By Philippe Omer Decugis, General Manager EMEA & SVP Sales, BlackLine
Artificial intelligence continues to attract significant attention in the business world, yet for many finance and accountancy professionals, the objective isn’t wholesale disruption. Rather, the focus is on operational efficiency: completing the close process more quickly, reducing manual errors, and ensuring teams are not working late into the night at month-end.
Crucially, AI is already capable of delivering these outcomes. From improving data integrity to streamlining the financial close and freeing up capacity for more strategic tasks, its practical applications are tangible. The key lies in understanding where AI can add value today, and how to implement it in a way that complements existing processes.
Improving data processes for sharper insight
One of the most immediate challenges in finance and accounting is the time consumed by manual data handling. Professionals routinely spend hours chasing figures, checking calculations, and aligning spreadsheets before they can begin meaningful analysis. AI can alleviate much of this burden.
With the appropriate tools, AI systems can structure and categorise financial data, identify inconsistencies, and highlight emerging trends. This not only improves reporting accuracy but also enables faster forecasting and a clearer view of overall business performance.
Enhancing the financial close
The financial close remains one of the most demanding elements of the finance function, and is often a time-intensive and error-prone process. AI-powered automation can reduce this burden by taking on routine tasks such as account reconciliations and journal validations.
While generative AI is concerned with content creation, agentic AI is built to execute actions – mirroring the tasks a human preparer might undertake. In practice, this means software can manage much of the transactional work involved in the close, allowing finance professionals to concentrate on exception handling and quality assurance. The result is a more efficient process and greater confidence in the accuracy and completeness of reported figures.
Delivering ROI in a cost-conscious environment
In today’s economic climate, finance leaders are rightly focused on return on investment. AI, when implemented thoughtfully, can deliver meaningful gains in a relatively short timeframe.
By automating repetitive processes – such as transaction matching, invoice processing, and anomaly detection – teams can reduce operational risk and free up valuable time each month. In addition to improving efficiency, AI can also generate insights that drive better business decisions. These may include identifying areas of revenue leakage, flagging emerging risks, or producing data-driven commentary that reflects the true financial position of the organisation.
Building skills for an AI-enabled function
Successfully integrating AI into the finance function isn’t solely a technological task: it’s also about people. Teams must develop the confidence and capability to engage effectively with AI tools.
This begins with foundational AI literacy: understanding how the technology works, how its outputs should be interpreted, and how best to apply its insights. Just as importantly, finance professionals must adapt to a new way of working – one that places greater emphasis on review, judgement and strategy, while routine work is increasingly handled by technology. It’s important to support this shift by embedding AI learning directly into the product experience, helping users build capability as they work.
Forward-looking CFOs are already taking steps to prepare their teams. Some are appointing finance transformation leads; others are incorporating AI training into development pathways. What unites these approaches is a recognition that upskilling is essential to long-term success.
Adapting to a changing landscape
The rapid evolution of AI is also reshaping the external environment. Traditional business process outsourcing (BPO) models are being challenged by AI’s ability to deliver similar outcomes – faster and at lower cost. Many BPO providers are now investing heavily in AI, acknowledging that the model of labour-based service delivery is under threat.
For finance leaders, this represents both a risk and an opportunity. The risk lies in inertia – falling behind to more agile competitors or relying too heavily on point solutions. But the opportunity is significant: to drive transformation internally, reduce dependency on third parties, and re-establish finance and accounting as a strategic function.
A path towards autonomous finance
Looking ahead, the trajectory for finance is increasingly clear. The future lies in autonomous systems – not in the sense of removing humans from the process, but in empowering AI to monitor performance, identify inefficiencies, and make proactive recommendations for improvement.
In this model, finance professionals take on more strategic roles as reviewers, advisors and exception handlers. AI, meanwhile, operates behind the scenes – processing data, flagging risks, and generating tailored narratives for different stakeholders. This isn’t a speculative vision. It’s already being realised in forward-thinking organisations, and those who act now will be best positioned to lead in the next phase of finance transformation.