest that more jobs are at risk due to technological advances, some organisations are actively investing in developing upskilling initiatives so that current employees can adapt as roles become increasingly digitised.

Ultimately, while technological advances can provide advantages from a financial perspective for business operations, it is important to consider any potential long-term impacts on the workforce so that appropriate measures can be taken before implementation.

Increased Cost of Implementation

Artificial intelligence (AI), bots, and other technology solutions have revolutionised the financial services sector.

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However, despite the many benefits these tech solutions can bring to businesses, they have some drawbacks. In particular, one of the major disadvantages of using AI, bots, and other technology within the financial services sector relates to cost.

The implementation and maintenance of these solutions can be a lengthy and costly process. To get an AI system or boot up-and-running, businesses need to invest substantial sums in both initial development fees and ongoing support costs; this is an expense not typically found when using traditional finance management methods. Furthermore, a specialist may be needed to diagnose and fix any issues that arise with the system – which can happen given its reliance on complex algorithms and data patterns. Considering these factors makes it clear why Microsoft opted for a flat headcount for finance management when the company deployed their own suite of AI-based financial solutions.

Nevertheless, despite this potentially substantial cost in terms of time and money, businesses must weigh up the pros against cons when considering whether or not to implement AI-based technologies within finance management roles; indeed conventional financial services processes still offer valid avenues through which businesses can successfully manage their finances while limiting associated overhead costs.

Increased Risk of Fraud

The use of technology over traditional finance methods such as manual bookkeeping and human labour increases the risk of financial fraud or theft. The increased automation of financial transactions provided by AI, bots, and other tech reduces the need for manual labour and thus increases the chance that problems will go undetected. The reliance on these technologies also introduces another layer of complexity to managing data. Small errors in data can lead to potentially large consequences for companies, as these mistakes can compound over time.

In addition, without proper controls, malicious actors can leverage AI bots and other technology to conduct fraudulent activities such as money laundering and unauthorised access to accounts or systems. Furthermore, data collected from robots and other AI tools could be vulnerable to hacking or attacks compromising customer information or funds.

Ultimately, companies need to put measures in place to prevent fraudulent activities and protect customer information from being misused. This includes incorporating robust fraud detection models into systems paired with strong user authentication processes when interacting with online services.

The use of AI, bots, and other tech to automate certain tasks and streamline processes in business can be a viable option for many organisations. However, there are still some disadvantages that should be considered when opting for this approach.

This article will discuss some potential drawbacks of using AI, bots, and other tech solutions over traditional finance and accounting methods.

Summary of Advantages and Disadvantages

Using AI, bots, and other tech to automate finance operations can save costs and speed up traditional processes. However, these tools also have some potential drawbacks which should be considered.


  • Automation can lead to greater accuracy in performing transactions and reducing the costs associated with manual processes.
  • With AI and automated programs, companies have better data management capabilities for improved money management.
  • These technologies offer increased speed of processes so that tasks can be completed faster with greater efficiency.


  • Companies must ensure that their software is up to date and secure to protect against potential breaches or data loss.
  • Technology can be expensive to implement initially and may require additional financial investment as it evolves.
  • If a company relies too heavily on technology solutions, it risks becoming disconnected from business activity and market trends.

Overall, AI, bots, and other tech are rapidly advancing into finance operations providing businesses with useful tools for streamlining their operations—but business owners must weigh both the advantages and disadvantages when determining how much automation should be used in their organisation’s finances. Ultimately, it’s about finding the right balance between innovation and traditional methods that best suit a company’s needs.

Implications for the Future of Financial Services

The use of AI, bots and other tech to automate manual processes or streamline tasks is beginning to have a major impact on the operations of financial services organisations. By eliminating the need for humans to do mundane tasks like verifying data or creating reports, companies can reduce their headcount and expenses, allowing them to focus more resources on growing their business.

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However, some potential risks are associated with using these technologies in finance. For example, relying too heavily on technology can lead to slower decisions or lack of oversight for important tasks. In addition, a lack of human touch could make customers and clients feel disconnected from their financial institutions.

Finally, AI-driven technologies are not infallible and could introduce unforeseen problems if implemented incorrectly. These potential issues must be understood before companies can fully embrace the benefits of technology in finance.

Ultimately, it is up to companies like Microsoft that take advantage of AI-driven financial services solutions to properly manage risk while providing quality service that meets customer expectations and regulatory requirements.

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