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Improving VMware migration workflows with agentic AI

9 min readMIT Technology Review
Cambridge, Massachusetts, United States
Improving VMware migration workflows with agentic AI
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For years, many chief information officers (CIOs) looked at VMware-to-cloud migrations with a wary pragmatism. Manually mapping dependencies and rewriting legacy apps mid-flight was not an enticing, low-lift proposition for enterprise IT teams. But the calculus for such decisions has changed dramatically in a short period of time. Following recent VMware licensing changes, organizations are seeing greater uncertainty around the platform’s future.

At the same time, cloud-native innovation is accelerating. According to the CNCF’s 2024 Annual Survey, 89% of organizations have already adopted at least some cloud-native techniques, and the share of companies reporting nearly all development and deployment as cloud-native grew sharply from 2023 to 2024 (20% to 24%).

And market research firm IDC reports that cloud providers have become top strategic partners for generative AI initiatives. DOWNLOAD THE ARTICLE This is all happening amid escalating pressure to innovate faster and more cost-effectively to meet the demands of an AI-first future.

As enterprises prepare for that inevitability, they are facing compute demands that are difficult, if not prohibitively expensive, to maintain exclusively on-premises. Download the full article. This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff.

This content was researched, designed, and written by human writers, editors, analysts, and illustrators. This includes the writing of surveys and collection of data for surveys. AI tools that may have been used were limited to secondary production processes that passed thorough human review.

Brightcast Impact Score (BIS)

30/100Minimal

The article discusses the changing landscape of VMware migrations to the cloud, highlighting the increasing adoption of cloud-native techniques and the role of cloud providers in generative AI initiatives. While it does not directly showcase a proven solution or measurable progress, it suggests that enterprises are facing pressure to innovate faster and more cost-effectively to meet the demands of an AI-first future, which could be seen as a modest positive achievement.

Hope Impact6/33

Emotional uplift and inspirational potential

Reach Scale12/33

Potential audience impact and shareability

Verification12/33

Source credibility and content accuracy

Limited positive elements

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