Report explores how organizations using AI are making it work, what technologies they’re using, and what best practices can maximize an organization’s success with AI and machine learning
Seattle, WA, Oct. 18, 2019 (GLOBE NEWSWIRE) -- TDWI Research has released its newest Best Practices Report, Driving Digital Transformation using AI and Machine Learning. This original, survey-based report looks at the many dimensions of artificial intelligence (AI) and machine learning (ML) so data professionals and their business counterparts can understand the benefits of the technology, how it’s used (and by whom), and how enterprises are achieving success with it.
The author of the report, Fern Halper, is vice president and senior director of TDWI Research for advanced analytics. She explains that organizations are embracing AI and ML to gain better insights, make better decisions, and improve competitive advantage. “In fact,” she writes, “AI is at the heart of the digital revolution around analytics occurring today. AI promises to help organizations improve their operations and processes and to drive new revenue opportunities.”
The report examines the many dimensions of AI, including why it is being deployed, by whom, and what best practices enterprises successful with AI use to ensure their success. She explores the skills needed for AI and the roles of data scientists, DevOps, and business analysts for AI.
This comprehensive report reveals:
- The importance of embedding AI and machine learning models and other AI technologies in intelligent applications, which are used within (38% of respondents) and outside (27%) the enterprise
- The most popular use case for AI is building predictive models using tools such as ML, according to 85% of respondents, followed by automating the generation of insights using tools with augmented intelligence
- Almost two-thirds (64%) of respondents using AI are using natural language processing, including text analytics; 35% of active AI users are developing bots for customer service
- Nine in ten respondents (90%) working with AI are using machine learning
- Those enterprises already using AI typically have five or more deployments in place
- Although data quality is critical for success with AI, only 14% of respondents are using AI-infused data quality tools that automate data cleansing
- The seven key challenges for the future of AI
The report also includes a glossary of popular AI technologies, such as transfer learning, deep learning, augmented intelligence, automated machine learning model building, and robotic process automation. Halper explores the importance of infrastructure to support AI, including the role multiplatform data environments and data catalogs play with AI, and why data pipelines are vital if digital transformations are to be successful.
Halper presents comments from survey respondents about best practices for success and shares five success factors that enterprises actively involved with AI have in common.
This research was sponsored by Alation, Hitachi Vantara, Infoworks, and Melissa Data.
About the Author
Fern Halper, Ph.D., is vice president and senior director of TDWI Research for advanced analytics. She is well known in the analytics community having been published hundreds of times on data mining and information technology over the past 20 years. Halper is also co-author of several Dummies books on cloud computing and big data. She focuses on advanced analytics, including predictive analytics, text and social media analysis, machine learning, AI, cognitive computing and big data analytics approaches. She has been a partner at industry analyst firm Hurwitz & Associates and a lead data analyst for Bell Labs. Her Ph.D. is from Texas A&M University. You can reach her by email (email@example.com), on Twitter (twitter.com/fhalper), and on LinkedIn (linkedin.com/in/fbhalper).
For more than 20 years, TDWI has provided individuals and teams with a comprehensive portfolio of business and technical education and research about all things data. TDWI’s in-depth, best-practices-based knowledge can be quickly applied to develop world-class talent across your organization’s business and IT functions to enhance analytical, data-driven decision making. TDWI offers four major conferences as well as topical seminars, onsite education, membership, certification, live webinars, resource-filled publications, industry news, and in-depth research. Visit tdwi.org or follow us on Twitter @TDWI.
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