While AI may seem futuristic or daunting, it's set to revolutionise the way we work, much like the introduction of computers, the internet, and smartphones did in previous decades.
To truly understand how AI works and what makes it so powerful, imagine a scenario where you accompany a six-year-old to school. Just as this child learns from their surroundings, AI learns from data, adapting and improving its processes over time.
Since the rise of computers, the way we work has largely been dictated by the programs designed for specific tasks—be it spreadsheets, financial systems, or invoice processing. Tools like Robotic Process Automation (RPA) can automate repetitive tasks, but they are often limited by their rigid programming. A minor change, such as a different invoice format, can cause an RPA system to fail, requiring manual intervention.
In the analogy, an RPA-based robot would need to follow a predefined route to take the six-year-old to school. Any unexpected detour, like roadworks, could confuse the robot, stopping it in its tracks. Similarly, in finance, a small change in data can disrupt RPA, leading to inefficiencies.
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This is where AI distinguishes itself from RPA. Instead of following a rigid set of instructions, AI learns from historical data and adapts to new situations, making it far more flexible and resilient. Imagine the same robot guiding the child to school using AI: it wouldn’t need explicit instructions for every step. Instead, after a few trips, it would learn the best routes, adapt to changes, and ensure the child arrives safely.
In finance, AI can handle complex tasks such as 3-way matching of purchase orders, invoices, and receipts, even when conditions or formats change. This adaptability is something an RPA system cannot achieve without extensive reprogramming.
The adaptability of AI is especially valuable in a finance department that deals with a wide array of invoices from various suppliers. These invoices can differ in VAT rates, payment terms, and other factors. While RPA might struggle with such variability, AI continuously learns and improves, extracting line item data with increasing accuracy, even as formats evolve.
This makes AI a far more powerful tool for automating finance processes. An AI-driven system can quickly identify patterns and correlations, improving data extraction accuracy and reducing errors. This allows finance teams to focus on more strategic tasks rather than getting bogged down in manual data entry and error correction.
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If you’re serious about using technology to optimize your finance department’s workflow, it’s crucial to choose a solution that is both flexible and capable of evolving with your organization. AI-based systems provide the adaptability needed to handle not only the simplest tasks but also more complex financial processes as your company grows.
By adopting AI, finance departments can not only improve current processes but also prepare for future challenges, ensuring efficiency and maintaining a competitive edge in an increasingly digital world.