Microsoft is a Chief in 2022 Gartner Magic Quadrant for Cloud AI Developer Providers | Azure Weblog and Updates

Gartner has acknowledged Microsoft as a Chief within the 2022 Gartner® Magic Quadrant™ for Cloud AI Developer Providers, with Microsoft positioned furthest in “Completeness of Imaginative and prescient”.

Gartner defines the market as “cloud-hosted or containerized providers that allow improvement groups and enterprise customers who are usually not knowledge science consultants to make use of AI fashions through APIs, software program improvement kits (SDKs), or functions.”

A square chart split into four quadrants that compares Cloud AI Developer Services on a vertical axis for Ability to Execute and horizontal axis for Completeness of Vision. Microsoft is shown in the top right quadrant as a Leader on both axes.

We’re proud to be acknowledged for our Azure AI Platform. On this submit, we’ll dig into the Gartner analysis, what it means for builders, and supply entry to the complete reprint of the Gartner Magic Quadrant to be taught extra.

Scale clever apps with production-ready AI

“Though ModelOps practices are maturing, most software program engineering groups nonetheless want AI capabilities that don’t demand superior machine studying abilities. For that reason, cloud AI developer providers (CAIDS) are important instruments for software program engineering groups.”—Gartner

A staggering 87 p.c of AI initiatives by no means make it into manufacturing.¹ Past the complexity of information preprocessing and constructing AI fashions, organizations wrestle with scalability, safety, governance, and extra to make their mannequin’s manufacturing prepared. That’s why over 85 p.c of Fortune 100 firms use Azure AI right now, spanning industries and use circumstances.

Increasingly more, we see builders speed up time to worth through the use of pre-built and customizable AI fashions as constructing blocks for clever options. Microsoft Analysis has made important breakthroughs in AI over time, being the primary to realize human parity throughout speech, imaginative and prescient, and language capabilities. In the present day, we’re pushing the boundaries of language mannequin capabilities with giant fashions like Turing, GPT-3, and Codex (the mannequin powering GitHub Copilot) to assist builders be extra productive. Azure AI packages these improvements into production-ready normal fashions referred to as Azure Cognitive Services and use case-specific fashions, Azure Applied AI Services for builders to combine through API or an SDK, then proceed to high quality tune for higher accuracy.

For builders and knowledge scientists seeking to construct production-ready machine studying fashions at scale, we help automated machine studying also referred to as autoML. AutoML in Azure Machine Studying relies on breakthrough Microsoft analysis targeted on automating the time-consuming, iterative duties of machine studying mannequin improvement. This frees up knowledge scientists, analysts, and builders to concentrate on value-add duties exterior operations and speed up their time to manufacturing.

Allow productiveness for AI groups throughout the group

“As extra builders use CAIDS to construct machine studying fashions, the collaboration between builders and knowledge scientists will turn into more and more necessary.”—Gartner

As AI turns into extra mainstream throughout organizations, it’s important that workers have the instruments they should collaborate, construct, handle, and deploy AI options successfully and responsibly. As Microsoft Chairman and CEO Satya Nadella shared at Microsoft Build, Microsoft is “constructing fashions as platforms in Azure” in order that builders with totally different abilities can make the most of breakthrough AI analysis and embed them into their very own functions. This ranges from skilled builders constructing clever apps with APIs and SDKs to citizen builders utilizing pre-built fashions through Microsoft Power Platform.

Azure AI empowers builders to construct apps of their most well-liked language and deploy within the cloud, on-premises, or on the edge utilizing containers. Not too long ago we additionally introduced the aptitude to use any Kubernetes cluster and prolong machine studying to run near the place your knowledge lives. These sources might be run by means of a single pane with the administration, consistency, and reliability supplied by Azure Arc.

Operationalize Accountable AI practices

“Distributors and clients alike are in search of extra than simply efficiency and accuracy from machine studying mannequin. When deciding on AutoML providers, they need to prioritize distributors that excel at offering explainable, clear fashions with built-in bias detection and compensatory mechanisms.”—Gartner

At Microsoft, we apply our Responsible AI Standard to our product technique and improvement lifecycle, and we’ve made it a precedence to assist clients do the same. We additionally present instruments and sources to assist clients perceive, shield, and management their AI options, together with a Responsible AI Dashboard, bot development guidelines, and built-in instruments to assist them clarify mannequin conduct, check for equity, and extra. Offering a constant toolset to your knowledge science group not solely helps accountable AI implementation but in addition helps present higher transparency and allows extra constant, environment friendly mannequin deployments.

Microsoft is proud to be acknowledged as a Chief in Cloud AI Developer Providers, and we’re excited by improvements taking place at Microsoft and throughout the trade that empower builders to sort out real-world challenges with AI. You possibly can learn and be taught from the complete Gartner Magic Quadrant now.

Study extra


¹Why do 87 percent of data science projects never make it into production? Enterprise Beat.

Gartner Inc.: “Magic Quadrant for Cloud AI Developer Services,” Van Baker, Svetlana Sicular, Erick Brethenoux, Arun Batchu, Mike Fang, Could 23, 2022.

Gartner and Magic Quadrant are registered logos and repair marks of Gartner, Inc. and/or its associates within the U.S. and internationally and are used herein with permission. All rights reserved. This graphic was printed by Gartner, Inc. as half of a bigger analysis doc and ought to be evaluated within the context of the whole doc. The Gartner doc is on the market upon request from Microsoft. Gartner doesn’t endorse any vendor, services or products depicted in its analysis publications, and doesn’t advise expertise customers to pick solely these distributors with the very best rankings or different designation. Gartner analysis publications include the opinions of Gartner’s analysis group and shouldn’t be construed as statements of reality. Gartner disclaims all warranties, expressed or implied, with respect to this analysis, together with any warranties of merchantability or health for a specific objective.

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