As artificial intelligence continues to weave itself into the fabric of global finance operations, the same shift is beginning to take root in the Maldives. From streamlining processes to reimagining job roles, AI is forcing finance teams to rethink not only how they work, but what skills they value and what the finance function ultimately stands for.
Across industries, traditional roles in finance are being redefined. The idea that AI merely automates the mundane is giving way to a new reality: AI does not just do the grunt work, it now performs entire layers of operational tasks that once defined entry-level finance jobs. From invoice reconciliation to vendor analyses, tasks that required human labour just a few years ago are increasingly handled by intelligent systems that can process large volumes of data with greater speed and accuracy.
What this means for finance professionals is twofold. Firstly, finance staff are shifting from doing the work to reviewing the work. AI becomes the junior team member that needs to be audited, not simply used. This change introduces new responsibilities. Professionals must now validate AI outputs, ensure financial accuracy, and translate these results into actionable insights for decision-makers.
Secondly, entry into the finance profession may become more complex. The traditional route of starting in data entry or basic reconciliation tasks no longer offers the same foundational training when such tasks are handled by machines. There is an emerging risk that young professionals will be left without the hands-on experience they need to develop expertise. To mitigate this, organisations may need to rethink how they onboard and train new hires, incorporating supervised AI workflows and structured learning environments.
As AI reshapes job responsibilities, it is also altering the skill sets that finance teams must cultivate. A basic understanding of accounting principles is no longer enough. Data literacy, familiarity with coding languages like SQL, and the ability to work with large datasets are becoming essential. For a country like the Maldives, where the finance sector is still building its technological base, this presents both a challenge and an opportunity.
Local businesses, especially SMEs and institutions in the public sector, may need to invest more deliberately in upskilling their workforce. Initiatives like internal AI training sessions, collaborative innovation challenges, and partnerships with local academic institutions could help close the skills gap. For larger financial institutions, the path may lie in creating hybrid roles. These are professionals who understand both finance and technology and who can bridge the divide between automated systems and strategic decision-making.
Perhaps most significantly, the shift to AI is changing how finance departments define their core value. Instead of being seen solely as gatekeepers of transactional data, finance teams are increasingly positioned as internal advisors, helping organisations extract meaning from financial data and shape future strategy. The focus is no longer on process execution but on insight generation and value creation.
Yet this transformation is not without regulatory implications. The introduction of AI into audits, reporting, and financial decision-making brings with it concerns about accountability, oversight, and accuracy. Maldivian financial regulators and professional bodies may soon have to grapple with the same questions their global counterparts are facing, such as how to ensure that AI-led processes remain trustworthy, compliant, and transparent.
In this evolving landscape, one thing remains clear: the finance function cannot afford to stay still. Whether through public policy, private sector innovation, or professional development, the future of finance will depend not just on adopting technology but on redefining the human role within it.
