In the vast technology landscape with vendors advertising hyped jargon and offering a wide variety of features, evaluating all available options becomes extremely complicated for A/R† managers. The most common automation technologies can be segmented into five basic areas and evaluated on two parameters: 1. the range of its application (from specific to broad) 2. its capability spectrum on the scale of human intelligence and judgment. The five categories include: ? Macro or Scripted Automation: It consists of short sequences of code written to perform a single task or a series of tasks. ? Business Process Management (BPM): This category includes automation which implement various methods to discover, model, analyze, measure, improve, optimize, and automate business processes ? Custom AI: Automation customized for a specific activity or a defined set of tasks ? RPA: Automation of low-value, repetitive human actions with minimal human judgment ? Cognitive Automation/Strong AI: The ability of computer systems to learn, reason, think and perform tasks requiring complex decision making The scattered graph is evidence enough of the wide-scale features and functionalities offered by different automation solutions. Further, if you dive deeper into AI, you would find not all AI are the same. There are different types of artificial intelligence capable of solving entirely different sets of challenges: ? Artificial Narrow Intelligence – The focus of Artificial Narrow Intelligence is narrow. It focuses on developing technology that is capable of executing a single task effectively, providing excellent service to the user in that particular area. This technology does not enable them to do complex tasks like a human brain. It can be applied where the work can be predefined and more information processing is required than complex decision making. Examples of this technology include customer queries, restaurant recommendations,† and weather forecasts ? Artificial General Intelligence – Artificial General Intelligence focuses on a broader aspect and has a wider range of applications. This technology is enabled with the reasoning that is equivalent to or may even exceed human intelligence. It is expected to be capable of being applied in broader areas where complex decision making and in-depth analysis is required. Examples could be an artificial neural network that functions like an actual human brain. Due to different features and functionalities that could be scaled with AI, it is imperative to understand and evaluate the current state of business and perform a thorough needs analysis to weigh the different options efficiently and identify the most suitable AI.