A CFO’s Guide to Using AI

CFO.University is proud to include in our Contributor corps global leaders advancing AI in finance. This issue of the Future of Finance Leadership recaps three articles by our AI Rock Stars and shares 10 actions CFOs should take to make AI work for their teams and businesses.

This edition includes a thought-provoking paper by Nathan Bell; a conversation with Tariq Munir and Prashanth H. Southekal; and an article by Glenn Hopper and guest contributor Rachel Cappell. These pieces collectively underscore how artificial intelligence (AI) is transforming corporate finance, while highlighting risks, strategic actions, and best practices for CFOs and finance leaders.

1. The AI Revolution in Corporate Finance: Unlocking New Frontiers

Author: Nathan Bell

Nathan’s article explores how AI is reshaping corporate finance by automating routine tasks, enhancing analytical capabilities, and enabling data-driven decision-making. He emphasizes that while AI can dramatically increase efficiency and lower costs, it also presents technical, data security, and change-management challenges. To overcome these, Bell advocates for clear strategic vision, robust data governance, staff training, and collaboration with AI experts. Ultimately, he foresees AI as a transformative force poised to advance risk assessment, strategic planning, and competitive advantage in finance.

He asserts that AI is redefining the fundamental nature of financial operations. His key points include:

• Automation & Efficiency Routine tasks like data entry, transaction processing, and compliance reporting can be effectively automated with AI. Use tools like the “AI in Finance – Identification Worksheet” to spot the most impactful AI-use cases in finance.
• Analytical Insights & Forecasting AI-driven predictive analytics helps finance teams spot intricate patterns in large datasets—proactively identifying trends, market shifts, and potential risks.
• Strategic Decision-Making With data-driven insights, finance professionals can make and aid their colleagues in making faster, better informed decisions. AI strengthens a culture of evidence-based management and adaptability in rapidly changing markets.
• Cost Optimization Reductions in manual labor, heightened speed, and minimal errors lead to lower operational costs. Freed-up resources can be repurposed for strategic initiatives, innovation, or further AI investments.
• Overcoming Challenges He identifies significant barriers—technical integration, data security, change management, and talent acquisition. Addressing these requires careful planning, robust data governance, employee training, and collaboration with AI experts.
• Future Outlook AI will become even more integral, notably in risk management, decision-making, and end-to-end financial management. Nathan cites emerging synergies between AI, blockchain, and IoT, which could transform payments and improve transparency.

Read the full article Here

2. Unlocking the Power of AI in Finance: A Conversation with Tariq Munir and Prashanth Southekal

Guests: Prashanth Southekal and Tariq Munir

This discussion highlights how CFOs can adopt an “AI mindset” and foster digital literacy to maximize AI’s potential. Prashanth and Tariq stress the need for thorough data governance, ethical practices, and reliable analytics frameworks, pointing out that data quality is a core requirement for effective AI deployment. These experts propose a modular learning path—covering AI fundamentals, real-world use cases, implementation frameworks, and risk/ethics—to accelerate AI adoption. Collectively, they argue that sustained success in AI-driven finance depends on continuous learning, well-structured integration, and a culture of innovation.

Tariq and Prashanth emphasize the value of an AI-positive culture and rigorous data management to bring about meaningful finance transformation:

• AI Mindset & Digital Literacy Prashanth encourages CFOs to cultivate a “strategic mindset for AI.” Tariq highlights the importance of “digital literacy” so the finance team understands AI’s limitations and strengths.
• Practical AI Applications AI can enhance financial processes, bolster forecast accuracy and manage risk more effectively. CFOs should identify clear use cases, for example, invoice automation or predictive analytics for cash flow forecasting.
• Data Quality is Paramount High-quality data underpins successful AI models. Poor data undermines AI insights, so robust data governance is crucial. Prashanth recommends using his “4 to the power of 4” framework (covering data types, data views, analytics types, and data building blocks) to ensure data readiness.
• Ethical Considerations & Responsible AI CFOs must oversee the ethical implementation of AI, mitigating privacy issues and biases. This also involves transparency around algorithms and compliance with regulatory standards.
• Modular Learning & Continuous Upskilling Tariq proposes four modules to streamline AI adoption: (1) AI fundamentals, (2) real-world AI tools for finance, (3) practical AI frameworks and roadmaps, (4) risk/ethics.

Read the full article Here

3. Embracing AI in Finance and Accounting: Balancing Risk and Innovation

Author: Glenn Hopper with Guest Contributor Rachel Cappell

Glenn Hopper and Rachel Cappell discuss how powerful AI models like ChatGPT can streamline tasks in finance and accounting, despite their current shortcomings in quantitative analysis. They warn that AI’s rapid development demands robust data governance, security measures, and adaptive audits to ensure integrity and compliance. The authors see major potential for AI in high-level financial tasks (such as risk management and financial planning), provided continuous updates address emerging risks and governance gaps. Ultimately, they encourage finance professionals to embrace AI’s benefits while vigilantly managing the complexities and risks inherent in this fast-evolving technology.

Glenn and Rachel focus on balancing the extraordinary promise of AI with the inherent risks:

• AI’s Rapid Emergence With large language models (LLMs) like ChatGPT, Claude and Gemini, AI has reached mainstream adoption. While LLMs excel at generating human-like text, they are weaker at complex math tasks. Still, they can save time on routine workflows (e.g., drafting emails, basic accounting memos).
• Security & Governance LLMs are often cloud-based, raising concerns about data confidentiality. Hopper recommends robust data governance policies, training employees on secure usage, and monitoring for anomalies or leaks.
• Future: Beyond Text Generation AI-driven automation will expand to advanced use cases—audits, risk management, and financial analysis. The authors highlight potential new audit requirements (System and Organization Controls - SOC-1, SOC-2, etc.) for AI applications.
• Fine-Tuning AI Big players like Microsoft, Google, and Amazon are investing heavily in domain-specific AI. With a sufficiently large, relevant dataset (e.g., IFRS, SEC filings), it’s possible to train finance-focused AI for tasks ranging from compliance to advanced analytics.
• Staying Proactive Finance leaders must embrace a forward-thinking approach, balancing “risk aversion in favor of innovation and efficiency.” As AI evolves, so will CFO responsibilities, requiring ongoing learning and ethical AI stewardship.

Use A Practical Approach to Using Artificial Intelligence, to help lay out your AI roadmap.

Read the full article Here

10 Actions CFOs Should Take to Get AI Working for Their Team

Check ✔️

1. _______Articulate a Clear Strategic Vision

Define how AI will contribute to overarching business objectives, ensuring alignment with broader corporate goals. A focused vision is the compass for evaluating AI opportunities.

2. _______ Promote an AI-Positive Culture and Mindset

Embed a “strategic mindset for AI” within the finance function. Encourage experimentation, and visibly endorse the value AI brings to streamline routine finance tasks.

3. _______ Invest in Team Digital Literacy

Offer structured training (like “AI for Finance Leaders”) so that finance professionals deeply understand both the capabilities and limitations of AI models. This empowers the team to use AI tools effectively and responsibly.

4. _______ Identify High-Impact Use Cases

Use practical worksheets, such as the “AI in Finance – Identification Worksheet,” to pinpoint finance tasks where AI-driven automation or predictive analytics will yield the strongest ROI (e.g., invoice processing, reconciliation).

5. _______ Implement Robust Data Governance

Secure, accurate, and complete data is the bedrock of AI. Invest in data quality initiatives, formal policies, role-based access controls, and continuous monitoring.

6. _______ Establish an AI Roadmap and ROI Metrics

Outline a phased approach, defining target outcomes, technical requirements, success measures, and timelines. Revisit ROI projections periodically to prioritize and scale successful pilots.

7. _______ Collaborate with AI Specialists

Partner with specialized AI vendors, consultants, or internal data science teams. Their expertise accelerates adoption, ensures best practices, and helps navigate technical complexities.

8. _______ Balance Risk with Innovation

Proactively address data security, model biases, and compliance (e.g., potential new audit frameworks like SOC for AI tools). Include a risk register for AI deployments and update it regularly.

9. _______ Leverage Modular Implementation Frameworks AI Essentials (Concepts, Limitations)

Real-World Finance Use Cases Playbooks for AI Integration Risk and Ethics Using a structured rollout helps your team adopt AI smoothly and sustainably.

10._______ Champion Ongoing Learning & Adaptability

Echoing Julie Winkle Giulioni’s - “Just Skill Me” Mindset : Encourage continuous upskilling. Ensure the finance team adapts to rapid changes in AI technologies by regularly refreshing skills and experimenting with new AI tools and methods.

Conclusion

Across these three articles, Nathan Bell, Tariq Munir, Prashanth Southekal, Glenn Hopper, and Rachel Cappell collectively emphasize that AI in finance is more than just a technological upgrade—it is a transformative force. By blending a clear strategy, robust data governance, thorough training, and responsible risk management, CFOs can seize AI’s potential for efficiency gains, deeper insights, and competitive advantage. Embracing AI ensures finance teams stay agile, effective, and prepared for the next chapter in digital transformation.

Four of the Rock Stars featured above will be joining us at the FInEx AmeriEuro Summit on March 27th. Learn more and register here for free, FInEx AmeriEuro Summit

Thanks to Nathan Bell , Prashanth H Southekal, PhD, MBA, ICD.D , Tariq Munir , Glenn Hopper and Rachel Cappell, CPA for their commitment to leading the global charge teaching CFOs and their charges how to make AI a powerful yet safe tool in their operations. ????????????????

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