4 min read

By Asheesh Mehra

Isaac Asimov, roboticist and science fiction writer, predicted in his novel I, Robot in 1950 that robots and artificial intelligence were going to be banned from Earth in the year 2030. Instead, we are seeing huge advances in AI and this is likely to continue within the next decade.

The UK’s investment in AI recently reached a record high for 2019, rising from $1.02 billion for the whole of 2018 to $1.06 billion in the first six months of 2019. What’s more, the European Commission’s new president, Ursula von der Leyen recently made calls for a GDPR-style regulation for the use of AI to be put in place, signaling the predicted mass uptake of the technology amongst businesses across different industries.

There are multiple facets of AI, all with varied uses and capabilities, and one area in particular that is attracting a lot of attention is Intelligent Automation. Intelligent Automation (IA) marries artificial intelligence including natural language processing, digital workforce management and machine learning with automation.

This branch of the technology is currently boasting an expected market growth of up to $14.4 billion by the year 2024 up from $8 billion in 2019. IA leveraging the potential of fractal science will be a key branch of AI that can help companies solve the unstructured data challenge. It will essentially enable companies to not only process structured data, but also unstructured data and given that this type of data will make up 80 percent of all business data by the year 2025, more companies will be looking to utilize IA with fractal science for their business processes. AI technology such as deep automation tools including Integrated Automation Platforms (IAP) will soon become the go-to business processing tools.

AntWorks predicts that in the next decade, it will be hard to find an industry not utilizing AI to intelligently automate business processes. With countless use cases for AI across all industries, here are our predictions for 2020 and beyond.

Automated workforces and services

Companies across all industries are in most parts experiencing a never-ending demand for convenience from customers. This has certainly been characterized by the increase in the adoption of chatbots in some sectors. It is clear that consumers are unopposed to the idea, with 40 percent of them not being concerned about whether a robot or a human assists them as long as the experience is positive and their problems are solved. However, automating customer service roles can put jobs at risk or may require a change in skillset for the human workforce. Companies need to integrate upskilling/reskilling programs into their digital transformation strategies to truly realize the value that comes when human and digital workforces come together.

AI to advance surveillance

The safety and security of the public is very high on the agenda for most governments in the world. this is why we will likely be seeing a rise in the adoption of computer vision technology as a form of surveillance within the upcoming decade. A key challenge on the horizon for governing bodies, however, will be the ethical implementation of this technology. In 2019, the CIA’s deputy director of technology development Dawn Meyerricks confirmed the organization had 137 ongoing AI projects, including a computer vision solution that is capable of identifying and tagging objects or individuals in real-time video recordings. These findings would then be flagged to the surveillance team for further analysis.

According to Meyerricks, the CIA is also working on an AI solution that can forecast any significant future events through trends and shifts in data analysis, enabling them to then prepare accordingly. Whilst the latter use cases for AI technology are positively in line with the safekeeping of the public, it is not out of the realm of possibility that it could be used for more sinister activities. This concern naturally reinforces the need for organizations to tackle issues around the safety and responsible use of an otherwise effective and promising new AI capability in security.

AI and ethics: the debate continues

The ethics regarding the use of AI across different industries will be a hot topic throughout the 2020s. AI has the potential to solve some of the world’s greatest challenges as well as enhance the quality of our personal and professional lives. Yet there is a real risk of AI falling into the wrong hands. From being used for political fixing to corporate espionage, there are countless dangerous ways in which perpetrators could use the technology for ulterior motives. Calls for the regulation and standardization of AI have already been made and will continue to surface. This means that the increased investment and desire to expand AI regulations across all industries will likely ensure that there are greater consequences for those out of compliance.

The success of using AI for good depends upon trust, and that trust can only be built over time with the utmost adherence to ethical principles and practices. As we plow ahead into the next decade, the only way we can really see AI and automation take the world of business by storm is if it is smartly regulated. This begins with incentivizing further advancements and innovation to the tech, which means regulating applications rather than the tech itself.

Governments need to provide a framework to ensure the protection against malicious use of AI. This means that we will hopefully see a greater onus and accountability put on major organizations in delivering any form of cutting-edge AI technology, in a way that is both responsible and ethical.

AI in healthcare to grow exponentially

The discovery and trials of drugs is an expensive endeavor. In fact, each new drug development program can cost approximately $2.6 billion to run. Given the increasing resistance of diseases and the rise of superbugs, it is starting to become a race against time for many big pharma companies in bringing new drugs to the market. AI can speed up drug trial processes.

The complexity of the molecular makeup of drugs means that finding data on new combinations for a particular medicine can be difficult as the combinations are numerous. Therefore, a lot work goes into studying research data on genes, molecular structures, and other biological information. Processing this large amount of data can be very difficult and time consuming for a human, which is why intelligent automation platforms are needed to process and analyze this catalog of data at a much faster rate using multi-tenancy bots and deep learning algorithms. Not only will this speed up the drugs time to market, but it will also save pharma companies billions in revenue

Another use case for intelligent automation in the healthcare industry is on the frontline. Currently, half of physicians’ time is spent on electronic health records (EHR) and paperwork. The use of AI to process patient data will not only enable physicians to see more patients per day, but the data insights AI can give will provide faster and more effective patient diagnosis.

AI technology has exceptional potential and is expected to create promising opportunities across all industries in the next decade. Its projected growth means that organizations will need to continue tinkering with their digital transformation strategies in order to accommodate the effective use of AI. More than anything, AI and machine learning will soon determine the fate of many companies as the markets become increasingly more saturated.