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Summit 2025 Recap #1: Future-Proofing Your Finance Career: How CFOs Can Thrive Alongside AI
Welcome to the CFO Connect Summit 2025 Recap Series — your go-to source for key insights and actionable takeaways from 2025’s most impactful finance leadership sessions.
On October 07, 2025, at the CFO Connect Summit, nearly 500 finance leaders gathered virtually to explore one of the most pressing topics facing the profession today: how to future-proof finance careers in the age of AI.
The session, titled "Future-Proofing Your Finance Career," covered upskilling strategies, salary trends, and practical approaches to thriving alongside artificial intelligence. For senior finance professionals navigating this technological transformation, the insights shared offer a roadmap not just for surviving but for excelling in an AI-driven finance landscape.
The discussion revealed compelling statistics that underscore the urgency of this topic: 56% of finance leaders now use AI in their work (up from just 17% in 2023), with 35% using ChatGPT daily. Yet most applications remain focused on administrative tasks rather than core finance processes, highlighting the significant opportunity ahead.
Speaker Credentials
The session featured two distinguished finance leaders bringing diverse perspectives on AI adoption:
Jessica Pillow, Global Head of Total Rewards at Deel – With over 20 years in compensation and total rewards, Jessica oversees programs for 7,000+ team members across 120+ countries at the global people platform. Her extensive experience in global compensation provides unique insights into how AI is reshaping talent strategies and salary expectations.
Mike Sang, Director of Finance at ARIA (Advanced Research and Invention Agency) – As Finance Director at the UK government's breakthrough technology funding agency, Mike manages a £1 billion R&D portfolio spanning everything from quantum computing to synthetic biology. His role at the intersection of finance and cutting-edge technology offers practical insights into implementing AI tools in complex, regulated environments.
Key Session Themes & Takeaways
Theme 1: Adopting an Experimental Mindset
Both speakers emphasised that there's "no playbook" for AI adoption in finance, underscoring the need for an experimental approach. Jessica highlighted Deel's strategy of "treating AI like a product" – constantly testing, iterating, and making incremental improvements. This approach enables organisations to identify effective strategies without requiring massive upfront investments.
Mike stressed the importance of making AI adoption "inspiring, not intimidating" for teams. He advocates for approaching AI implementation from first principles, encouraging curiosity and embracing failures as learning opportunities. This experimental mindset is particularly crucial because AI ROI may not be immediately apparent, requiring longer-term thinking.
Practical Application: Finance leaders should start with small pilots, focusing on high-friction, repetitive tasks. Create structured assessment processes to identify pain points in daily, monthly, and quarterly cycles, then systematically test AI solutions.
Theme 2: The Evolution of Finance Team Structures
A significant discussion emerged around the future shape of finance teams. Mike described the transformation from traditional "consulting pyramids" to more "obelisk-like" structures with fewer junior positions but enhanced strategic roles for remaining team members.
Rather than viewing this as a threat, both speakers positioned AI as an opportunity to elevate finance professionals. Jessica noted she now views "AI just as much as a resource as my headcount," fundamentally shifting how she thinks about team capacity and capabilities.
Key Insight: The most successful approach is to use AI to eliminate mundane, transactional work, freeing finance professionals to focus on strategic, value-added activities that require human judgment and business intimacy.
Theme 3: Skills and Competencies for the AI Era
When asked about essential skills, Mike identified two critical areas: curiosity and rigour. Finance professionals already excel in this area, but AI amplifies their importance. Curiosity drives experimentation and vision exploration, while rigour ensures structured adoption with clear roadmaps and measurable outcomes.
On the technical side, experience with data structures and warehousing systems becomes increasingly valuable. However, the most exciting development is the ability for finance professionals to prototype AI-enabled tools themselves using platforms like Lovable, Airtable, or Google AI Studio – without requiring technical staff involvement.
Career Development Focus: Finance professionals should prioritise developing skills in workflow automation (chosen by 52% of session attendees as the most critical AI skill), followed by data literacy (23%).
Theme 4: Responsible AI Implementation
Both speakers emphasised the critical importance of responsible AI adoption, particularly in finance, where compliance and confidentiality are paramount. Jessica stressed the importance of clear AI policies and enterprise-wide solutions to prevent "shadow AI" usage, which could compromise sensitive financial data.
Mike highlighted the importance of maintaining human decision-making authority, using AI as a tool alongside human judgment rather than replacing it entirely. This approach builds trust both internally and with external stakeholders.
Compliance Framework: Implement enterprise AI licenses, establish clear usage policies, and maintain human oversight for all AI-generated outputs, especially in regulated environments.
Practical Implications for Finance Leaders
Based on the session insights, finance leaders should take these actionable steps:
Start with High-Impact, Low-Risk Applications: Focus on repetitive tasks like expense reimbursement processing, resume screening, or compliance checking – areas where errors have limited strategic impact but efficiency gains are significant.
Develop Structured AI Assessment Processes: Create systematic approaches to identify friction points in your finance operations, evaluate potential AI solutions, and measure implementation success using existing KPIs rather than creating AI-specific metrics.
Invest in Upskilling Initiatives: Whether through formal training programs, peer learning networks, or experimental projects, ensure your team develops AI competencies that will become as essential as Excel skills are today.
Position AI Investment at Board Level: Jessica's approach of evaluating AI investment against headcount expenses provides a framework for securing executive support and resources for AI initiatives.
Build Cross-Functional Partnerships: Engage more deeply with your SaaS providers as they integrate AI capabilities, treating these relationships as partnerships rather than vendor arrangements.
Challenges & Pitfalls to Watch
The speakers identified several common obstacles in AI adoption:
Data Security and Compliance Risks: Organisations must guard against employees using unsecured AI tools with confidential financial data. Implement enterprise solutions and clear policies before individuals create workarounds.
Over-Focus on Cost Savings: While efficiency gains are significant, the real value of AI lies in enabling strategic insights and decision-making capabilities that weren't previously possible.
Inadequate Change Management: Mike emphasised the ethical responsibility to existing employees, ensuring AI adoption enhances rather than threatens career development paths.
Premature ROI Measurement: Both speakers cautioned against rigid ROI tracking in early experimentation phases, as the most valuable AI applications may have longer-term, strategic benefits that aren't immediately quantifiable.
Key Quotes & Sound-bites
"There's definitely no playbook... we're all sitting around wondering how we have this AI and it's not going anywhere. What we're doing at Deel is treating it like a product – constantly testing, iterating, making small incremental movements." — Jessica Pillow, Global Head of Total Rewards, Deel.
"You've really got to make this transition inspiring and not intimidating. You need an almost experimental mindset because we're all learning with this." — Mike Sang, Director of Finance, ARIA.
"I am viewing AI just as much as a resource as my headcount. That mindset shift has really gained traction and excitement on the change curve." — Jessica Pillow.
Real-World AI Applications Shared
Jessica's LinkedIn Talent Insights Integration: Deel utilises AI-powered talent capacity heat maps to pinpoint optimal hiring locations for specific roles and skills. This data is then integrated with their applicant tracking system, enabling automated candidate screening from a database of 1.5-2 million applications annually.
Mike's Bespoke Compliance Tools: ARIA developed custom AI tools to automate R&D portfolio compliance checks across its £1 billion funding portfolio, enabling faster, more thorough reviews of expenditures while freeing staff for strategic analysis.
Expense Management Automation: Both organisations highlighted AI applications in expense reimbursement processing, using AI to scan and categorise business expenses while maintaining human oversight for final decisions.
Salary Impact and Career Implications
Jessica provided exclusive insights from Deel's upcoming global compensation report, revealing an uptick in AI-specific roles and salary premiums globally. However, she predicts that this premium will normalise within a few years as AI skills become embedded in core functions – similar to how data science evolved from a premium speciality to a standard expectation.
For finance professionals, Mike's recruiting approach focuses on behaviours rather than specific AI experience: candidates who can approach problems from first principles, work with data structures, and demonstrate creative problem-solving mindsets. However, the moderator noted that employers increasingly ask candidates about familiarity with AI tools and automation experience as differentiating factors.
Career Strategy: Finance professionals should actively document their AI experimentation and implementation experiences, as this practical experience becomes increasingly valuable in the job market.
Frequently Asked Questions
How is AI changing finance careers?
AI is transforming finance careers by automating repetitive, transactional tasks and elevating professionals to more strategic roles. Finance teams are transitioning from traditional pyramid structures to leaner, more strategic units, where professionals concentrate on analysis, decision-making, and business partnerships rather than manual processing. This shift requires finance professionals to develop new skills in workflow automation and data literacy, all while maintaining their core competencies in curiosity and analytical rigour.
What AI tools should CFOs use?
CFOs should focus on three categories of AI tools: Large Language Models (like ChatGPT) for cognitive tasks and problem-solving, AI-enabled features within existing SaaS platforms (like Spend Desk), and bespoke tools built using platforms like Lovable, Airtable, or Google AI Studio. The key is to start with high-impact, low-risk applications such as expense processing, compliance checking, and talent screening, before expanding to more complex strategic applications.
How can finance leaders measure ROI from AI initiatives?
Rather than creating AI-specific metrics, finance leaders should use existing KPIs and measure how AI implementation improves them. Focus on operational efficiency gains, time savings that enable strategic work, and quality improvements in decision-making. However, avoid rigid ROI tracking during experimental phases, as the most valuable AI applications may have longer-term strategic benefits that aren't immediately quantifiable.
What skills do finance professionals need for the AI era?
The most critical skills are curiosity and rigour – qualities finance professionals already possess but that AI amplifies in importance. Technical skills should focus on workflow automation (a priority for 52% of finance leaders) and data literacy. Additionally, experience with data structures and warehousing systems, and the ability to prototype AI-enabled tools using no-code platforms, become increasingly valuable for career advancement.
How should organisations implement AI responsibly in finance?
Responsible AI implementation requires clear policies, enterprise-wide solutions, and maintained human oversight. Organisations should implement enterprise AI licenses to prevent "shadow AI" usage with confidential data, establish clear usage guidelines, and ensure human decision-making authority remains paramount. Focus on compliance and confidentiality, especially in regulated environments, while building trust through transparent communication about AI's role as a tool alongside human judgment.
Recommended Resources & Further Learning
CFO Connect Tools Report: Access the latest research on AI adoption trends among finance leaders
Peer Learning Networks: Both speakers emphasised the value of finance-focused AI discussions over generic AI courses
Platform Experimentation: Explore tools like Lovable, Airtable, and Google AI Studio for hands-on AI application development
LinkedIn Learning and YouTube: For practical, concrete examples of AI implementation rather than theoretical frameworks
Conclusion
The message from this CFO Connect Summit session is clear: AI adoption in finance is no longer optional – it's essential for professional relevance and organisational success. However, success requires thoughtful implementation that balances experimentation with governance, efficiency with strategy, and automation with human judgment.
Finance leaders who adopt an experimental mindset, invest in their teams' AI capabilities, and prioritise high-impact applications will not only future-proof their careers but also position themselves as strategic drivers of organisational transformation. The opportunity window is open, but it requires action now.
Ready to future-proof your finance career? Join the CFO Connect community to access the full session recording, connect with fellow finance leaders navigating AI adoption, and download practical resources for implementing AI in your organisation.
