in the enterprise will change how work is done, but companies must overcome several challenges to derive value from this powerful and rapidly evolving technology.
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The application of in the enterprise will profoundly change the way businesses work. Companies are beginning to incorporate into their business operations with the aim of saving money, boosting efficiency, generating insights and creating new markets.
There are -powered applications to enhance customer service, maximize sales, sharpen cybersecurity, optimize supply chains, free up workers from mundane tasks, improve existing products and point the way to new products. It is hard to think of an area in the enterprise where — the simulation of human processes by machines, especially computer systems — will not have a deep impact.
Enterprise leaders determined to use to improve their businesses and ensure a return on their investment, however, face big challenges on several fronts: The domain of is changing rapidly because of the tremendous amount of research being done. The world’s biggest companies, research institutions and governments around the globe are supporting major research initiatives on .
There are a multitude of use cases: can be applied to any problem facing a company or to humankind writ large. In the COVID-19 outbreak, is playing an important role in the global effort to contain the spread, detect hotspots, improve patient care, identify therapies and develop vaccines. As we eventually emerge from the pandemic, analyst firm Forrester Research expects investment in -enabled hardware and software to surge as companies strive to build resilience against other catastrophes.
To reap the value of , enterprise leaders must understand how works, where technologies can be easily used in their businesses and where they cannot — a daunting proposition for the reasons cited above.
This wide-ranging guide to enterprise provides the building blocks for becoming an intelligent business consumer of . It begins with a brief explanation of how works and the main types of . You will learn about the importance of to companies, including a discussion of ’s principal benefits and the technical and ethical risks it poses; current and potential use cases; the challenges of integrating applications into existing business processes; and some of the technological breakthroughs driving the field forward. Throughout the guide, we include hyperlinks to TechTarget articles that provide more detail and insights on the topics discussed.
How does work?
Many of the tasks done in the enterprise are not automatic but require a certain amount of intelligence. What characterizes intelligence, especially in the context of work, is not simple to pin down. Broadly defined, intelligence is the capacity to acquire knowledge and apply it to achieve an outcome: The action taken is related to the particulars of the situation rather than done by rote
Getting a machine to perform in this manner is what is generally meant by . But as experts take pains to state, there is no single or simple definition of . In a 2016 report by the National Science and Technology Council on preparing for the future of , the authors noted that definitions of vary from practitioner to practitioner. […]
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