Building on the success of Nigel Garner’s recent talk, “The Power of AI in Accountancy: Practical Applications for Real Business Value”, this post-talk Q&A with the audience offered an invaluable opportunity to delve deeper into the practical and strategic considerations surrounding AI adoption.
From addressing foundational skills to balancing costs and value, the session uncovered key insights for accountancy firms ready to embrace AI.
If you missed the original blog outlining Nigel’s talk, read it here. In this follow-up, we explore the audience’s burning questions and the insights shared.
1. How Do We Ensure Foundational Skills Are Developed as AI Automates Routine Tasks?
A significant concern raised was the risk of losing foundational skills as AI takes over tasks such as bookkeeping, report generation, and basic decision-making. With AI handling these repetitive processes, how do we ensure future accountants and engineers still develop the critical thinking and problem-solving skills essential for higher-level work?
Nigel and the group acknowledged that while AI can handle many technical tasks, it is crucial to maintain a strong focus on education and training. The balance lies in using AI as a learning tool, not just an automation solution. For example, junior accountants could use AI to assist with tasks while simultaneously learning the reasoning behind AI’s outputs. This ensures they still grasp fundamental skills while benefiting from efficiency.
Key takeaway: We must focus on blending AI with hands-on learning. The future workforce will need to understand not only how to use AI but also why it makes certain decisions, ensuring human oversight remains strong.
2. Is AI Really Replacing Jobs or Simply Complementing Human Roles?
The group discussed the common fear that AI will replace accountants or reduce the need for human expertise. However, it was agreed in the group that AI should be seen as a complementary tool, elevating human roles rather than replacing them.
Nigel outlined three key AI models:
- Human in the loop: AI assists but doesn’t replace decision-making.
- Human over the loop: Humans oversee AI outputs, adjusting where needed.
- Human out of the loop: Full AI automation with no human involvement.
For most accountancy practices, the first two models offer the safest and most pragmatic path, ensuring that humans remain in control, using AI to improve accuracy, speed, and insight.
Key takeaway: AI is less about job replacement and more about job enhancement. By automating low-value tasks, professionals can focus on strategic, higher-value work, fostering growth rather than fear.
In my experience, AI is best viewed as a tool for human empowerment. It allows accountants to focus on the strategic, high-value tasks that machines can’t do.
Nigel Garner, CTO at Nimble Approach
3. How Do We Balance the Cost of AI Tools with the Value they Deliver?
Many attendees were concerned about the pricing of AI tools. Some AI vendors charge high rates, which raises the question of whether the value generated justifies the cost. Nigel pointed out that it’s crucial to assess whether off-the-shelf AI tools are sufficient or if a custom-built solution better fits a firm’s needs.
While off-the-shelf tools can be cost-effective and quick to implement, they often lack the integration and customisation that would generate deeper insights or handle more complex tasks. These wrapper applications tend to be thin veneers around existing models which are resold at high prices. Bespoke AI integration of off-the-shelf models, while more expensive, offer greater flexibility and long-term value and the lighter weight ‘wrapper’ applications.
Key takeaway: Firms must carefully evaluate their needs before investing in AI. Custom AI solutions can provide deeper business value, but for many, starting with affordable, ready-made tools is a good initial step.
4. What Role Does Data Quality and Governance Play in AI Success?
A major obstacle discussed was data quality. Nigel emphasised that “Good AI relies on good data.” Without solid data governance and high-quality datasets, AI models will fail to deliver accurate, valuable insights. This is a particular challenge in industries like accountancy, where data is vast and often siloed.
Learn more about our Data & AI Solutions here.
In response to questions about data privacy and security, it was agreed that strong governance protocols need to be in place. Businesses must safeguard sensitive financial data to ensure compliance with regulations like GDPR while maintaining client trust.
Key takeaway: Ensuring data quality and strong governance is the foundation for successful AI implementation. Companies must focus on cleaning, securing, and structuring their data before diving into AI.
5. What About the Ethical and Privacy Concerns Surrounding AI?
As AI technologies advance, so do concerns around ethical implications. The conversation turned to potential biases in AI, especially in areas like fraud detection or client data analysis. The fear of AI “hallucinations” (errors or unfounded outputs) and data misuse was also raised.
Nigel advised that firms need to maintain a human oversight role to monitor AI decisions. This ensures that ethical standards are upheld, and privacy concerns are addressed. Additionally, AI systems must be transparent, with clear explanations for how decisions are made.
Key takeaway: AI adoption comes with ethical responsibilities. Firms must prioritise transparency, build strong governance frameworks, and ensure that humans are always able to override AI when necessary.
6. How Can AI Help Me Give My Clients A Better Service?
One of the most exciting discussion points was how AI could provide enhanced services to clients. Beyond operational efficiency, AI-driven insights can give accountants the tools to offer more proactive, data-driven advice. Examples shared during the talk and Q&A included:
- AI-powered fraud detection to flag unusual transactions.
- Customised financial insights, helping clients make better decisions based on historical patterns and trends.
- Conversational AI, enabling accountants to interact with client data in real time, asking questions and retrieving insights instantly.
These innovations don’t just improve internal processes – they create a stickier, more differentiated client experience that sets firms apart from competitors.
Key takeaway: AI can deepen client relationships by providing smarter, faster, and more proactive insights, enhancing value beyond traditional accountancy services.
Preparing for AI’s Role in the Future of Accountancy
The discussions following Nigel’s talk reveal that the future of AI in accountancy is bright, but it requires careful, strategic implementation.
The key takeaway? Start small, focus on good data, and use AI to complement rather than replace human expertise. By adopting AI thoughtfully, firms can unlock new efficiencies, offer superior client services, and position themselves as forward-thinking leaders in the industry.
If you’re ready to explore AI in your accountancy practice, start by asking yourself: What can AI do to make my team’s work smarter, not harder?
Not sure where to begin? Nimble Approach helps firms define clear AI objectives and align them with their business goals. Then our Data and AI teams can make it happen. Get in touch to start your AI journey.
Authors Bio:
Nigel Garner, Chief Technology Officer at Nimble Approach:
Nigel has over 23 years experience working in Technology Consultancy across many sectors including FinTech, HealthTech and EdTech to name a few. Describing himself as a pragmatic technologist he has been working on AI and machine learning for several years with a strong focus on safe, real world value based implementation of emerging technology.
