How to measure the true impact of artificial intelligence and automation on business operations
- Written by Fabian Calle, managing director for small and medium businesses, SAP Concur Australia and New Zealand
It’s clear to today’s business leaders that artificial intelligence (AI) and automation are transforming the finance landscape in profound ways. These advancements offer enormous potential to fulfil the longstanding goal of working smarter, not harder.
AI and automation can reshape how businesses function by streamlining operations, lifting efficiency and productivity, and adding a new dimension to decision-making. Unfortunately, the path to realising the full benefits of these technologies isn’t always straightforward, and businesses can struggle to measure and maximise the return on investment (ROI) from these powerful tools. As such, it’s clear that the challenge doesn’t lie in deciding to adopt AI and automation; instead, it’s about gauging and maximising their ROI post-implementation. This arises because the benefits are often multifaceted and evolve over time, making traditional ROI calculations inadequate.
Companies need to approach these technologies strategically to unlock the full benefits. Businesses of all sizes must consider the broader implications of these technologies, such as their role in futureproofing operations and creating a competitive edge. A critical part of this strategy involves understanding how AI and automation integrate with existing processes, enhance decision-making, and streamline operations, without increasing costs exponentially.
Financial managers will find themselves in the hot seat as company leaders look to them for rapid and accurate appraisals of the value of AI investments. Measuring the ROI of AI projects is a daunting task, as their unique characteristics, the evolving nature of applications, and the difficulty in predicting when benefits will appear, all complicate traditional calculations.
One of the major obstacles in quantifying the ROI of AI and automation is that these technologies don’t deliver benefits in a linear or immediate manner. AI’s predictive capabilities, for example, grow more sophisticated over time, as it gathers and processes more data. This means that businesses need to commit to long-term investment before they start seeing the significant efficiency gains and cost reductions that AI promises.
However, this raises an important question for companies: how can they ensure their AI investments are delivering value when the return might not be immediately apparent? The solution is to establish clear objectives at the outset. Businesses that start AI projects with a defined set of goals, such as reducing manual processing times or improving forecast accuracy, will be better placed to track their progress and adjust as necessary. Clear objectives also make it easier to measure the success of AI projects over time.
The challenge becomes even greater when company leaders try to assess the indirect benefits of AI, such as improved decision-making or enhanced customer experience. While these outcomes are invaluable, they’re difficult to quantify in monetary terms. Businesses must develop approaches to ROI that account for both short-term efficiency gains and long-term potential for growth and innovation.
This highlights another crucial aspect to maximising the ROI of AI and automation: data management. AI systems are only as good as the data they process, so if the data is inaccurate or incomplete, the insights generated will be flawed and lead to poor decision-making. Companies must invest in robust data management practices to facilitate data accuracy and develop the ability to process and analyse data quickly and efficiently.
It’s critical to recognise that AI and automation are not one-size-fits-all solutions, and what works for one business may not work for another regarding AI implementation, particularly when considering the differences in industry requirements and company size. Smaller businesses, for instance, may need to take a phased approach, starting with small, manageable AI projects that deliver quick wins before scaling up their efforts. This approach lets the company build momentum and fine-tune their AI strategies before committing to larger investments.
Even with the best strategies in place, AI implementation can come with its own set of challenges, and change management is one of the most significant hurdles. Employees who are accustomed to traditional ways of working might be resistant to new technologies, particularly if they fear that automation could make their roles redundant. Business leaders should communicate the benefits of AI for the company as a whole and for individual employees to overcome this. This will show staff that AI and automation are tools designed to enhance rather than replace their roles so they can focus on more strategic, value-added tasks rather than mundane, repetitive work.
Building a culture of continuous learning is essential in this context. AI and automation technologies evolve rapidly, and businesses need to ensure their employees have the skills and knowledge required to work alongside these new tools. This means investing in training and development programs that teach employees how to use AI systems and help them understand the strategic value these technologies bring to the company.
AI and automation are powerful tools that can streamline and improve the way businesses operate, though their full potential will only be realised if companies approach their implementation strategically. This means going beyond traditional ROI calculations and considering the broader implications of these technologies. Businesses can unlock the true value of AI and automation and position them for long-term success by focusing on clear objectives, investing in data management, and fostering a culture of learning and innovation.
