Discussions surrounding big data and artificial intelligence (AI) technologies are taking centre stage within organisations.
Business leaders, board members and management accountants alike agree that AI has the potential to revolutionise the profession.
Essential questions arise as finance leaders are asking how big data and AI redefine success and create value for organisations. What does the future hold for accounting and finance at the intersection of big data and AI?
In the second episode of the Reshaping Finance podcast, Cathy R. Cobey, FCPA, CISA, AIGP, EY’s Global Responsible AI Leader for Assurance, and Trevor Hughes, President and CEO of the International Association of Privacy Professionals (IAPP), share key insights into AI fundamentals, risk management and best practices for finance professionals.
‘AI is not just one technology, but really an umbrella of AI systems’, said Cobey.
‘Many organisations already have predictive and generative AI systems, and now we’re moving towards agentic AI, AI that is more autonomous and can perform much more complex functions’.
AI is increasingly integrated into enterprise resource planning (ERP) systems. Understanding how and where AI is deployed within an organisation, and how AI is used to generate value in decision-making, is critical for maximising its value.
The podcast episode, Big data and AI technologies: Fundamentals and applications, focusses on challenges to AI adoption and how doing data governance well gives you a superpower.
Navigating privacy challenges in AI
The intersection of AI with privacy laws and regulations is complex. In the podcast episode, Trevor Hughes highlighted the growing risk of unmonitored AI applications in everyday business tools.
‘Shadow AI is a growing reality in organisations. Many tools, like word processors, email clients and social media platforms are now embedding AI functionalities. These tools often operate outside the formal oversight of IT or compliance teams, creating risks that organisations need to proactively manage’, Hughes said.
The significant overlap between AI and privacy issues adds to the complex intersection of AI policies, laws and standards.
With an intricate network of global data protection laws, it’s crucial to stay informed to ensure compliance while also taking advantage of the efficiencies driven by AI.
Governance and data protection: A superpower
Finance professionals who establish strong governance frameworks will be better equipped to handle developing AI regulations.
‘If you do data governance well, it gives you a superpower. It allows you to respond to emerging standards and laws in a far easier and less costly way, especially in finance and accounting, where data is so sensitive’, Hughes said.
Management accountants play a critical role in establishing secure AI frameworks. Robust governance, cross-functional collaboration and proactive data protection strategies are vital.
‘Finance and accounting professionals are likely to be the governance, risk and control experts within their organisations. They need to educate themselves so they can be at the table when decisions about AI systems and data are being made’, EY’s Cathy Cobey said.
Ensuring strong collaboration between finance teams and data security experts is key to mitigating AI risks, and data privacy must be a top priority.
‘Finance professionals need to be privacy champions within their organisations. They touch some of the most sensitive data, and a little bit of education and a strong relationship with the privacy team can go a long way’, Hughes said.
Secure AI implementation requires precise control mechanisms, encryption and authentication protocols.
Deepfakes, as an example, pose emerging risks to financial security. According to Cobey, deepfakes have become a significant control risk for finance professionals.
‘We’ve seen cases where a customer or vendor calls in, but it’s actually a deepfake of their voice, leading to unauthorised financial transactions’.
Management accountants must lead AI governance
Data protection laws vary widely across different regions and countries, creating a complex legal landscape for organisations to navigate. For example, the General Data Protection Regulation (GDPR) in the EU has stringent requirements for data handling and privacy, whilst the California Consumer Privacy Act (CCPA) in the United States has its own set of rules.
Organisations must ensure compliance with multiple, sometimes conflicting, regulations, which can be resource-intensive and complicated.
According to Hughes, ‘The greatest challenge organisations face is the complex intersection of data protection laws, AI standards and other issues like intellectual property and algorithmic discrimination. It’s going to take a team to navigate these challenges effectively’.
AI is significantly affecting finance, and management accountants must be proactive in its adoption, risk management and compliance.
Through professional development, collaboration with security teams and championing data governance, finance leaders can harness the potential of AI while protecting sensitive financial data.
For more insights, listen to the full Reshaping Finance podcast episode.
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