Deciding Who’s Who in Cloud, Data and AI


Every vendor aspires to be #1 in their marketplace – or be recognized as a leader in a particular segment. Vendors often overstate their offerings’ capabilities and characteristics to create the perception of unique differentiation over competitors.  While these may be easy claims to make, they can leave customers and prospects confused as to who’s who when it comes to being the market leader for a particular market segment.

Claiming to be #1 is subjective as it is based on the needs, wants and perceptions of the organization or individual evaluator.  To help decipher these claims, I believe it is best to refer to independent industry analysts who will ask customers about their perceptions – based on their experiences of using vendors’ offerings.  Added to this, each industry analyst firm develops and uses their own methodology for positioning and evaluating vendors’ offerings in particular market segments as to whether a vendor is identified as a leader. Often, analyst firms define those market segments differently.

Analyzing and Interpreting your findings

In this recent IBM News article of March 25 2021 Gartner positioned IBM as a Leader in the 2021 Gartner Magic Quadrant for Insight Engines1. Insight engines combine search capabilities with artificial intelligence to deliver actionable insights derived from a full spectrum of content and data sourced within – and external to – an enterprise. 

IBM Watson Discovery is an insight engine. It is an AI-powered search and text-analytics service, using advanced natural language processing (NLP) to help companies find new insights from complex enterprise documents and data. 

To give businesses, data scientists and developers the capabilities they need to scale AI, IBM continues to bring new innovations to IBM Watson from IBM Research in the core areas of NLP, trust and automation. In 2020, IBM unveiled advanced NLP capabilities from IBM Research Project Debater in IBM Watson, expanded its AI-powered automation capabilities with the launch of IBM Watson AIOps and announced AI Factsheets, a new methodology for embedding trust and transparency into the development of AI models. Over the past year, IBM unveiled new features in beta for IBM Watson Discovery including Reading Comprehension; commercialized advanced sentiment analysis and summarization tools.

Earlier this month in this IBM News article of March 11 2021, Gartner positioned IBM as a leader in two other published Gartner Magic Quadrant reports: the 2021 Magic Quadrant for Cloud AI Developer Services[2] and the 2021 Magic Quadrant for Data Science and Machine Learning Platforms[3]

All these reports position vendors based on their “completeness of vision” and “ability to execute”.

As stated in the aforementioned news article, IBM tries to bring value to organizations through its strategy and the strong innovation pipeline between IBM Research and IBM Watson technologies. For example, IBM designed IBM Watson Studio on IBM Cloud Pak for Data to provide end-to-end AI lifecycle management for both experts and citizen data scientists and developers, and to provide strong support for areas such as explainability, fairness and governance to help businesses build AI models that they can trust.

Customers are more than willing to talk with analysts about the experiences of using a vendor’s offerings. After all, customers are the ultimate judges of how well a vendor’s offerings meet or exceed their business needs.

Your Next Steps

Deciding if a vendor is #1 can be challenging. It is really down to the perceptions of the organizations and their users’ experiences of those offerings.  I certainly can’t make a definitive claim as to whether a particular vendor is #1. So, I refer you to some useful resources that are publicly available so that you, the reader, can arrive at your own conclusions.

For your convenience, complimentary copies of the Gartner Magic Quadrant reports mentioned above are listed here:

Other publicly available analyst reports are also available here:

And more information about IBM Watson can be found here

1 Source: Gartner, “Magic Quadrant for Insight Engines,” Stephen Emmott, Anthony Mullen, [March 22, 2021]

2 Source: Gartner, “Magic Quadrant for Cloud AI Developer Services,” Van Baker, Bern Elliot, Svetlana Sicular, Anthony Mullen, Erick Brethenoux, [February 24, 2021]

3 Source: Gartner, “Magic Quadrant for Data Science and Machine Learning Platforms,” Peter Krensky, Carlie Idoine, Erick Brethenoux, Pieter den Hamer, Farhan Choudhary, Afraz Jaffri, Shubhangi Vashisth, [March 1, 2021]

4 Source: Gartner, Magic Quadrant for Data Integration Tools, Ehtisham Zaidi, Eric Thoo, Nick Heudecker, Sharat Menon, Robert Thanaraj, [18 August 2020]

5 Source: The Forrester WaveTM: Multimodal Predictive Analytics And Machine Learning, Q3 2020. The 11 Providers That Matter Most And How They Stack Up by Mike Gualtieri and Kjell Carlsson, PhD [September 10, 2020] 

6 Source: IDC MarketScape: Worldwide Advanced Machine Learning Software Platforms 2020 Vendor Assessment by Ritu Jyoti and David Schubmehl [October 2020]

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