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.
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.”
“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.”