AI: Like a Swiss army knife – capable of cutting through problems or creating them

AI is the buzzword promising to solve all our problems, optimise our operations, and even make our coffee in the morning.

However, it’s more like a Swiss army knife—versatile, powerful, and incredibly useful, but wield it recklessly at your peril.

The truth is, if your goal is efficiency and real transformation, don’t start with AI.

The Quick fix myth

It would be ideal if AI could just wave a magic wand and fix everything? Unfortunately, that’s not how it works. AI’s true potential isn’t unlocked by simply sprinkling it on your problems like some kind of tech fairy dust. No, the real magic happens when you reimagine and redesign entire processes—or even entire functions—with AI as a key player. It’s about taking a step back, figuring out where AI can add value, and avoiding the temptation to just layer it on top of existing inefficiencies.

Adding AI on messy processes won’t help

It isn’t a band-aid for broken processes. To truly harness its power, you need to re-engineer your workflows to be more efficient and AI-compatible.

So, what exactly is AI?

The term gets thrown around a lot, but it actually covers a whole spectrum of technologies. On one end, you’ve got basic automation tools like macros through to Robotic Process Automation (RPA), which is like macros on steroids, capable of interacting with multiple systems to streamline more complex processes.

Then we enter the realm of machine learning and deep learning, where AI starts to learn from data, make predictions, and even help you make decisions. And there’s Artificial General Intelligence (AGI) and Artificial Superintelligence (ASI) — which are more sci-fi than reality.

Reimagining a domain with AI

I’ll use the finance function, one of my favourite domains, as an example. AI has the potential to do wonders here, but only if you lay the groundwork properly. Think of your finance processes as the garden, and AI as the fancy new sprinkler system you’re thinking of installing.

If the soil is rocky and the plants are wilting, no amount of high-tech watering is going to turn things around. You need to prep the soil first—get those processes in tip-top shape before you even think about adding AI to the mix.

Start by reviewing your current workflows and handoffs, identifying where things get stuck, and standardising practices across the board. This might mean streamlining steps, integrating data sources, or even tearing down and rebuilding entire processes. It’s work, but it’s worth it.

Take your close cycle for example, or perhaps how you update the GL with claims and policy data from underlying systems - are they already optimised?

Without this groundwork, even the most advanced AI tools will struggle to deliver the results you’re hoping for. It’s like trying to build a house on quicksand—things are bound to go awry.

The road to AI nirvana in finance is a journey, not a sprint. Here are some key steps in the journey:

Basic automation (basic bookkeeping related)

Start with the low-hanging fruit—automating repetitive, rule-based tasks like data entry, invoice processing, or simple reconciliations. RPA is the most straightforward AI application here, designed to mimic human actions in interacting with digital systems. RPA doesn’t require deep learning or complex algorithms, making it ideal for quick wins in efficiency. This is the easy win, but don’t stop here.

Enhanced data processing (number crunching)

Level up by moving beyond basic bookkeeping to more sophisticated data analysis and number crunching. Think predicting cash flow, spotting anomalies or identifying trends. Machine learning algorithms can process and analyse large volumes of financial data to identify patterns, predict outcomes, and flag anomalies. This level of AI allows for more sophisticated data insights that go beyond simple automation.

Advanced decision support (strategic decision making)

Here, AI begins to help with more complex nuanced tasks like financial planning and risk assessment. Cognitive computing systems use advanced ML to support decision-making processes. They can process unstructured data, learn from historical decisions, and provide actionable insights for financial planning and risk management. These systems go beyond number-crunching to help inform strategic decisions and drive business value with a higher degree of intelligence.

End-to-end process optimisation (AI as a consultant)

This is where AI starts to flex its muscles, optimising entire workflows and helping you re-engineer your processes from the ground up. AI-driven process mining tools analyse your entire workflow to identify inefficiencies, bottlenecks, and opportunities for optimisation. These tools can suggest process re-engineering opportunities, helping streamline operations across the finance function. Optimisation algorithms can then be applied to fine-tune processes, ensuring they operate at peak efficiency. Goodbye inefficiencies, hello streamlined operations. You can’t get here without the right building blocks.

Strategic transformation

At the pinnacle, AI isn’t just a tool—it’s a game-changer. It automates complex decisions and influences business strategy in real-time, turning your finance function into a proactive driver of growth. At this level, AI becomes a strategic partner in driving transformation. AI-driven decision automation systems can make real-time adjustments to business strategies, like dynamically managing investment portfolios or optimising pricing models based on market data. Predictive analytics further enhances this by providing foresight into future trends, allowing for proactive rather than reactive decision-making.

The bigger picture: AI as a catalyst, not a crutch

At the end of the day, the successful use of AI in finance—or any other part of your business—requires a holistic approach. It’s not just about the technology; it’s about the people, the processes, and the overall strategy. AI is a powerful tool, but it works best when it’s part of a broader effort to rethink and optimise the way your organisation operates.

As you integrate AI, you’ve got to ensure it’s done ethically and in compliance with regulations. Think of it as building the guardrails before you let your AI system loose on the track. Control frameworks, transparency, and accountability aren’t optional—they’re essential.

So, as you consider how AI can help your business, don’t just look for quick wins. Instead, seize the opportunity to reimagine your processes and functions, ensuring they are as efficient and effective as possible. That’s where the real power of AI lies—not as a silver bullet, but as a Swiss army knife in your toolkit for transformation.

For more information, contact Buki Obayiuwana, or your usual Crowe contact.