Why agentic AI is becoming non-negotiable for finance

Technology

Sponsored by Esker

Since generative AI exploded onto the scene in 2022, it has dramatically reshaped our personal and professional lives in ways not previously seen since the advent of the internet.

Its near-instant capacity to synthesise information and jumpstart strategy, productivity and decision-making has been transformative. CFOs and other finance leaders – navigating in an era of heightened complexity and margin pressure – have taken notice.

But before they could even finish hitching their wagon to gen AI’s promise and potential, another fast-emerging AI technology has rapidly staked its claim as the real next frontier: agentic AI.

Gartner forecasts that, by 2028, 33 per cent of enterprise software applications will include agentic AI and 15 per cent of day-to-day work decisions will be made autonomously – a prediction that suggests agentic AI is far more than a passing trend.

This shift signals a broader evolution in enterprise AI. When financial agility is at a premium, agentic AI offers a valuable opportunity to rethink the operating model of finance with a stronger emphasis on orchestration, scalability and resilience at the core.

But how exactly does agentic AI work, and why is it getting so much attention? Perhaps more importantly, if it is becoming a “non-negotiable”, what are the safest, most practical and proven ways for enterprises to use the technology?

From digital assistants to autonomous agents: harnessing agentic AI’s true value

More than ever, the demands on today’s finance leaders are tied to real business outcomes – from faster close cycles and lower operational costs to optimised working capital and cash flow. In this regard, despite its immense and impressive capabilities, gen AI’s value often plateaus at “assistive”.

Agentic AI goes a step beyond prompts and suggested actions to orchestrate actual business execution, with AI agents capable of initiating, adapting and completing tasks autonomously.

For example, where gen AI can generate a report or surface a forecast, agentic AI can assess that forecast, cross-reference variables and take specific actions (for example, triggering a workflow, engaging a supplier, initiating a follow-up).

These are more than theoretical use cases. In fact, they’re already being deployed across key business processes and functions, such as:

Autonomous collections forecasting that not only predicts when invoices will be paid but adjusts dunning strategies in real time
AI-led procurement that reconciles invoices against contracts, flags discrepancies and initiates approval routing without unnecessary human intervention
Adaptive workflows that sense disruptions (such as supply chain delays or customer risk scores) and proactively reroute processes or escalate approvals

When it comes to agentic AI, the primary goal is not replacing talent but augmenting it. This facilitates new routines and processes where tedious tasks are absorbed; accuracy is easily governed, and finance teams are free to focus more on strategic goals and actions.

Why a standalone AI solution isn’t enough

It’s clear why enthusiasm and momentum for agentic AI is accelerating. But there is nuance involved. Simply implementing agentic AI isn’t guaranteed to deliver returns – especially when operating in a vacuum.

Without the right infrastructure, co-ordination and support behind it to improve context, consistency and results, agentic AI becomes just another misapplied, disparate tool.

In fact, Gartner predicts that over 40 per cent of agentic AI projects will be scrapped by 2027 due to “escalating costs, unclear business value, or inadequate risk controls”.

Thus, unlocking agentic AI’s full potential requires organisations to look beyond isolated tools and pursue agentic AI solutions built around a unified digital foundation that enables:

End-to-end automation across finance functions, ensuring agents can act without bottlenecks or manual inputs
Scalable, integrated architecture that allows cross-functional agents to work across systems, data sources and geographies
Clean, accessible data that ensures agents operate with real-time intelligence instead of guesswork

The same way an elite sports team relies on strategy and structure to win – not raw talent alone – successful enterprises need more than fragmented tools. The best results stem from the harmony of aligned objectives and co-ordinated execution.

Platforms that unify automation, data, compliance and integration are key to turning agentic AI into a lever for controlled, repeatable business execution capable of reshaping how enterprises operate, compete and grow.

From efficiency to orchestration: the new CFO mandate

Undoubtably, the role of CFO has significantly shifted in recent years from a narrower focus on budget controls and financial discipline to broader responsibilities such as those of strategic growth partner or value architect.

As agentic AI matures, its benefits pair perfectly with this new financial mandate by extending well beyond efficiency into end-to-end visibility, scalability and true process orchestration.

These are the new hallmarks of leadership, and it’s why agentic AI is arguably a non-negotiable for finance. But success will not be defined by who’s first, but by who can execute with purpose and precision.

Want to see what agentic AI can really do for finance? Explore Esker’s on-demand demo library or download the white paper AI Automation Suite for the Office of the CFO to explore real use cases, proven ROI, and what sets successful adopters apart.