JP Morgan frontline research: Microsoft is at least 10 light-years ahead of everyone else, with very strong ecosystem integration capabilities!

JP Morgan's latest frontline research indicates that Microsoft has established a significant advantage in the cloud ecosystem integration field, described by respondents as "leading everyone by at least 10 light-years." Its comprehensive and collaborative product system is becoming the preferred platform for enterprises to scale AI and digital transformation.

This conclusion is based on in-depth interviews with over 30 key industry participants, including system integrators, software suppliers, distributors, and large clients. The research further reveals that key trends in the software market over the next 12-18 months include: AI projects are transitioning from pilot scale (USD 250,000 - 500,000) to production-level investments (USD 2.5 million - 5 million); decision-making power for enterprise IT spending has shifted from Chief Information Officers to Chief Financial Officers, with decisions increasingly focused on clear measurable returns and investment cycles; at the same time, data infrastructure companies like Databricks, Snowflake, and Datadog continue to benefit from this transformation process.

These frontline market feedbacks provide investors with a forward-looking perspective distinct from public financial reports, helping to identify structural opportunities and potential risks in the software sector in the near future.

Microsoft's Ecological Advantage Highlights Accelerated AI Project Implementation

The report points out that Microsoft has established a significant advantage in ecosystem integration, described by respondents as "leading other vendors by at least 10 light-years." By systematically integrating capabilities such as Work IQ and Fabric IQ into its product matrix, it has built a collaborative ecosystem centered on global efficiency and data insights.

In contrast, AWS focuses more on the infrastructure layer, while Google delves deeply into the data field. This difference has translated into actual market performance—federal business insiders have revealed that the Azure team in their organization has significantly outgrown the AWS team.

At the same time, AI applications are accelerating from pilot to large-scale production. System integrators have observed that AI project budgets have expanded from the pilot range of USD 250,000 - 500,000 to production-level deployments of USD 2.5 million - 5 million, with most enterprises building internal solutions based on OpenAI and Anthropic's APIs. Specific cases show that AI has helped biotechnology clients reduce molecular screening cycles from five years to several weeks, saving millions of dollars in R&D costs, marking a stage where AI investment returns become quantifiable and perceptible.

AI Scaling Faces Cost and Implementation Challenges

Despite Microsoft's clear advantages, competition remains fierce: AWS is seen as the closest contender, with Google following closely in an agile manner. Data also shows a coexistence of integration and divergence—Snowflake and Databricks are mutually penetrating, and enterprise choices are often driven by culture: business-oriented preferences lean towards Snowflake, while technology-oriented preferences favor Databricks, with large enterprises often having both.

The report also highlights structural challenges facing the industry: reasoning costs are under stricter scrutiny due to their inclusion in sales costs; the scaling of AI projects is still constrained by a lack of "repeatable, standardized use cases"; furthermore, change management during the implementation process is also a key limiting factor

IT Budget Stabilizes, Data Investment Heats Up

Multiple respondents pointed out that the IT budget in 2026 will not experience explosive growth, but the pipeline is healthy. The key change is: "Now CFOs and finance departments are reviewing IT spending, whereas three years ago it was led by CIOs. Customers are focusing on shorter cycles, ROI, and cash returns." Some system integrators indicated there is a backlog of spending on "non-AI software," as companies realize the need to simultaneously maintain core systems such as CRM, HCM, and ERP.

Investment in data infrastructure remains active. Respondents stated: "Customers are very serious about data modernization and are actively addressing the gaps after realizing them." Snowflake and Databricks are experiencing rapid billing growth, which sometimes surprises customers, but most still recognize the value. The adoption rate of Databricks Lakehouse on Azure significantly increased in Q3