Artificial Intelligence (AI) has world-changing implications—and momentous changes are already occurring. Building a greater understanding of this technology, especially in business, is essential. The decisions we make now about how it may be used in the future could impact society for centuries. AI is already improving so rapidly that it will soon affect virtually every aspect of our lives. Explore this page to learn more about different types of AI, and where, when, and how they’re already being implemented in business.
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Simply put, Artificial Intelligence (AI) is about making computer-based machines think and act like human beings. The term actually goes back to the mid-20th century, but AI’s advancement and the types of AI we use have always been dependent on the speed and power of computers—which is why we’re hearing and talking about it more with each passing year. The faster the computers are, the faster AI can evolve into something new and more human-like. Forecasts of how AI will impact the future can therefore change constantly—so educating ourselves on AI technology and embracing its capabilities in the present, while exploring its new possibilities as it continually changes, is probably the best way (and likely the only way) to maintain some semblance of readiness for an uncharted future. In business in particular, we must also be cognizant of how strategic decisions we make today on using AI in the workplace can have a long-lasting impact on our future success.
It can create images. It can work in the audio modality. It can listen to your speech and take a live transcription. Of course, it continues to be able to make decisions, especially ones driven with numbers and make translations between human to human languages, sometimes human to machine languages
There are many evolving pros and cons of AI in the workplace; for example, AI technology may eliminate one type of job function, while simultaneously creating opportunities for a new type of job. For the present, businesses can choose from among a selection of different AI technologies to enhance, support, simplify, modify, or even automate certain processes. The following models are currently relevant to this effort:
- Machine learning
With machine learning, an algorithm executes a particular task as it was instructed to do, remembers the output of the task, and integrates that information into the software. It can then update its own internal instructions to create a better, more efficient output the next time.
The inherent power of machine learning is that it allows us to not only create models, but train them gradually so that they can ultimately yield the results we desire.
- Natural language processing (NLP)
Natural language processing refers to a computer’s ability to understand human language, both written and spoken. A chatbot, for example, looks at all of the past natural language search data on a subject, as well as available response data, and can then formulate a reasonable, “human” type of response.
- Generative AI
Generative AI is where AI actually begins to mimic human intelligence, and in many cases, exceed it. A common example of this today is ChatGPT. (GPT is an acronym for Generative Pre-Trained Transformer, because it was pre-trained based on the data it had “learned” to communicate with.) Since it’s generative, it responds to and creates (generates) a response or content when requested to do so, and based on the volume of human-created input data that it has absorbed, it can produce conversational, natural language responses.
Because it's pre-trained, a business can utilize its algorithm and retrain it to generate responses based on that business’s own data. It therefore has the capability to scan huge volumes of existing data and use it as a basis for generating an entirely “new” output. It scans and reorganizes existing work it has access to, while discerning patterns in that existing work.
Another benefit of AI in the workplace is that it can draw upon large amounts of data that have been already been measured, and analyze it and develop a model so a new output can be created, such as predictive models and simulations of new models. When one uses an Excel document with a large amount of data and then applies its tools to reveal a trend, for example, AI techniques are being employed to generate new data that would have previously required the effort of human beings. With enough data to power its model, AI’s predictive analytics capabilities can produce new predictions down to the second, if desired.
These types or predictive analytics (or logistics-oriented AI) can also be used in scheduling, as in proactive alerts for medical screenings.
AI can be used in process automation by employing software and technology to automate complex business processes and functions. Organizations in all kinds of industries utilize it to improve administrative efficiency. A common example of this is AI-powered accounts receivable automation to pull data from invoices and match them with prior purchase orders. The technology can then follow up on payments due, evaluate creditworthiness, forecast cash flow and more—thus eliminating the need for a dedicated team of people to perform these functions.
Human Resources teams today use AI to screen candidates, enhance onboarding, manage performance, hire new employees, and more functions typically performed by people.
In addition, most of us have encountered phone menus when calling banks, credit card providers, insurance companies, etc., that use AI technology to offer us options (e.g., “If you’d like to report your card lost or stolen, press 1,” or “To make a payment, press 3,” etc.) These virtual assistants have improved in sophistication and are also more adept at discerning the caller’s purpose in making the call.
Examples of AI in the Workplace
Companies use customer-facing chatbots to handle and streamline routine and repetitive customer service requests, freeing up employees for more complex and creative endeavors.
- Topic Modeling
Topic modeling is a machine learning process that surveys and scans a large volume of documents and independently discerns word and phrase patterns, similar expressions, as well as different topics that occur in the documents, and can abstract or discover the essence of the documents. It is used for preliminary document sorting and can help to sort and separate the information relevant to what the user is seeking.
Whether we’ve noticed it or not, AI has permeated our work and personal lives in countless ways for years—in healthcare, manufacturing, retail, and financial services, to name just a few. Companies and service industries utilize AI to streamline processes, improve the customer experience, and increase efficiencies of all kinds.
We encounter AI-driven software whenever we browse or order from Amazon, look for a movie on Netflix, perform routine or complex searches in Google, use an iPhone to find a restaurant, determine the best itinerary to a particular location, order an Uber to get to the airport, or almost anything that would have required human interaction and knowledge before AI. From shopping to communicating to planning and beyond, AI is everywhere and will continue to be.
Creative professions also use AI in creating images, writing content, etc. It is also being used in education at all levels, inventory and supply chain management, for medical research and analysis, patient diagnoses and treatments, pharmaceutical research, vaccine development, etc.,
AI can also analyze demographics, develop and update software, generate monitoring and emergency alerts, and almost any other endeavor previously dependent on human intelligence and effort.
As summarized and reported in a recent AMA research report, Artificial Intelligence (AI) Is Booming, But Companies Are Not Ready, most organizations lack the strategic plans and processes to manage and capitalize on the vast capabilities of AI.
AMA recently surveyed 457 business professionals in a broad range of industries to learn about their perspectives on AI and its impact on their companies. Only 43% of respondents said their companies plan to use AI, and less than a third have already leveraged the technology.
To discover other key findings and explore the complete results of our research, read our complimentary Whitepaper:
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Before implementing an AI strategy in the workplace, it’s important for those in leadership and management roles to understand the different uses of AI, the implications of utilizing a still-evolving technology, and how it might affect the jobs of those on their teams. See below for tools and resources to help business professionals take charge of AI in this changing landscape.
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