Robotic Process Automation (RPA) is one of the most popular technologies for automating business processes. This technology enables fast and, above all, efficient automation of standardized processes. However, the range of uses is limited by the need for structured data and programmable decision-making. However, this shortcoming can be overcome through the use of artificial intelligence. In the following, we will show you RPA and AI, and how artificial intelligence can help RPA bots become smarter.

CIOs are implementing both automation and AI at a quickening pace, prodded into expanding and expediating deployments for the speed and cost-saving efficiencies they each deliver. Recently released figures quantify the accelerating rate of adoption. More than 72% of global enterprises already started AI implementations, according to a January report from Everest Group. The firm expects that global spending on AI services will accelerate by 32%, from $25 billion in 2019 to $95 billion by 2024. The global robotic process automation (RPA) software market hit $1.2 billion at the end of 2019, posting year-on-year growth of more than 75%.

Robotic process automation (RPA) and artificial intelligence (AI) have traditionally been viewed as separate and somewhat unequal worlds--RPA proponents consider AI to be impractical, while AI enthusiasts deem RPA primitive--but these two fields are highly complementary. Think of them as the brawn and the brains of performance. Companies can gain quick wins through RPA while strategically introducing AI for sustainable benefits and continual optimization. Services are especially amenable to this approach. By services, we mean both service industries, such as banking, insurance, and telecommunications, as well as services provided by in-house support functions, such as finance, HR, and IT.

AI and robotic process automation are taking over more and more tasks from ERP users. RPA mimics human behavior, recording users as they enter data, execute commands and move documents across applications. The machine-learning AI in ERP scans information for patterns, "learns" what to expect, makes decisions and even tries to predict the future. Both technologies are enabling a new kind of ERP that is more automated, responsive and easier to use than its often frustratingly obstinate ancestors. But just how intelligent, really, is the AI in ERP? Where does robotic process automation (RPA) belong?

For the past few years, headlines have abounded about how robots are going to take over -- specifically people's jobs. It's true robots have been taking on more mundane tasks, but there's more to the story. A recent McKinsey report found that more companies were pursuing automation in 2020. However, many of the organizations surveyed said they were automating with an eye toward their personnel, complementing existing talent to allow for growth. For modern finance teams interested in automating tasks, below is a look at two types of automation technology.

Aggressive marketing language can often drive a lack of clarity around technical concepts. Somewhat surprising, is that confusion between RPA and AI is high even among organizations that have automation in place and have likely gone through the diligence and/or request for proposal (RFP) process to select their automation solution. More than 50 percent of CFOs and revenue cycle leaders in organizations that are actively using automation say they consider RPA to be a form of artificial intelligence. "RPA based bots can be good tools for automating simple, discrete, and static tasks," said Varun Ganapathi, co-founder and Chief Technology Officer at Alpha Health. "AI and machine learning based technologies are capable of automating much more complex tasks that require some degree of judgment or subject matter expertise. Additionally, AI and machine learning based solutions can have the ability to navigate changes or new variables without the need to reprogram or recode a bot every time something changes."

Many people often asked about the difference between Robotic Process Automation (RPA) and Artificial Intelligence (AI). Some even confused the two to be the same. To make matters worse, many vendors are now brandying about terms like Intelligent Automation (IA) or Intelligence Process Automation (IPA). For the uninitiated, all these jargon can be very confusing, and perhaps daunting. To help you out, we have put together this blog post to highlight the key differences between RPA and AI, particularly in the context of process automation.

Robotic Process Automation (RPA) and Artificial Intelligence (AI) are not mere buzzwords. Companies across the world have been using these technologies to automate tasks, improve productivity, and allow the human workforce to focus on human-centric tasks. For a very long time, companies have been divided in their opinion of choosing between RPA and AI or using them in combination. In this blog, we explore this in detail. Before we delve into it, let's first understand these two technologies. RPA is a software programmed to help the human workforce to complete basic, repetitive tasks.

Government is ushering in a new era of work, using automation and artificial intelligence to help the federal workforce achieve higher levels of productivity and decision-making. Over the past two years, agencies have focused on shifting the workforce to "high-value" work -- a key goal of the President's Management Agenda -- by taking advantage of robotic process automation and other technologies to reduce error, improve compliance and eliminate repetitive administrative tasks. Although RPA is a useful IT capability that allows agencies to eliminate low-value, mundane, transactional work, it can only make simple decisions. By adding AI to the equation, agencies can accelerate the ability of RPA to complete a multitude of tasks at once. This can be particularly helpful when analyzing large swaths of data, enabling decision-makers to meet goals more efficiently and effectively.

As consumers and businesses continue to seek personalized banking experiences, the financial services industry is responding with technological tools that can help fulfill those interests. An uptick in the use of artificial intelligence (AI) and robotic process automation (RPA) has provided financial services firms with integrated solutions that allow them to offer more precise financial forecasts and personalized services for everyone in the process. What they are: RPA is a software category that allows financial services firms to automate functions that previously required significant human interaction but not a tremendous amount of thought. For instance, RPA software can automatically reconcile account balances, significantly reducing the time to perform this task. On the other hand, AI uses data to actually "think" similarly to how a human would, allowing it to anticipate patterns, make forecasts and respond intelligently to inputs.