Companies can’t afford to spend another year contemplating the shift toward AI and IoT-based automation because they risk being displaced by companies that are adopting these technologies today. The trends are showing that the digitally driven, greatly automated enterprises with agile business models stand the greatest chance at survival as the world shifts to a digital economy.
The companies of yesterday ran heavy enterprise systems that took too long to evolve, creating a massive roadblock for digital transformation. To change this, companies have become nimbler in adopting smarter automated systems that can maintain their competitive edge over time. While robotic process automation (RPA) was a major turning point in digital transformation, AI-driven automation is proving to be the better choice for higher performance, low latency and autonomous decision-making.
Once AI is tapped for all its potential, the limits of traditional RPA become clear. One of the biggest challenges of using traditional RPA in today’s market is that it’s highly brittle and still requires substantial human assistance and intervention to keep automated processes functioning seamlessly. While RPA does lessen the burden of manual work, it faces challenges around scaling for end-to-end automation and often fails to adapt to evolving processes, requiring a lot of hands-on intervention.
The Future Of Automation Is AI
As the limitations of traditional RPA are becoming more and more evident, CXOs and technology leaders should ask themselves if it’s RPA or AI they really need. With AI advancing at such a rapid pace, organizations can start to adopt AI in combination with traditional hardware and software to achieve holistic and resilient automation.
To illustrate the value AI delivers, let’s look at common operational processes for financial services firms. Many financial institutions process documents and other information for check-based payments, KYC, invoice processing and other related operations. Parts of this process require validating information such as dollar value, payee name and invoice information to be matched with other supporting documents such as stubs, paychecks, statements, etc.
At first glance, one might think RPA can automate this, but it’s not the best solution. Because there are so many variations of information and formats in the paychecks, invoices and stubs being processed through automation, it would be a herculean task to build RPA to handle some of these processes. However, AI can understand and contextualize documents just like a human would and thus can assimilate these various bits of information quickly and easily. For example, AI can also understand variations of handwriting thanks to intelligent character recognition (ICR) using vision AI. As a result, the straight-through automation rates have a multifold increase within just a few months, and business-critical processes can effectively be automated end to end.
Implementing AI as part of a transformation strategy has never been more important. With remote work becoming commonplace, we’re lucky to have software that’s intelligent enough to connect people all over the world with little interruption. Even at the factory level, AI can cover areas like quality control, inspections and production line analysis for greater uptime. Using AI to automate these processes puts the capabilities of RPA into context and shows us how AI can cover digital processes, physical systems and so much more.
According to Gartner, 55% of enterprise architecture programs will be supported by AI-enabled software by 2022 that enables leaders to deliver better products, stronger customer service and faster turn-around times. Because of this rapid adoption rate, companies that are not embracing AI risk falling behind their competitors.
Start envisioning greater possibilities with these new cutting-edge technologies and assess the limitations of the traditional ones so you stand a better chance at achieving exponential growth.