This article series is designed to provide you with insight on the ways artificial intelligence (AI), machine learning (ML), and deep learning (DL) can be (or already are being) utilized in a variety of industries.
Although artificial intelligence (AI), machine learning (ML), and deep learning (DL) have been around for more than half a century, we still aren’t anywhere close to being able to create complex machines that possess all the characteristics of human intelligence. However, we have learned how to get computers to perform certain tasks – especially repeatable tasks – as well as, or in some cases, better than human beings. And, we have learned how to embed AI, ML, and DL into business processes to generate insights that can have a profound impact on the way an organization sets themselves apart from their competitors.
In fact, AI, ML, and DL are being used in this manner today to:
- Disrupt industry leaders (by enabling smaller companies with fewer resources to create innovative techniques that challenge the established way of doing business – for example Uber and Airbnb)
- Expand a company’s demographic reach (by predicting customer behavior, evaluating customer sentiment towards products and services offered, and using predictive analytics to gain insight into how a new product or service will be accepted)
- Personalize interactions with customers
- Improve IT operational efficiency
- Detect fraud – not only after it has taken place – but also before a fraudulent transaction is completed
- Improve employee and/or operational productivity (by looking at behavioral patterns of employees or characteristics of targeted operations)
The use cases for AI, ML, and DL are endless. And research has shown that companies are rapidly becoming adopters. In a recent study titled, The State of Machine Learning Adoption in the Enterprise, O’Reilly noted that “49% of organizations reported they were exploring or looking into deploying ML, while a slight majority of 51% claimed to be early adopters.” Moreover, Forbes’ Roundup Of Machine Learning Forecasts And Market Estimates, 2020 states that one in ten enterprises now use ten or more AI applications.
Chatbots, process optimization, and fraud analysis lead in use cases. And according to MMC Ventures’ The State of AI Divergence, 2019, report (referenced in the Forbes report just cited), the most prevalent AI applications include consumer/market segmentation (15%), computer-assisted diagnostics (14%), call center virtual assistants (12%), sentiment analysis/opinion mining (12%), face detection/recognition (11%), and HR applications such as those used to screen resumes (10%).
Stay Tuned
In the next part of this article series, we’ll take a look at how AI, ML, and DL are being used in the financial sector.
Sources:
The State of Machine Learning Adoption in the Enterprise: (O’Reilly)
https://www.oreilly.com/data/free/state-of-machine-learning-adoption-in-the-enterprise.csp
Roundup Of Machine Learning Forecasts And Market Estimates, 2020 (Forbes)
https://www.forbes.com/sites/louiscolumbus/2020/01/19/roundup-of-machine-learning-forecasts-and-market-estimates-2020/?sh=5f8e2ce75c02
Roger E. Sanders is a Principal Sales Enablement & Skills Content Specialist at IBM. He has worked with Db2 (formerly DB2 for Linux, UNIX, and Windows) since it was first introduced on the IBM PC (1991) and is the author of 26 books on relational database technology (25 on Db2; one on ODBC). For 10 years he authored the “Distributed DBA” column in IBM Data Magazine, and he has written articles for publications like Certification Magazine, Database Trends and Applications, and IDUG Solutions Journal (the official magazine of the International Db2 User's Group), as well as tutorials and articles for IBM's developerWorks website. In 2019, he edited the manuscript and prepared illustrations for the book “Artificial Intelligence, Evolution and Revolution” by Steven Astorino, Mark Simmonds, and Dr. Jean-Francois Puget.
From 2008 to 2015, Roger was recognized as an IBM Champion for his contributions to the IBM Data Management community; in 2012 he was recognized as an IBM developerWorks Master Author, Level 2 (for his contributions to the IBM developerWorks community); and, in 2021 he was recognized as an IBM Redbooks Platinum Author. He lives in Fuquay Varina, North Carolina.
MC Press books written by Roger E. Sanders available now on the MC Press Bookstore.
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QuickStart Guide to Db2 Development with Python Discover how Python, SQL, and Db2 can successfully be used with each other. List Price $9.95 Now On Sale
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Artificial Intelligence: Evolution and Revolution Operational AI has become available to the masses, setting the wheels in motion for a worldwide AI revolution that has never been seen before. List Price $16.95
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Data Fabric: An Intelligent Data Architecture for AI This book explains the concepts and values that a data fabric approach can deliver to both technical and business communities. List Price $19.95
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Business users want new applications now. Market and regulatory pressures require faster application updates and delivery into production. Your IBM i developers may be approaching retirement, and you see no sure way to fill their positions with experienced developers. In addition, you may be caught between maintaining your existing applications and the uncertainty of moving to something new.
IT managers hoping to find new IBM i talent are discovering that the pool of experienced RPG programmers and operators or administrators with intimate knowledge of the operating system and the applications that run on it is small. This begs the question: How will you manage the platform that supports such a big part of your business? This guide offers strategies and software suggestions to help you plan IT staffing and resources and smooth the transition after your AS/400 talent retires. Read on to learn:
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