How NRI’s former CFO is using AI to achieve cost optimisation
Jodie Meadows, former CFO at NRI ANZ, and Shilpa Bhale, Director of Strategy and Product Management at Oracle, discuss the transformative role of finance in fostering innovation and the importance of adopting AI and technology within financial operations.Jodie Meadows, former CFO at NRI ANZ, and Shilpa Bhale, Director of Strategy and Product Management at Oracle, discuss the transformative role of finance in fostering innovation and the importance of adopting AI and technology within financial operations at CFO Edge.
Shilpa outlines her role at Oracle, highlighting her focus on finance transformation to boost agility, compliance, and efficiency in financial processes.
By leveraging Oracle’s ERP Cloud Fusion, Shilpa collaborates with finance leaders to embed AI and machine learning, automating routine tasks and enhancing data quality to deliver accurate insights and predictive analytics.
This automation supports seamless, touch-free operations, allowing finance teams to move away from mundane tasks and improve decision-making, expediting month-end processes and enabling strategic business outcomes.
Jodie shares her experience leading a digital transformation at NRI, where finance has a pivotal role in driving ERP-led innovations.
She discusses the increasing involvement of CFOs in technology decisions due to their broad organisational view, which allows them to balance innovation with risk management effectively.
Jodie notes that integrating AI within an ERP framework governed by finance simplifies implementation and minimises risks.
She envisions finance moving from traditional historical analysis to predictive insights, enabling finance teams to focus on forward-looking data and collaborate more with other departments.
Both speakers agree that balancing innovation with risk requires trust in AI, robust data governance, and a gradual adoption approach to maintain compliance and data accuracy while empowering finance functions.
CFOs are encouraged to adopt a cautious yet proactive approach to integrating AI within organisations, focusing on specific use cases as a practical starting point.
Leveraging vendor-maintained AI within existing software (such as Oracle Fusion) allows organisations to balance innovation with risk, without needing extensive investment or management.
This incremental, use-case-driven approach helps demonstrate AI’s value, securing buy-in from key decision-makers and delivering a clear return on investment.
The conversation also highlighted the importance of evolving workplace skills and culture—fostering curiosity, adaptability, and collaboration, especially in traditionally siloed areas like finance.
Early AI adoption has enabled finance teams to automate tasks, reallocate resources, and reduce headcount, indicating a shift towards roles requiring broader analytical and communication skills.
Jodie and Shilpa also discussed the need to nurture a data-driven culture, where aligning teams around data objectives can mitigate resistance and build trust.
Their core message was to embrace experimentation, utilise available AI tools, and foster a partnership with technology, supporting a gradual AI adoption aligned with organisational goals.
Key Takeaways
- Start small, experiment, and build trust: Organisations should start by trialling specific AI applications, particularly those embedded in existing software solutions, to balance innovation with risk. This enables teams to build trust with AI while showcasing clear, tangible business value and gaining support from decision-makers.
- Evolve skills and create a data-driven culture: As automation frees up resources, employees need to develop new skills, particularly in communication and analysis, to adapt to evolving roles. Cultivating a culture of curiosity and collaboration, where teams work together to understand and leverage data effectively, is essential to maximising the value of AI and data.
- Leverage existing technology and align teams: Many organisations already have AI capabilities embedded in their software, which should be fully utilised to maximise value. Fostering alignment across departments and prioritising data-sharing and collaboration can reduce resistance, ensuring that AI initiatives integrate smoothly with the broader business strategy.