AI and the CFO: Elevate and transform finance operations

Artificial intelligence (AI) offers today’s CFOs opportunities to enhance their operations – and reduce costs.


CFOs across industries have an opportunity to elevate and transform their organizations by enlisting artificial intelligence (AI) solutions to tackle challenges, from talent shortages to data volume. Depending on the type of AI, these solutions can move the needle from automating routine tasks to solving complex problems – reducing the need for human intervention and increasing accuracy by eliminating human error. They can help improve financial analysis, reporting, and decision-making, reduce cost of operations, and boost efficiency. 

With careful planning, and consideration of current and future needs balanced with potential risks, the office of the CFO can stand at the forefront of revolutionary operational changes, propelling corporate finance into new territories and setting the stage for a dramatic shift in how things work. 

Technology has seen more change in the past year than in the previous decade, thanks to breakthroughs in generative AI. Significant transitions are happening in e-commerce, customer service, data management, cost optimization, forecasting, and transaction processing – all powered by AI to identify trends and make informed decisions about governance, compliance, investments, and strategic initiatives.

What is AI? And what does it mean to the CFO?

AI technology is capable of learning, thinking, and evolving. As AI becomes more widely available, CFOs can now move beyond automating repetitive tasks to deploying tools that can analyze data, solve somewhat complex problems, and learn over time to provide better customer experience, improve performance, and increase the bottom line.

In a business context, this means that now technology can be used to augment many roles, often faster and more accurately than humans – enabling professionals to focus on more strategic, relationship-driven, or creative tasks. For the CFO, integrating these technologies can translate to heightened accuracy, improved governance and compliance, shorter processing times, and more accurate, timely reporting – all of which helps boost outcomes and drive organizational maturity. 

Use cases and considerations for AI in the OCFO

Today’s CFOs are facing new challenges as the complexity and scope of their roles evolve. It is imperative to keep a close eye on financial health, manage risk, and drive nimble business strategy that delivers profit. Additionally, poorly integrated acquisitions and rapid growth have led to inconsistencies, inefficiencies, and duplication of processes and systems, costing organizations valuable time and money. Not to mention, they face resource constraints and the ongoing talent shortage in the middle market, which both makes it difficult to address these issues and presents new ones.  

These challenges open the door for creative, AI-driven solutions. While AI will not replace accountants and finance professionals and leaders, it stands ready to empower them. 

AI technology can be used to:

  • Augment roles
  • Expedite research
  • Elevate the speed and accuracy of reconciliations, intake, and communication tasks
  • Streamline information processing and consolidation
  • Improve collaboration and transparency
  • Optimize transaction processing for accuracy, speed, and lower costs
  • Improve forecasts, working capital, and financial modeling
  • Increase efficiency and automate core finance processes
  • Improve compliance with regulatory and statutory requirements 

However, AI is not without its own challenges. A main one is that it relies on “big data” and clean datasets; clean, accurate, complete datasets are needed for reliable outputs. Despite maturing in various aspects, many finance operations still struggle to fully adopt technologies and to streamline processes and enforce data cleanliness during implementation. The need for speed often overrides best practices, and bad data and inefficient processes are moved from system to system. People may use workarounds to produce accurate reports and forecasts, adding days and cost to accounting and financial processes.

Additionally, those large datasets call for careful consideration of privacy and security. Protocols must be put in place for data limitations and use of personally identifiable information (PII) or other sensitive datasets.

Without an outcome-focused, use-case-driven approach, AI-driven transformation projects are likely to fail.

Best practices and next steps

The key to success with AI tools is in posing good questions and employing robust algorithms, using trustworthy datasets. It’s important to follow standard business rules, policies, and regulatory and statutory guidelines for data protection and security. 


  • Be intentional and have a plan, with targeted items to gain small wins. Organizations can swiftly implement impactful changes by concentrating on smaller, specific tasks. Engage in readiness assessments of your capabilities and processes to identify areas to mature, optimize, or transform: Processes that are lagging in functionality or disconnected, or areas where you need to better manage cash flow or forecasting or to reduce cycle times, time to close, or DSO.
  • Work with your finance transformation team and advisors to develop a detailed plan with supporting KPIs (key performance indicators), so that you can measure your success over time.
  • Protect your processes and data. Strong governance and data policies are necessary to ensure timely, accurate, compliant data and reporting. Having a strategy and vision is key; don’t do it all at once, and put in place strong governance practices that enable your goals – growth, cost reduction, or scale.
  • And finally, make sure that comprehensive training and adoption efforts are part of the implementation plan, so that everyone in the organization is on board to support this new way of working, transitioning from traditional practices to embracing the transformative potential of AI.

How CohnReznick can help

Working with a skilled advisor can give your team confidence, increase capacity, and provide a framework and expertise to draw from.

Our experienced teams have worked across industries to help identify and implement strategies, automate processes, and support clients in adopting automation solutions that enable the target operating model and align talent with KPIs and mission.

Contact our CFO Advisory team to learn more and get started on your AI-empowered transformation.

Get in touch with our specialists

View All Specialists
Kim Clark-Pakstys

Kim Clark Pakstys

Managing Director, CFO Advisory
Swami Venkat

Swami Venkat

CPA, CISA, CFE, ACA, Partner, CFO Advisory Leader

Looking for the full list of our dedicated professionals here at CohnReznick?



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This has been prepared for information purposes and general guidance only and does not constitute legal or professional advice. You should not act upon the information contained in this publication without obtaining specific professional advice. No representation or warranty (express or implied) is made as to the accuracy or completeness of the information contained in this publication, and CohnReznick LLP, its partners, employees and agents accept no liability, and disclaim all responsibility, for the consequences of you or anyone else acting, or refraining to act, in reliance on the information contained in this publication or for any decision based on it.