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Data has been a crucial component to the evolution of artificial intelligence (AI), a market that could reach $98 billion by 2023 and exceed $169 billion by 2025. Most (64%) of financial services executives expect AI to transform the industry within two years. Better still, the technology could generate $140 billion in productivity gains and cost savings. When applied to all industries, AI is expected to create $2.9 trillion in business value in 2021 alone.
That growth is now being fueled by the coronavirus pandemic, with 88% of organizations having already added or scaled up AI technologies since its onset. AI is now being combined with new approaches to automation, dubbed intelligent automation or hyperautomation. By utilizing these technologies, businesses can now do much more with less. But do they have the data to accomplish their end goals?
COVID-19 proved that businesses will continue to operate in the dark if they lack the necessary data to predict possible outcomes. The pandemic was uncharted territory for most of the world, but the data collected can now be used to build algorithms for future events, which will be essential to predicting and overcoming future challenges.
For many businesses, that may not be enough. The reality is that most firms are focused on day-to-day objectives and do not have the time to worry about things that are ultimately out of their control. They need real-world solutions to their problems, and while AI and automation can be that solution, the technology requires a tremendous amount of support from specialists within the field, as well as engineers and data scientists. This can bog down the efforts of firms that may not have the resources to achieve optimum results. But there is a way around this, and it starts by using AI that was built for these very situations.
No Programming Necessary = No Barrier to Entry
There is significant demand for people who can build and amplify what AI can do and accomplish for a business. This issue could be further magnified if a talent shortage were to occur, raising salaries and a war for top-tier experts among organizations with the deepest pockets. Instead of trying to compete, the majority of businesses can benefit right now by relying on no-code AI platforms, which allow business professionals to utilize the technology without a team of AI specialists.
Designed to be the first true mainstream implementation of the technology, no-code AI can be carried out by business analysts and process experts. As a result, this tech is poised to bring genuine intelligence to an endless number of organizations.
Good AI relies on good data to accurately create models that serve those on the receiving end, but the combination of smarter AI models – which require less data – allows all enterprises to utilize the technology. This empowers smaller firms to compete with the world’s largest dot-com giants, which have had access to huge amounts of data that gave them an early edge, resulting in significant profit gains.
Hyperautomation Is RPA in Overdrive
Enterprises are also benefiting from the meteoric rise in AI by adopting intelligent automation as part of an integrated solution. The days of relying on generic robotic process automations (RPAs) are over – enterprises need AI-driven automation solutions to solve their day-to-day challenges. RPA bots weren’t effective at solving more complex, end-to-end back-office tasks, especially ones with unstructured data input or with real-time automation requirements.
This is where a more advanced form of automation discipline – known as hyperautomation – comes into play. Hyperautomation successfully and reliably reacts to things in real time and utilizes AI to deal with unstructured information, enabling the number of possible automation use cases to increase exponentially. It is the No. 1 approach for attaining end-to-end automation of anything that can be automated – a significant differentiator when comparing what was possible with RPAs.
Hyperautomation orchestrates automation through multiple methods including application programming interfaces (APIs), command-line interfaces, databases and, naturally, RPA as well. Better still, hyperautomation incorporates AI to identify and analyze the best way to perform automation when inputs are unstructured. Instead of merely automating simple tasks based on spreadsheets data, hyperautomation can carry out tasks based on real-time conversations with employees and customers. It can also dissect voicemails using natural language understanding to determine what was requested and follow through with the right action all on its own, allowing human employees to continue focusing on higher-value work.
The Future of Business
AI is going to disrupt most industries, but the need to hire specific talent and a lack of clear direction from business executives have prevented the technology from living up to its promise. No-code AI can resolve this talent gap, allowing enterprises to take full advantage of the technology without the same level of commitment – in time or resources – that was once required. The emergence of the hyperautomation mindset is another important development that allows businesses to stay ahead of the curve and persevere through challenging times, using both past and present data to propel forward. This makes it especially useful in the current climate.