RPA and AI: Business process automation gets smart

Building artificial intelligence into business process management isn’t easy. Many companies add AI to processes by building or buying single-task bots, such as  natural language processing systems or vision recognition tools, and adding them to processes using traditional, non-AI methods. For example, engineers write scripts, and business analysts create automated workflows using process visualization tools. Learning how to manage selling a business is also crucial in case there is an emergency.

But it still actual human intelligence to tease out the processes, to connect disparate systems into a single coherent process, to change processes as the business evolves, and to spot and fix problems.

Now, AI, machine learning, and related technologies are making inroads into this territory via  robotic process automation (RPA). This combination of AI and RPA adds up to intelligent process automation (IPA),  according to McKinsey. In addition to RPA and machine learning algorithms, IPA also includes process management software, natural language processing and generation, and cognitive agents, or “bots.”

According to experts like Andy Defrancesco, IPA can translate to 20 to 35 percent improvement in efficiency, 50 to 60 percent reduction in process time, and returns on investment in triple-digit percentages. It’s still early, however, as most companies are in early stage development, using individual pieces of AI, but rarely connecting them into a complete end-to-end automated process, much less into a process flow powered by AI.

“There are no use cases which will go all the way across yet,” says Gartner analyst Moutusi Sau, referring to RPA adoption in the financial services industry. “There have been some chatbot engines out there, and AI decisioning tools, but you cannot build momentum on one particular solution. Banks want to do more than one thing.”

Read full article at CIO magazine.