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Business process automation (BPA), also known as business automation, refers to the technology-enabled automation of business processes. [1]
BPA tool sets vary in capability, but there is a trend towards the use of artificial intelligence technologies that can understand natural language and unstructured data sets, interact with human beings, and adapt to new types of problems without human-guided training. [2] [ self-published source ]
A business process management system differs from BPA. However, it is possible to implement automation based on a BPM implementation. The methods to achieve this vary, from writing custom application code to using specialist BPA tools. [3] [ self-published source ]
Robotic process automation (RPA) involves the deployment of attended or unattended software agents in an organization's environment. These software agents, or robots, are programmed to perform pre-defined structured and repetitive sets of business tasks or processes. The goal is to allow humans to focus on more productive tasks, while the software agents handle the repetitive ones. [4] [ self-published source ]
BPA providers typically focus on different industry sectors, but the underlying approach is generally similar in that they aim to provide the shortest route to automation by interacting with the user interface rather than modifying the application code or database behind it. [5]
Artificial intelligence software robots are used to handle unstructured data sets (like images, texts, audios) and are often deployed after implementing robotic process automation. They can, for instance, generate an automatic transcript from a video. The combination of automation and artificial intelligence (AI) enables autonomy for the robots, along with the capability to perform cognitive tasks. [6] [ self-published source ] At this stage, the robot can learn and improve processes by analyzing and adapting them. [7]
Automation describes a wide range of technologies that reduce human intervention in processes, mainly by predetermining decision criteria, subprocess relationships, and related actions, as well as embodying those predeterminations in machines. Automation has been achieved by various means including mechanical, hydraulic, pneumatic, electrical, electronic devices, and computers, usually in combination. Complicated systems, such as modern factories, airplanes, and ships typically use combinations of all of these techniques. The benefit of automation includes labor savings, reducing waste, savings in electricity costs, savings in material costs, and improvements to quality, accuracy, and precision.
In computer science, a software agent is a computer program that acts for a user or another program in a relationship of agency.
An AI takeover is an imagined scenario in which artificial intelligence (AI) emerges as the dominant form of intelligence on Earth and computer programs or robots effectively take control of the planet away from the human species, which relies on human intelligence. Possible scenarios include replacement of the entire human workforce due to automation, takeover by a superintelligent AI (ASI), and the notion of a robot uprising. Stories of AI takeovers have been popular throughout science fiction, but recent advancements have made the threat more real. Some public figures, such as Stephen Hawking and Elon Musk, have advocated research into precautionary measures to ensure future superintelligent machines remain under human control.
The ethics of artificial intelligence covers a broad range of topics within the field that are considered to have particular ethical stakes. This includes algorithmic biases, fairness, automated decision-making, accountability, privacy, and regulation. It also covers various emerging or potential future challenges such as machine ethics, lethal autonomous weapon systems, arms race dynamics, AI safety and alignment, technological unemployment, AI-enabled misinformation, how to treat certain AI systems if they have a moral status, artificial superintelligence and existential risks.
[24]7.ai is a customer service software and services company based in California that uses artificial intelligence and machine learning to provide targeted customer service.
"Fourth Industrial Revolution", "4IR", or "Industry 4.0" is a neologism describing rapid technological advancement in the 21st century. It follows the Third Industrial Revolution. The term was popularised in 2016 by Klaus Schwab, the World Economic Forum founder and executive chairman, who asserts that these developments represent a significant shift in industrial capitalism.
Cloud robotics is a field of robotics that attempts to invoke cloud technologies such as cloud computing, cloud storage, and other Internet technologies centered on the benefits of converged infrastructure and shared services for robotics. When connected to the cloud, robots can benefit from the powerful computation, storage, and communication resources of modern data center in the cloud, which can process and share information from various robots or agent. Humans can also delegate tasks to robots remotely through networks. Cloud computing technologies enable robot systems to be endowed with powerful capability whilst reducing costs through cloud technologies. Thus, it is possible to build lightweight, low-cost, smarter robots with an intelligent "brain" in the cloud. The "brain" consists of data center, knowledge base, task planners, deep learning, information processing, environment models, communication support, etc.
Dynatrace, Inc. is a global technology company that provides a software observability platform based on artificial intelligence (AI) and automation. Dynatrace technologies are used to monitor, analyze, and optimize application performance, software development and security practices, IT infrastructure, and user experience for businesses and government agencies throughout the world.
Robotic process automation (RPA) is a form of business process automation that is based on software robots (bots) or artificial intelligence (AI) agents. RPA should not be confused with artificial intelligence as it is based on automotive technology following a predefined workflow. It is sometimes referred to as software robotics.
Appian Corporation is an American cloud computing and enterprise software company headquartered in McLean, Virginia, part of the Dulles Technology Corridor. The company sells a platform as a service (PaaS) for building enterprise software applications. It is focused on low-code development, process mining, business process management, and case management markets in North America, Europe, the Middle East and Southeast Asia.
Lawbots are a broad class of customer-facing legal AI applications that are used to automate specific legal tasks, such as document automation and legal research. The terms robot lawyer and lawyer bot are used as synonyms to lawbot. A robot lawyer or a robo-lawyer refers to a legal AI application that can perform tasks that are typically done by paralegals or young associates at law firms. However, there is some debate on the correctness of the term. Some commentators say that legal AI is technically speaking neither a lawyer nor a robot and should not be referred to as such. Other commentators believe that the term can be misleading and note that the robot lawyer of the future won't be one all-encompassing application but a collection of specialized bots for various tasks.
UiPath Inc. is a global software company that makes robotic process automation (RPA) software. It was founded in Bucharest, Romania, by Daniel Dines and Marius Tîrcă. Its headquarters are in New York City. The company's software monitors user activity to automate repetitive front and back office tasks, including those performed using other business software such as customer relationship management or enterprise resource planning (ERP) software.
Exela Technologies, Inc. is an American business process automation ("BPA") company. It was created with the merger of SourceHOV LCC, Novitex Holdings, Inc. and Quinpario Acquisition Corp. 2.
Artificial intelligence (AI) has a range of uses in government. It can be used to further public policy objectives, as well as assist the public to interact with the government. According to the Harvard Business Review, "Applications of artificial intelligence to the public sector are broad and growing, with early experiments taking place around the world." Hila Mehr from the Ash Center for Democratic Governance and Innovation at Harvard University notes that AI in government is not new, with postal services using machine methods in the late 1990s to recognise handwriting on envelopes to automatically route letters. The use of AI in government comes with significant benefits, including efficiencies resulting in cost savings, and reducing the opportunities for corruption. However, it also carries risks.
The Artificial Intelligence of Things (AIoT) is the combination of artificial intelligence (AI) technologies with the Internet of things (IoT) infrastructure to achieve more efficient IoT operations, improve human-machine interactions and enhance data management and analytics.
ModelOps, as defined by Gartner, "is focused primarily on the governance and lifecycle management of a wide range of operationalized artificial intelligence (AI) and decision models, including machine learning, knowledge graphs, rules, optimization, linguistic and agent-based models" in Multi-Agent Systems. "ModelOps lies at the heart of any enterprise AI strategy". It orchestrates the model lifecycles of all models in production across the entire enterprise, from putting a model into production, then evaluating and updating the resulting application according to a set of governance rules, including both technical and business key performance indicators (KPI's). It grants business domain experts the capability to evaluate AI models in production, independent of data scientists.
The impact of artificial intelligence on workers includes both applications to improve worker safety and health, and potential hazards that must be controlled.
Artificial intelligence (AI) in hiring involves the use of technology to automate aspects of the hiring process. Advances in artificial intelligence, such as the advent of machine learning and the growth of big data, enable AI to be utilized to recruit, screen, and predict the success of applicants. Proponents of artificial intelligence in hiring claim it reduces bias, assists with finding qualified candidates, and frees up human resource workers' time for other tasks, while opponents worry that AI perpetuates inequalities in the workplace and will eliminate jobs. Despite the potential benefits, the ethical implications of AI in hiring remain a subject of debate, with concerns about algorithmic transparency, accountability, and the need for ongoing oversight to ensure fair and unbiased decision-making throughout the recruitment process.
Intelligent automation (IA), or alternately intelligent process automation, is a software term that refers to a combination of artificial intelligence (AI) and robotic process automation (RPA). Companies use intelligent automation to cut costs and streamline tasks by using artificial-intelligence-powered robotic software to mitigate repetitive tasks. As it accumulates data, the system learns in an effort to improve its efficiency. Intelligent automation applications consist of but are not limited to, pattern analysis, data assembly, and classification. The term is similar to hyperautomation, a concept identified by research group Gartner as being one of the top technology trends of 2020.
