From Automation to Autonomy: How Much Should Finance Departments Trust AI?
For years, the promise of automation in finance has been straightforward: let technology handle mundane, repetitive tasks, freeing people to focus on what really matters.
The arrival of AI agents changes the proposition. Systems are no longer simply assisting with tasks but can increasingly determine what needs to be done and take action themselves.
For many people, this marks the point at which the promise of AI transforms from aspiration into reality.
But Rentia Burger, Head of SAP Consulting at Monocle Solutions, warns there is a catch: “Giving a machine more autonomy does not make a flawed process a good one, or unreliable data trustworthy.”
“In fact, the more autonomous the function becomes, the more ruthlessly its underlying weaknesses are exposed.”
The question, then, is no longer simply what an organisation can automate, but what it should – and whether the data, processes and controls in place are robust enough to trust AI to safely operate more autonomously.
As organisations increasingly look to scale AI across their operations and unlock greater value from this technology, SAP and other enterprise technology providers are moving beyond copilots that assist with individual tasks towards autonomous agents that can connect systems, coordinate activities and take meaningful action.
For finance functions, the potential applications of these agents are significant, encompassing reconciliations, reporting, planning, financial close processes, controls and exception management.
With Gartner estimating that by 2030, at least 15% of day-to-day finance work decisions will be made autonomously by AI agents, this promises significant efficiency gains – but it will also fundamentally change how finance teams operate.
As processes become increasingly automated and continuously monitored, AI agents will take on more of the routine work of gathering information, checking dependencies, identifying risks and coordinating responses.
This can accelerate decision-making and reduce the friction between reaching a conclusion and acting on it, while allowing human intervention to become more focused.
In practical terms, this means AI agents will increasingly move beyond a supportive role to acting autonomously.
For example, SAP’s finance-focused AI agents can validate banking details, predict payment risks, identify invoice clearing patterns, manage exceptions, route unresolved items to the appropriate teams and provide proactive recommendations to improve cash flow and working capital outcomes.
As agents assume a growing share of routine and, increasingly, more complex judgements, this will allow finance professionals to spend less time on the mechanics surrounding decisions and concentrate on where they add greatest value: applying critical thinking, creativity and human judgement gleaned through years of experience to interpret insights, consider context and navigate complex situations.
Burger highlights that the pace of AI innovation can, however, obscure a more fundamental constraint: the ability to delegate tasks to an AI agent depends heavily on the quality of the foundations underpinning it.
Agents require trusted data, well-defined processes, appropriate access controls and robust governance to perform optimally and reliably.
They must understand how processes connect, how decisions and exceptions flow through the business, and the relationships between customers, suppliers, financials and operations.
Their actions must also be explainable, auditable and aligned with sound governance policies.
“Without these fundamentals in place, organisations risk simply automating existing inefficiencies, or even creating new ones, rather than meaningfully transforming and enhancing their operations,” says Burger.
This means that scaling AI is ultimately an organisational challenge as much as a technological one. People, processes, data and governance all need to be aligned to create the conditions in which AI can be trusted to operate, while keeping humans at the helm of the decisions that truly shape the business.
How Monocle Can Help
SAP provides the connected foundation for tighter control, faster insight and better decision-making – but many financial institutions fall short of realising its full potential, held back by fragmented data, complex processes and legacy technology that cannot keep pace with evolving business needs.
This is where Monocle comes in. With decades of experience in financial services, we combine industry knowledge with specialist SAP technology expertise to ensure the solutions we help our clients to design and implement reflect the realities of running and transforming a financial institution.
We work across the full SAP agenda, from defining a value-led transformation strategy aligned with your organisation’s risk and regulatory environment, through to delivering practical solutions that produce immediate business value, while also remaining agile enough to embrace future innovation.
SAP transformation is not simply a technology programme; it’s an opportunity to rethink how information moves, how decisions are made and how the organisation performs.
With Monocle, you gain a partner that understands the technology, the transformation and the environment in which it must succeed.
Click here to learn more about SAP Consulting at Monocle Solutions.
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