The content of this article is inspired by the Amazon bestseller book “Intelligent Automation.”
Intelligent Automation technologies have great potential to reduce financial losses across all businesses, from multinational corporations to small family businesses and sole traders.
I have identified three categories of financial losses that IA could help prevent: fraud, error, and work-related accidents and illnesses. I estimate that $10 trillion could be saved overall, which is half the GDP of the US.
These savings could be used for valuable purposes such as health and education. The potential impact is enormous: $10 trillion is roughly the total amount spent on health and education worldwide.
Fraud
Increasing amounts of money are being lost due to fraud. The total cost per year is over $5 trillion worldwide, or 6% of global GDP, and has more than doubled in the last decade, according to research from Crowe and the University of Portsmouth’s Centre for Counter Fraud Studies (CCFS). The researchers suggest three reasons for the recent rapid increase in fraud: the erosion of collective ethical norms due to individualism, the increasing complexity and vulnerability of systems and processes, and the lag between technological innovation and regulation.
IA can help by automatically logging every action, increasing transparency and facilitating compliance. At a more advanced level, machine learning can spot patterns in the data generated by this logging and use it to make predictions and raise alerts about potential fraud scenarios.
Error
Medical errors, as well as causing unnecessary death and injury, also incur economic costs of almost $1 trillion per year in the US alone. This is not counting mistakes purely in billing, which add up to another $68 billion of wasted US healthcare spending per year. The equivalent figures for the whole world are estimated to be two or three times higher.
This is in the medical profession alone, so consider the magnitude of the figure extrapolated across all industries.
IA tools cannot become tired or distracted. They can be used to provide an extra error-checking step in transactions and calculations without incurring additional ongoing costs in time or labour. They can also be used to flag transactions that appear anomalous according to complex criteria, alerting a human expert who can check whether the anomaly is an error or a valid exception.
Accidents at work and work-related illnesses
Accidents at work and work-related stress illnesses cost the global economy $3 trillion per year, according to the International Labour Organization (ILO).
IA can play a vital role in reducing this figure. Robots can prevent accidents by taking on the more physically dangerous tasks. Robotic process automation and zero-code platforms can reduce stress by automating the more repetitive and boring tasks, freeing up humans for more creative, engaging, and fulfilling work.
In cases where IA cannot yet take on dangerous tasks itself and avoid the need for humans to do them, it can still help reduce accidents at work by automatically checking compliance with safety regulations and reminding users of precautions they may have overlooked. As for stress-related illnesses, a wide range of IA tools exist for monitoring employees’ stress levels and mental health. Sentiment analysis can be applied to large datasets of emails, instant messages and phone calls. Biometric data such as heart rate can be collected from smartwatches. Computer vision can monitor users’ facial expressions in real-time. Machine learning can analyse all this data to look for patterns that indicate or predict stress and help managers to address them.
Conclusion
Overall, I estimate that IA has the potential to prevent $10 trillion of losses per year due to fraud, error, accidents at work, and work-related illnesses. Even if I can only realize half of this potential over the next ten years, that’s still $5 trillion of savings. These could be redeployed, using regulation or taxation, to areas where they will have the greatest impact.
As an example of the scale of the potential effects, this $5 trillion that could be saved by realizing just half of the potential of IA would be enough to end hunger and malnutrition worldwide. Alternatively, it could more than double global investment in education, or increase global healthcare budgets by more than 70%, or increase environmental investment by a factor of twenty. This is a vast untapped resource with the potential to improve the world almost beyond recognition.
