4 Key Considerations for Your AI Adoption Strategy

Emily Perkins

Emily Perkins

Head of Content Strategy

Following best practices for API implementations is imperative to create meaningful change in the accounting function, in particular when adopting AI technology.

May 16, 2024

4 min read

4 Key Considerations for Your AI Adoption Strategy

As a finance leader, it’s imperative to continue improving operations, uncovering bottlenecks, and positively impacting the bottom line. Yet, daily challenges will most likely continue to create obstacles in achieving ideal operational excellence. Manual accounting, financial errors, hazy forecasting, and continuous audit or fraud concerns are common for most finance and accounting teams.

A recent survey by Gartner found that 59 percent of accountants are making several errors per month, and these errors are linked to low capacity on the AP team. An overworked team member is inevitable to make mistakes, and the potential consequences of errors on the overall financial health of the business can be significant.

On the bright side, automation and artificial intelligence (AI) solutions are helping to relieve and resolve these historical pains in the accounting function.

A 2023 Financial Services GenAI Survey by Ernst & Young found that a staggering 99% of financial leaders surveyed reported their organizers were deploying AI in some manner, and all respondents said they are either already using, or planning to use, generative AI (GenAI) specifically within their organization.

And even with the astounding findings in the Ernst & Young survey, only one in five respondents said they are nervous or skeptical about the potential impact of GenAI in their organization. The AI revolution is already here — but how finance leaders adopt the technology will be critical to their success in the long term. Here are four best practices to follow for a successful adoption of AI in accounting:

1. Identify a use case for augmenting the team with AI

Ensuring there is a viable use case and opportunity to leverage AI seems like a no-brainer; however, it’s important to reiterate that where you implement AI is just as important as how. Manual, mundane, and repetitive tasks are an ideal place to start — in particular areas that are time-consuming, cost-prohibitive, and error-prone.

For the accounting function, ideal use cases for leveraging AI technology include invoice processing, invoice and PO matching, exception handling, invoice approvals, fraud detection, cash flow forecasting, predictive analytics, spend management, regulation and compliance, and audit preparation.

2. Complete a cost-benefit analysis for the investment

Once a use case, or use cases, have been identified for leveraging GenAI tools, it’s imperative to do a cost-benefit analysis. While AI can transform financial operations by improving efficiency, cost savings, and strategic decision making, the investment may — or may not — make sense for every organization or scenario.

Alexander Hagerup, CEO and founder of, an AI-first accounts payable platform, recommends a cost-benefit analysis to ensure the right decisions are made for the overall business.

It requires “careful consideration of potential benefits, costs, feasibility, strategic impact, and ethical considerations. By taking a holistic approach, finance leaders can make informed decisions about adopting AI and ensure they derive the maximum benefit,” Hagerup says in a recent article.

3. Prepare and expand your team for GenAI

With any new technological advancement, fear and uncertainty are common. Rightly so, finance leaders have concerns about the impact of implementing AI technology and its successful adoption within the organization. There is a common misconception that AI tools will take away jobs and eliminate roles, but in reality, AI can be strategically leveraged as a collaborative business partner to handle mundane, time-consuming, and repetitive tasks — the unfulfilling work that humans don’t enjoy.

AI can automate repetitive tasks, freeing time for employees to focus on more meaningful work. It can also provide data-driven insights into workload management, helping distribute tasks evenly across the team and reducing stress. Changing the perception of the role of AI within an organization before implementation is critical, and this takes time, attention, and identifying evangelists within a team.

Business leaders may also find that they don’t have the appropriate staff on hand to lead and manage the change. Ensuring a change agent or champion is leading the project is critical to the success of the project, and hiring a technical specialist with an accounting background may also be helpful.

4. Follow a reputable adoption methodology

While it’s possible to independently research and select an AI tool for accounting, it is worth considering following an adoption methodology or framework. These frameworks can include implementation roadmap best practices, maturity models for benchmarking goals and milestones, guidelines for ethical use and data security best practices, and much more.

Gartner offers many research reports and best practices on adopting AI, MITRE offers an AI Maturity Model and Organizational Assessment Guide, and even Info-Tech Research has blueprints available. Look to the AI technology provider for best practices and implementation guides, too.

Incorporating AI technology into the finance and accounting function is an exciting project for any finance leader. Ensuring plans for AI adoption are in place will only support the project’s long-term success. And if managed correctly, an AI implementation can truly transform an organization and support future growth.

This article was originally published on in April 2024.

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