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Azure OpenAI vs IBM Watson Machine Learning comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 4, 2024

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

Azure OpenAI
Ranking in AI Development Platforms
1st
Average Rating
7.8
Reviews Sentiment
6.7
Number of Reviews
33
Ranking in other categories
No ranking in other categories
IBM Watson Machine Learning
Ranking in AI Development Platforms
13th
Average Rating
8.0
Reviews Sentiment
7.1
Number of Reviews
7
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of April 2025, in the AI Development Platforms category, the mindshare of Azure OpenAI is 12.9%, down from 21.1% compared to the previous year. The mindshare of IBM Watson Machine Learning is 1.8%, down from 2.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AI Development Platforms
 

Featured Reviews

Viswanath Barenkala - PeerSpot reviewer
Offers tools to moderate generated content and guidance to safely design applications, but it is not consistently accessible
Instead of a feature, the GPT-4 model has been most beneficial for automating tasks. We transitioned from GPT-3.5 to GPT-4 and actively use it. However, we face limitations due to geographic availability, subscription constraints, and rate limiting, which we are currently negotiating and working towards optimizing. While we haven't formally benchmarked Azure OpenAI's language understanding against industry standards, we find it performs well about 70-80% of the time. Occasionally, we need to refine our queries and adapt our systems accordingly to improve accuracy and effectiveness.
Anurag Mayank - PeerSpot reviewer
A highly efficient solution that delivers the desired results to its users
I had not considered how the solution could be improved because I was focused on how it was helping me to solve my issues. If I consider how we want to use it in our organization, certain areas of improvement can be addressed. For instance, we want to use it with Generative AI, not like ChatGPT, but in a way intended for industrial use. It would be beneficial to incorporate more AI into the solution.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"The solution has a very drag-and-drop environment. Instead of coding something from scratch or understanding any concept in extensive depth before deployment, this is good. Plus, they have an auto dataset, which means you can choose any dataset they have instead of providing your own. So that's also pretty nice."
"The most valuable features include analyzing comments and preparing requests for customers, making emails easier and faster."
"We can use the solution to implement our tasks and models quickly."
"Azure's integration with OpenAI's GPT is beneficial as well, especially for text generation tasks."
"The product is easy to integrate with our IT workflow."
"Its ability to understand and respond well to queries, including language translation for clients, is beneficial."
"The product saves a lot of time."
"Azure OpenAI is very easy to use instead of AWS services."
"I was particularly interested in trying the AutoML feature to see how it handles data and proposes new models. The variety of models it provides is impressive."
"The most valuable aspect of the solution's the cost and human labor savings."
"We can enable and change developer productivity with artificial intelligence-recommended code based on natural language input or exciting source code."
"It has improved self-service and customer satisfaction."
"The solution is very valuable to our organization due to the fact that we can work on it as a workflow."
"It is has a lot of good features and we find the image classification very useful."
"Scalability-wise, I rate the solution ten out of ten."
 

Cons

"We are awaiting the new updates like multi-model capabilities."
"Azure needs to work on its own model development and improve the integration of voice-to-text services, particularly for right-to-left languages such as Arabic and Urdu. The accuracy in these languages requires improvement."
"The product must improve its dashboards."
"The dialogue manager needs to be improved."
"Deployment was slightly complex for me to understand."
"There could be an ability to generate visual data, such as architecture diagrams."
"There is room for improvement in their support services."
"There are certain shortcomings with the product's scalability and support team where improvements are required."
"Honestly, I haven't seen any comparative report that has run the same data through two different artificial intelligence or machine learning capabilities to get something out of it. I would love to see that."
"In future releases, I would like to see a more flexible environment."
"They should add more GPU processing power to improve performance, especially when dealing with large amounts of data."
"The supporting language is limited."
"Scaling is limited in some use cases. They need to make it easier to expand in all aspects."
"Sometimes training the model is difficult."
"If I consider how we want to use it in our organization, certain areas of improvement can be addressed. For instance, we want to use it with Generative AI, not like ChatGPT, but in a way intended for industrial use."
 

Pricing and Cost Advice

"I rate the product pricing six out of ten."
"Azure OpenAI is a bit more expensive than other services."
"Regarding pricing and licensing, it's a bit complex due to the minimum purchase requirement for PTO units. We're evaluating the best approach between PTE and pay-as-you-go models. Our organization is cautious about committing to PTE due to the fixed bandwidth reservation, while pay-as-you-go doesn't offer enough flexibility. We're discussing these matters with legal teams to ensure compliance and data security."
"I'm uncertain about the licensing, specifically the pricing. This falls under the purview of other teams, particularly the sales teams. I am not informed about the pricing details."
"The cost is quite high and fixed."
"The pricing is acceptable, and it's delivering good value for the results and outcomes we need."
"We started with monthly payments, but we plan to switch to yearly billing once we've stabilized our solution."
"According to the negotiations taking place and the contract, there is a need to make either monthly or yearly payments to use the solution."
"The pricing model is good."
"I've only been using the free tier, but it's quite competitive on a service basis."
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Top Industries

By visitors reading reviews
Financial Services Firm
15%
Computer Software Company
13%
Manufacturing Company
11%
Government
6%
Computer Software Company
16%
Financial Services Firm
12%
Educational Organization
11%
University
10%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

What do you like most about Azure OpenAI?
The product is easy to integrate with our IT workflow.
What is your experience regarding pricing and costs for Azure OpenAI?
The pricing is very good for handling various kinds of jobs. While small jobs are manageable, more complex jobs require a higher model, which is a bit challenging.
What needs improvement with Azure OpenAI?
Maybe with the next release, the response will be more precise and more human-like.
What do you like most about IBM Watson Machine Learning?
I was particularly interested in trying the AutoML feature to see how it handles data and proposes new models. The variety of models it provides is impressive.
What needs improvement with IBM Watson Machine Learning?
Sometimes training the model is difficult. We need to have at least a few different components to evaluate and understand the behavior of different users to have a very, very high accuracy in the m...
 

Overview

Find out what your peers are saying about Azure OpenAI vs. IBM Watson Machine Learning and other solutions. Updated: March 2025.
845,040 professionals have used our research since 2012.