How to Navigate the Challenges of AI Implementation in Finance

Bringing the power of artificial intelligence (AI) to streamline and automate various aspects of your business operations can be challenging. You may have come across success stories and real-world applications of AI in the financial world, but when it comes to implementing AI, the road can be bumpier than expected.

Having recently explored concrete use cases of generative AI in finance, we've seen the potential benefits of AI. However, I'd like to acknowledge that achieving success with AI implementation often falls short of our best intentions. Return on investment (ROI) doesn't always meet expectations.

In this blog, I won't just point out the challenges; I'll provide you with practical recommendations to navigate them effectively.

Whether you're looking to implement AI for the first time or seeking to enhance your existing AI models, these insights will help you achieve greater certainty of success. Join us as we explore how to implement AI in finance, unlock its potential, and overcome the challenges that may arise along the way.

Strategies to a successful AI implementation

Let's delve into practical strategies to ensure your AI projects thrive and effectively leverage AI in your business processes:

1. Investments are often judged based on a limited view of ROI

When assessing implementation of AI strategy and the potential benefits of artificial intelligence, it's common for evaluations to focus solely on a limited view of ROI. As a finance professional, you excel in the hard side of analysis, emphasizing cost-benefit assessments. However, a critical pitfall lies in the insufficient consideration of 'soft' variables.

Some opportunities arising from AI tools, such as reallocating resources to foster innovation through AI automation, cannot be easily quantified in monetary terms. Neglecting to incorporate tools that offer both quantitative and qualitative data can lead to inaccurate conclusions regarding the technology's impact. This oversight may include the disregard of culture-driven barriers to successful AI implementation and adoption.

To address this challenge, we recommend continuously gathering user feedback.

This approach allows you to gain insights into how AI technologies will perform in various organizational contexts, aligning your AI strategy more closely with your business needs and facilitating a more comprehensive evaluation of ROI. Building a multidisciplinary AI team can also be valuable in this regard, ensuring that both technical and non-technical aspects are considered in your AI implementation strategy.

2. Technology decisions are not always made by the right person

Another real-world challenge in the development process of deploying AI relates to decision-making. Often, the right people are not involved in these crucial choices, particularly those who will be using the AI system daily. This oversight increases the risk of failure.

The result is an ad-hoc, top-down approach when proposing and selecting new technologies, disregarding essential aspects like aligning with business goals, the cost of upskilling employees, or understanding how the AI system's algorithm will function in day-to-day activities.

To address this issue effectively, it's essential to engage both strategy makers and dedicated employees in the decision-making process. This collaborative approach ensures that investments in new AI solutions align with your business objectives and gain support and adoption after deployment.

Our recommendation is to establish a formal decision-making process with standardized procedures for gathering opinions and feedback. The most successful technology changes encompass input from both technical and managerial functions, along with customer-facing employees.

Transparency is critical when adopting AI, which is more prone to employee resistance due to fear of potential job loss.

3. Project and change management are not based on best practices

When it comes to managing projects and changes in the world of AI and machine learning, it's crucial to adhere to best practices. Typically, the more complex and interconnected a technology implementation project is, the greater the risk of failing to meet its core objectives or realizing the expected benefits. Unfortunately, many companies fall short in applying proper project management practices.

How to Navigate the Challenges of AI Implementation in Finance

It's essential to acquire proficiency in established project management frameworks such as SCRUM Agile. Additionally, for efficient management of IT/cloud costs, familiarity with FinOps  practices becomes a necessity. While some elements of these frameworks are often utilized, they may not be fully integrated, leading to suboptimal control and adjustments during project execution.

By integrating these best practices more tightly into your project and change management processes, you can improve the chances of success, ensuring that your data scientists and teams can effectively execute AI use cases and machine learning initiatives while harnessing the potential of AI and ML technologies.


By following these strategies and creating a solid implementation plan, you can effectively leverage AI in your business processes and financial operations. It's about making smart decisions guided by AI experts and business teams, continuously gathering feedback, and involving the right people in the process. Embracing best practices in project and change management, as recommended by AI experts, will also enhance the effective deployment of AI algorithm.

So, don't rush; take the time to plan and collaborate effectively. AI has the potential to revolutionize finance and bring about real change in your business strategy. With the right approach and a well-executed implementation plan, you can harness the power of AI and drive success in your financial endeavors, unlocking significant business value along the way.

If you don't know where to begin, join our Generative AI Workshop. It will give you the knowledge and skills to understand and use ai across your business effectively. Don't miss the chance to stay ahead and succeed in the changing world of finance.

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