Accountability in AI: How to Ethically Use AI in Finance

With all the developments that are currently happening with Artificial Intelligence (AI), knowing its positive and negative sides has become more important than ever.

You see, AI is actively transforming how industries operate, from healthcare and education to the finance and accounting sector. It’s now being used to automate reports, detect fraud, analyze spending patterns, and even forecast future trends. 

But while the technology offers countless advantages, it also introduces new ethical challenges — adding a new layer of responsibility that top management, especially finance chiefs, need to be aware of. 

Read: Accounting Automation: A Comprehensive Guide for Modern Firms 

Understanding AI in Finance and Accounting

Before we discuss the main point of this article, let’s first define what Artificial Intelligence really means in the context of finance. 

AI refers to the ability of machines or software to perform accounting-related tasks that typically require human intelligence, such as analyzing historical transactions, identifying unusual patterns, automating data entry, and even detecting potential fraud — all in a fraction of the time that it would take a person to do manually. 

Why Accountability Matters Using AI?

Accountability plays such an important role in using AI in finance and accounting where integrity and trust are at the heart of every decision, particularly when handling clients’ financial data. 

Although AI is great at processing information, detecting patterns, and generating insights, its output still depends entirely on the humans who design, train, and operate it. That means when something goes wrong, whether it’s due to a system error, a biased output, or a miscalculation, accountability doesn’t fall on the technology itself, but on the people using it. 

In fact, study by Salesforce revealed that 55% of employees have used unapproved generative AI tools at work, and 37% of organizations still lack formal policies on how AI should be used in the workplace. These findings highlight why accountability  and governance must be built from the start and a top priority that leaders should set on. 

Why are Ethics Important in AI? 

Now that we’ve seen why accountability and governance matter when using AI, it’s also important to look at the foundation behind these practices: ethics. 

Ethics plays an important role in how AI systems are designed, developed, and used, especially in the finance and accounting industry where every decision can affect client’s trust, compliance, and even the firm’s reputation. 

On top of that, a company with a clear set of values and guiding principles on AI use is a sign that they uphold standards that employees are expected to follow.  

However, putting ethics into practice isn’t just about having policies written down; it’s about building a workplace where responsible AI use becomes part of everyone’s daily routine. To make that happen, the leaders within the organization should: 

• Train employees to understand both the potential and the risks of the AI tools they use. 

• Establish clear policies on what data can be shared, how it should be processed, and who is accountable when errors occur. 

• Encourage transparency in every AI-driven decision, so clients and stakeholders can see how results are generated. 

• Regularly review AI models and outputs to identify possible biases or inaccuracies before they affect business outcomes. 

How to Ethically Use AI in Finance?

At this point, you get to have a better overview of why ethics plays a crucial role in the use of AI. The next step is putting those principles into action. 

This practice doesn’t just help the organization, but it also builds a stronger sense of trust among clients and partners, showing them that your firm values transparency and integrity in every decision made with AI. 

In fact, according to Harvard Business School Online, organizations that rush through AI implementation have often overlooked key ethical factors such as privacy, bias, and transparency — all of which are critical in maintaining public trust. 

Here are a few ways finance leaders can put ethical AI into practice within their organizations: 

1. Set clear boundaries for AI use

The first thing you need to do is define where automation adds value and where human oversight is still required, especially in areas that involve sensitive financial data or client interactions. They must keep in mind that not every process should be fully automated, and keeping people in the loop ensures that accountability remains intact. 

2. Promote transparency in AI-driven processes

Make sure employees and clients understand how AI systems generate results, whether it’s for credit assessments, audit alerts, or spending forecasts. Doing this helps build trust and prevents your organization from facing confusion or misinterpretation that could affect financial decisions or client relationships. 

On top of that, being open about the limitations of AI is just as important. When people understand what the system can and can’t do, they’re less likely to rely on it blindly and more likely to use its insights responsibly. This openness not only promotes accountability but also strengthens confidence in how your firm uses technology. 

3. Monitor and review AI performance regularly

While AI systems can learn and adapt over time, it is important to note that AI systems will never be perfect or guaranteed to make the right calls 100% of the time. Hence, you should regularly monitor and review how these systems perform to ensure their outputs remain fair, accurate, and aligned with your firm’s standards. 

Within the financial sector, even a small error can trigger serious compliance concerns or worse, damage to client trust. This is why it’s important to schedule periodic review to help you detect issues early on whether it’s biased data, inaccurate predictions, or process inefficiencies before they escalate into costly problems. 

4. Encourage human oversight and accountability

Even with all the advancements in AI, human judgment still plays an irreplaceable role, especially in this industry, where decisions impact compliance, reporting accuracy, and client trust. Yes, AI can process data faster than any person, but it lacks the ability to understand context, ethics, or intent. 

This is why as a finance chief, you should make sure there’s always a human in the loop — someone who reviews, validates, and takes responsibility for AI-generated outcomes. Doing so not only reduces the risk of blind reliance on automation but also reinforces accountability across the team. 

5. Prioritize client data protection

Lastly, when talking about clients’ financial data, it’s important to remember that trust and privacy go hand in hand. AI may make it easier to process and analyze large volumes of information, but it also increases your responsibility to keep that data secure. 

As a finance leader, you need to make sure that every AI system your organization uses, whether it’s for reporting, forecasting, or fraud detection follows strict data protection and privacy standards. This includes enforcing access controls, encrypting sensitive information, and working only with AI vendors that meet regulatory compliance requirements. 

According to an article from the Corporate Finance Institute, maintaining AI ethics in finance requires ongoing assessment of model fairness, continuous monitoring for unintended biases, and transparency in every AI-driven decision — always reinforcing the need for careful oversight and data security. 

Read Next: AI and Accounting Ethics: Ensuring Transparency and Accountability 

Why Being Ethical in Using AI Builds Long-Term Partnerships? 

Every form of partnership requires trust and integrity to thrive. From a client perspective, using AI ethically communicates that your firm values careful decision-making, respects sensitive information, and takes accountability seriously. 

This approach has tangible benefits: 

a. Reduced risk

One important benefit of using AI ethically is that it helps your organization prevent a wide range of issues, such as errors in financial reporting, biased outcomes, or compliance violations. By proactively addressing these risks, your firm not only protects its reputation but also safeguards clients’ interests. 

b. Stronger compliance

AI also helps your organization stay compliant with regulations. When transparency and accountability are built into AI processes, it’s easier to meet regulatory requirements and avoid potential penalties showing both clients and regulators that your firm takes compliance seriously. 

c. Increased client trust

On top of that, a key benefit of using AI ethically is that it helps strengthen client trust. When clients see that your firm handles their financial information responsibly, makes careful decisions, and is accountable for AI-driven outcomes, they feel confident in your services.  

This confidence goes a long way — clients are more likely to maintain long-term relationships, recommend your firm to others, and view you as a reliable partner they can depend on. 

How to Build Accountability When Using AI in Finance

Once your firm embraces the ethical use of AI, the next challenge is making sure those principles are consistently applied. This is where accountability makes sense. 

According to Australia’s AI Ethics Principles, accountability is about ensuring that the people responsible for different stages of an AI system’s lifecycle are identifiable and accountable for its outcomes. For finance leaders, this means having the right frameworks, controls, and culture in place to make ethical AI use measurable and transparent. 

Here’s how to build accountability in practical terms: 

1. Establish a Formal AI Governance Framework 

Start with a written policy that outlines how AI is developed, validated, and monitored across the finance function. This framework should clearly define: 

• Roles and responsibilities: Who approves, monitors, and audits AI-driven outputs. 

• Review frequency: How often AI models and results are assessed for accuracy and fairness. 

• Compliance alignment: How AI processes meet internal policies and regulatory standards. 
  

The goal is to make accountability visible, so every AI process has a human point of contact and a documented audit trail. 

2. Integrate Accountability into Performance Monitoring

Accountability should be something you can measure. Develop metrics that show whether your AI systems and teams are operating responsibly. 

For instance:

• Frequency of AI model reviews and bias tests 

• Number of audit exceptions or errors detected 

• Response time for addressing flagged AI issues 

Regularly reviewing these indicators ensures that AI-driven outputs remain accurate, unbiased, and aligned with company standards. This kind of measurable accountability gives both your internal team and your clients greater confidence in your systems. 

3. Strengthen Oversight in Vendor and Outsourcing Partnerships

If your firm uses AI-powered tools or works with outsourcing partners, make accountability part of every agreement. You may require vendors to: 

• Provide documentation on how their AI systems are trained and validated. 

• Meet data privacy and regulatory compliance standards. 

• Include audit rights or escalation procedures in the event of an AI-related issue. 

This ensures your firm stays accountable even when external tools or services are involved, a critical factor for protecting both clients and your organization’s reputation. 

You may also read: Accounting Outsourcing Services: Is it still Relevant? 

4. Encourage a Top-Down Culture of Shared Accountability

Accountability isn’t just about policies — it’s about people. Encourage leaders and staff to take ownership of AI-assisted tasks by making accountability part of your firm’s culture. 

• Include AI ethics and risk oversight in leadership KPIs. 

• Offer training programs on responsible AI use and data integrity. 

• Encourage employees to speak up when they notice irregularities in AI outputs. 

When everyone understands their role in keeping AI use ethical and transparent, accountability becomes part of the organization’s DNA. 

The Bottom Line 

With the incredible opportunities that AI can give comes great responsibility that every leader must be ready to take on. And CFOs, who champion responsible AI use, must set the tone for their entire organization to show clients, stakeholders, and regulators that innovation in finance can go hand in hand with integrity and transparency. 

Back-office accounting support for modern finance teams 

Building accountability in AI starts with the right systems, people, and processes. At D&V Philippines, we are a reliable outsourcing firm specializing in finance, accounting, and data analytics. If you need assistance in your accounting automation efforts, our professional accountants are always ready to help. Talk to our team today to learn how we can help you. 

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