Artificial intelligence has quickly become one of the most discussed topics in finance. Finance leaders are being asked to evaluate new tools, identify opportunities for efficiency, strengthen decision-making, and prepare their organizations for a future that is evolving faster than ever. 

Amid the excitement, many organizations are asking the same question: Where do we start? 

While AI technology continues to advance at a remarkable pace, the organizations seeing the greatest success are not necessarily those moving the fastest; They are the ones building the right foundation. They understand that successful AI adoption depends on more than technology. It requires strong processes, engaged teams, thoughtful governance, and a willingness to learn. 

For finance leaders, that is encouraging news. The path forward does not require transforming everything overnight. Instead, it starts by focusing on a few fundamental principles. 

Start with business problems, not technology 

The pressure to adopt AI can make it tempting to begin with tools and then search for ways to use them. However, the most successful implementations typically begin with a business challenge. 

Rather than asking, "How can we use AI?" finance leaders may achieve better results by asking: 

• • Which processes consume too much time? 

• • Where are our biggest bottlenecks? 

• • What work is highly repetitive? 
  • Which activities create frustration for our teams? 

In many organizations, valuable opportunities are hiding in plain sight. Manual data entry, recurring reconciliations, report preparation, and routine administrative tasks often represent ideal starting points. 

By focusing on specific business challenges, organizations can create meaningful wins while building confidence and momentum. 

AI works best on a strong foundation 

One lesson is becoming increasingly clear across industries: AI does not replace the need for good processes. 

Organizations often discover that automating a poorly designed process simply accelerates inefficiencies. In contrast, when processes are standardized and well understood, AI can dramatically improve speed, consistency, and scalability. 

This makes process evaluation an important part of any AI strategy. 

The emergence of AI also presents an opportunity to challenge long-standing assumptions. Many finance processes were designed before today's technology capabilities existed. Rather than simply automating existing workflows, organizations may benefit from stepping back and reimagining how work could be performed from the ground up. 

The human side of transformation 

Much of the conversation around AI focuses on technology, but successful adoption is ultimately a people initiative. 

Within most organizations, enthusiasm exists alongside uncertainty. Some team members eagerly explore new tools and possibilities. Others may be concerned about how AI will affect their roles or responsibilities. 

Finance leaders can play an important role by helping teams understand that AI is not simply about reducing effort. It is about elevating work. 

As routine tasks become more automated, finance professionals have greater opportunities to focus on analysis, business partnership, strategic planning, and decision support. The work becomes less transactional and more advisory. 

That evolution has the potential to make finance careers more engaging while increasing the strategic value finance brings to the organization. 

Create a culture of learning 

One of the challenges of AI is that no organization has all the answers. 

Technology is evolving rapidly, new use cases are emerging constantly, and many leaders are learning in real time alongside their teams. 

For that reason, successful organizations are creating environments where experimentation is encouraged. 

Small pilots, practical use cases, and shared learning experiences often produce better results than extensive planning efforts. Teams should feel comfortable testing ideas, learning from failures, and sharing discoveries with one another. 

Interestingly, organizations frequently find their strongest AI advocates in unexpected places. Curiosity, creativity, and openness to change often matter more than technical expertise alone. 

The teams that learn together tend to adapt faster together. 

Governance remains essential 

Even as organizations embrace innovation, finance leaders continue to play a critical role in governance and oversight. 

Questions around security, data protection, compliance, and responsible use cannot be overlooked. Organizations should understand how data is being used, how information is protected, and what controls exist to ensure accuracy and accountability. 

In many ways, the traditional strengths of finance leadership become even more valuable in an AI-enabled environment. Strong judgment, risk management, critical thinking, and governance help ensure technology delivers value responsibly. 

The future role of finance 

Perhaps the most significant opportunity AI presents is not greater efficiency. It is the potential to further elevate the finance function. 

Historically, finance teams invested substantial time collecting, reconciling, and reporting information. As AI reduces the effort required for many of those activities, organizations can redirect talent toward higher-value work. 

Finance professionals will increasingly be asked to interpret information, identify emerging trends, evaluate risks, and help shape business strategy. 

In other words, AI is not replacing the role of finance. It is expanding its influence. 

Five steps finance leaders can take today 

For organizations feeling overwhelmed by the pace of change, the good news is that meaningful progress does not require a massive transformation initiative. 

Instead, finance leaders can begin by focusing on a few practical steps: 

• • Identify one repetitive or time-consuming process that creates frustration for your team. 

• • Engage the employees closest to the work to understand where inefficiencies exist. 

• • Evaluate whether the underlying process should be improved before it is automated. 

• • Establish clear governance around security, data usage, and oversight. 
  • Experiment with a small, measurable use case and build from there. 

AI adoption is a journey, not a single project. The organizations that gain the most value will be those that approach it with curiosity, discipline, and a commitment to continuous learning. 

Technology will continue to evolve. The organizations that succeed will be the ones that combine strong processes, engaged people, thoughtful governance, and a willingness to adapt. For finance leaders and their teams, that foundation can turn AI from an emerging technology into a lasting competitive advantage. 

For a deeper dive, listen to the podcast: Why CFOs Can't Just Layer AI on Broken Processes – with CohnReznick