Amazon Quick Pitches Connected Workflows as Vertiv Plans 25% User Growth in 2026
AWS is framing Quick as a conversational layer across business systems, but its customer examples describe deployments and intended uses rather than comparable measures of productivity or return.
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3 key pointsAWS is using Amazon Quick to make a broader enterprise-AI case: connected agents can retrieve internal, web and third-party context, act across business software, and produce finished files or lightweight tools. The clearest expansion signal is Vertiv’s plan to increase Quick users by at least 25% in 2026. However, the customer examples remain qualitative; they show deployment and intended scale, not comparable...
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Vertiv plans to grow its Amazon Quick user base by 25% or more during 2026.
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AWS says Quick connects to thousands of applications and data sources through built-in connectors.
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Quick can generate documents, presentations, spreadsheets and images, plus no-code intake forms and calculators.
AWS is promoting Amazon Quick as a work assistant that uses agentic teammates for research, business insights and automation, while also turning conversations into finished work products. The pitch is a broad one: connect business systems, retrieve context, take actions and create outputs without leaving the assistant.
That positioning matters because Quick is not being presented as a single-purpose chatbot or reporting tool. AWS says it can conduct research across business data, the public internet and third-party datasets, then produce documents, presentations, spreadsheets or images from the conversation. It also says the service can schedule meetings, build dashboards and automate repetitive tasks.
The connective layer
The mechanism AWS emphasizes is connection rather than a new standalone interface. Quick is described as connecting to thousands of applications and data sources through built-in connectors for popular apps. AWS says those connections let the assistant pull context, take action and return results from a single conversation.
- Research can draw on internal business information, public-web material and third-party datasets.
- Conversation outputs can include a document, presentation, spreadsheet or image.
- Teams can create internal intake forms, status trackers and specialized calculators without writing code, according to AWS.
Vertiv says it plans to scale its Amazon Quick users by 25% or more in 2026.
Adoption evidence is use-case specific
AWS supports the enterprise pitch with four customer examples, each describing a different stage or purpose. DXC Technology says it deployed Quick across its global workforce to test AI at enterprise scale with guardrails. Vertiv calls the product a catalyst for digital transformation and says it intends to expand users in 2026.
The other examples are narrower operational claims. 3M says it uses Quick’s agentic capabilities to synthesize information about sales effectiveness, risks and pricing. Jabil says its unified capabilities are part of an AI-driven transformation effort focused on efficiency and operational excellence.
A broad promise, with a measurement gap
The customer accounts establish that Quick is being deployed, used for targeted information synthesis and considered for wider rollout. They do not provide comparable productivity, cost or accuracy results, so they cannot yet show which parts of the connected-workflow pitch deliver the greatest operational gains. The nearer-term test is whether companies turn those discrete uses into sustained, scaled access such as the expansion Vertiv has planned.
Sources
- aws.amazon.comNot all enterprise AI is built the same. CIOs are asking: Does this AI connect to your tools? Respect your permissions? Keep data where it belongs? Amazon Quick checks all three, s