Finance Automation Playbook: Fix Issues with People and Process before applying Technology

In the rush to embrace AI and automation, many in the accounting and business services world assume that technology is the answer to every inefficiency. Automate reconciliations, let AI handle audits, deploy chatbots for client queries—problem solved, right?

Not quite.

While automation is beginning to transform how accountants work, it doesn't replace the need for human expertise, strategic thinking, and well-designed processes. In fact, over-reliance on technology can create blind spots, introduce risk if applied incorrectly, and even lead to missed opportunities.

The real challenge isn’t just about what you automate—it’s about how and where you integrate technology without losing the human judgment that’s required to provide value to your stakeholders.

Gartner research supports this approach, emphasising that organisations should optimise processes and prepare their teams before introducing new technologies. According to their findings, companies that prioritise process improvements before automation experience 30% fewer implementation failures and achieve higher ROI from technology investments (Gartner, 2024).

Similarly, Forrester Research highlights that businesses that implement structured change management and process reengineering before deploying new technology see 40% higher adoption rates and greater long-term efficiency (Forrester, 2024).

These insights reinforce that technology alone is not the solution—it must be paired with strong processes and well-prepared teams.

1. The Limits of Automation in Accounting

Automation excels at handling repetitive, rule-based tasks. It speeds up workflows, reduces errors, and enables teams to focus on higher-value activities. But there are critical areas where automation falls short:

1.1 Complex Problem-Solving

AI can analyse vast amounts of financial data, but it struggles with nuance and judgment. For instance:

• A machine learning algorithm can flag an unusual transaction, but humans are still best positioned to determine if it’s fraud, an error, or a legitimate business expense.

• AI can generate financial forecasts, but it can’t account for real-world uncertainties—like an upcoming merger, a regulatory change, or shifting client relationships.

1.2 The Context Problem

Automation relies on data patterns, but context matters:

• A client switching suppliers may look like a random anomaly to AI, but an accountant with industry knowledge knows it’s due to changing raw material costs.

• AI might recommend cost-cutting measures based on historical trends, but a finance leader understands the cultural and operational impact of those decisions.

1.3 Compliance & Ethics Risks

Regulatory compliance is not just about applying rules; it’s about interpreting intent:

• Automated compliance tools can scan financial records, but they can’t navigate gray areas where professional judgment is required.

• AI-driven tax optimisation might suggest an aggressive strategy, but only a human advisor can assess legal and ethical risks.

2. Where the Real Opportunity Lies: People & Process

Instead of assuming technology alone is the answer, firms should focus on enhancing people and process first.

2.1 Strengthening Processes Before Automating

Automation works best when applied to well-designed, efficient processes. Too often, companies automate broken workflows, leading to:

• Faster errors instead of fewer errors.

• More inefficiencies instead of improved productivity.

• Greater compliance risks instead of better control.

Before automating, firms should: Map out existing processes and eliminate bottlenecks. Redesign workflows to balance efficiency with control. Standardise data inputs to avoid garbage-in, garbage-out automation.

2.2 Empowering Accountants with Technology—Not Replacing Them

Instead of framing AI as a replacement, firms should position it as an enhancement or tool:

• AI as an assistant: Let technology handle repetitive calculations while accountants focus on advisory and strategic insights.

• Automation as a guide: Use AI to flag anomalies, but keep humans in the loop to make final decisions.

• Data-driven decision-making: Train teams to use AI insights, but ensure they bring business context to every decision.

2.3 Upskilling Talent for the AI Era

Rather than automating entire roles, firms should reskill and upskill their teams to work alongside AI:

• Train accountants in data analytics and AI-driven insights.

• Shift finance teams from transactional work to strategic advisory roles.

• Focus on relationship-building skills that automation can’t replicate.

3. The Right Balance: Where to Draw the Line

To get the best of both worlds, businesses should follow a strategic automation framework:

Automate:

• High-volume, repetitive tasks (data entry, invoice matching, reconciliations).

• Standardised compliance checks and report generation.

• AI-driven alerts for anomalies, fraud detection, and forecasting.

Don’t Automate (Fully):

• Client advisory and strategic financial decision-making.

• Compliance and risk assessment in complex scenarios.

• Ethical decision-making and business-critical interpretations.

Augment (Hybrid Approach):

• AI-powered tools that assist humans rather than replace them.

• Data analysis that highlights risks—but leaves decisions to professionals.

• Workflow automation with human oversight for quality control.

Technology is a Solution, but it's Not the Only Solution

The best accounting firms and finance teams won’t be the ones that automate the fastest. They’ll be the ones that use technology wisely—without losing sight of human expertise and strong processes.

At Kinore, we believe the competitive advantage lies in harmonising people, process, and technology—not replacing one with another.

So, the next time you’re considering automation, ask yourself:

• Are we solving a real problem—or just adding technology for the sake of it?

• Do we understand the human expertise that needs to remain in the process?

• Are we setting up our team for success—or just making their jobs harder?

If the answer isn’t clear, it’s time to rethink your application of People, Process, and Technology (PPT).

Gartner, 2024. "Digital Transformation Strategies: The Role of Process Optimization Before Automation." Available at: Gartner

Forrester, 2024. "Digital Strategy and Change Management: How Businesses Can Achieve Higher Adoption Rates." Available at: Forrester