AI Readiness: Navigating the AI Revolution

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In this article, we will examine several key considerations related to AI readiness that Chief Financial Officers (CFOs) need to focus on to fully harness the capabilities of Artificial Intelligence (AI). AI is set to bring significant changes to the evolving role of the CFO, particularly through its integration into the broader financial operations function. CFOs are increasingly required to offer real-time decision-making, interpret results and forecasts using data-driven insights, and lead automation initiatives. Therefore, embracing AI readiness is essential for CFOs to remain competitive and excel in a complex, data-centric business environment.

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Establish AI Governance

When implementing AI throughout an organization, it is essential to do so in a structured and coordinated manner. A strategy for achieving this is to form a steering committee focused on AI. This committee should consist of members from various departments, including, at the very least, experts in finance, operations, and technology. Its primary role is to guide the overarching AI strategy and ensure that its execution is harmonized across the organization. The main responsibilities of the committee include:

• Establishing governing policies addressing the acquisition and use of AI
• Identifying and prioritizing potential AI uses
• Identifying and evaluating key AI risks
• Supervising the ethical and responsible implementation of AI solutions

This diverse group of stakeholders enables the organization to approach AI in a well-rounded and informed manner.

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Address Regulatory, Compliance and Ethical Considerations

When adopting AI, CFOs must dedicate significant time to thoroughly investigate the regulatory and compliance impacts of AI on their company, customers, vendors, and other stakeholders. Understanding these implications is crucial for ensuring that the deployment of AI aligns with various legal and ethical standards. Examples of requirements to consider include:

• SOX Compliance: Assessing how AI affects financial reporting, internal controls, and corporate governance
• ESG Considerations: Understanding the impact of AI on Environmental, Social, and Governance (ESG) factors, alignment with the company's ESG goals and relevant sustainability standards
• Data Privacy: Evaluating how AI processes personal data considering global privacy regulations such as General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA), and others; securing proprietary corporate data and information to protect it from unwanted or unauthorized consumption
• Cybersecurity: Ensuring that AI systems are secure against cyber threats and breaches, complying with established cybersecurity standards and frameworks
• Other Regulatory Domains: Investigating how AI impacts sector-specific regulations, international trade laws, anti-money laundering directives, ethical guidelines, etc.

By taking the time to understand these areas, CFOs can ensure that their organization’s AI adoption is not only compliant but also responsible, aligning with broader organizational values and maintaining the trust of customers, vendors, and other stakeholders.

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Prepare for Adoption through People Engagement

For successful AI adoption, organizations must focus on engaging their workforce and cultivating buy-in. The CFO has a crucial role in this process, not just in aligning financial strategies with AI implementation but also in leading the drive for organizational alignment and skill-building in AI.

• Championing an AI-Adaptive Culture: CFOs should lead efforts to create a culture receptive to AI, by addressing any apprehensions about AI, highlighting its benefits, and fostering collaboration. Initiatives could include regular communications, collaborative forums, etc. to discuss AI's impact and uses, thereby easing fears and misconceptions.
• Encouraging Skill Development and Training: It’s vital to invest in training and upskilling programs that enable finance professionals to effectively utilize AI tools
• Strategic Investments in AI: The CFO should lead the strategic investments in AI ensuring organizations conduct in-depth cost-benefit analyses and a strong business case for key AI initiatives.

By taking a leadership role in this area, the CFO can help the organization navigate the changing landscape of AI, ensuring both technological advancement and people alignment.

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Scale Infrastructure

For effective AI adoption, the CFO must work closely with IT to evaluate and enhance the necessary IT infrastructure. This collaboration is key in identifying and implementing the right technological foundations for AI. Essential IT considerations may include:

• Computing and Data Storage: is there sufficient computational power and storage to meet the demands of AI?
• Network Capabilities: Can existing networks handle AI's data processing needs, with adequate bandwidth and speed?
• Cloud-Based Solutions: Are there cloud computing solutions that can offer greater scalability and flexibility, to meet the demands of AI?
• Security and Compliance: What additional security measures are required to adopt AI technologies?
• Integration with Existing Systems: How will AI integrate and operate with existing systems and applications? How do you create a smooth integration between new AI tools and existing tech?
• Remote and Mobile Work Support: Are changes required to the infrastructure to support remote access to AI resources, catering to modern work environments?

By collaborating on these IT considerations, the CFO can help ensure that the organization's IT infrastructure is adequately prepared for AI adoption, aligning technological capabilities with the company's strategic AI objectives.

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Data Readiness

The effectiveness of certain AI applications, including those involving machine learning and Generative AI (GenAI), are heavily reliant on the availability and quality of data. Therefore, data is a critical readiness area. Furthermore, GenAI can be greatly enhanced when using retrieval augmented generation (RAG).

RAG combines the power of information retrieval with GenAI models. It first retrieves relevant information from a large dataset and then uses this information to generate more accurate and contextually relevant outputs.

For businesses, it's vital to assess the quality and accessibility of their data, ensuring the following:

• Availability of Data: Data exists, is readily accessible and available for AI processes.
• Structured, accurate and Unbiased Data: Data is organized, consistent, and free from biases and errors that could skew AI outcomes.
• Robust Data Governance: Data governance practices are in place for maintaining the integrity and reliability of the data.

When addressing these considerations, finance leaders can also consider how to leverage GenAI as a tool for data collection and organization. GenAI has the capability to gather data and create structured formats for data points that were previously unstructured. This approach can enhance the overall effectiveness of their AI initiatives.

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Conclusion

Artificial intelligence is set to significantly change the finance function and organizations as a whole. Those who are prepared stand to benefit greatly. It's important to understand the potential of AI and address key readiness issues as part of this process. When exploring AI and planning your adoption strategy, make sure to spend time evaluating your readiness and allocating resources to address essential readiness factors. This will help ensure you keep pace with the evolving landscape of AI.

At Connor Group, our AI subject matter experts stand ready to collaborate with you, providing practical AI solutions tailored to your organization's needs. By leveraging their insights and expertise, you can not only stay ahead of the AI curve but also build a powerful technology strategy that maximizes automation and value. As AI continues to evolve, let's embark on this exciting journey together, adapting and thriving in a world of boundless possibilities.

If you're seeking to adopt AI and looking to understand what key readiness tasks you need to address, contact Connor Group. Leveraging both our operational and technology expertise, we'll share our experiences and help you create practical AI roadmap.

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Authors

Jason Pikoos - Managing Partner, Client Experience

Tim Brandt - Partner

Erik Olson - Director, Digital Solutions