CIO Survey Shows Software Spending Continues to Lead in 2026, with AI and Automation Becoming Core Incremental Themes
AI summary card
CIO Survey Shows Software Spending Continues to Lead in 2026, with AI and Automation Becoming Core Incremental Themes
Morgan Stanley’s 2026 first-quarter CIO call shows a moderately improving IT budget environment, with incremental funding mostly going to software, AI/ML, workflow automation, and data management, while companies overall still prefer packaged solutions over large-scale build-it-yourself approaches.
- CIOs expect 2026 IT budget growth of 3.7%, slightly above 3.6% in 2025, but still below the 10-year average of 4.1%.
- Software is expected to remain the fastest-growing major IT area; the report text cites year-over-year growth of 4.1%, while charts show software spending expected to grow 3.8% in 2026.
- AI/ML remains the top spending priority, accounting for 17.7% in 1Q26, up from 16.3% in 4Q25.
- Enterprises still lean toward buying packaged AI solutions, but may add custom coordination layers, data management, and process tools when interoperability is insufficient or pricing pressure rises.
- Microsoft is viewed by CIOs and specialists as having the clearest edge in AI applications, automation, hybrid cloud, and Copilot deployment.
Report interpretation
Overview
This report summarizes Morgan Stanley’s software-industry 2026 Q1 CIO conference call and survey highlights, based on discussions with three CIOs on April 9 and AlphaWise survey results, covering the 2026 IT budget, software spending, AI/ML priorities, buy-versus-build decisions, workflow automation, data platforms, and the competitive positioning of major software vendors. The core conclusion is that the budget environment has improved, but incremental capital is not broadly distributed and is instead more concentrated in software, AI, application workflows, and data access-related areas.
Core views
The report argues that software remains the most resilient and growth-oriented area in 2026 IT spending. AI/ML remains the top enterprise priority, but the size of budget adjustments indicates CIOs are still cautious. Enterprises usually do not want to fully rebuild core systems and generally prefer buying capabilities from mature vendors; however, in areas such as cross-system interoperability, pricing pressure, data integration, and agent orchestration, in-house or custom development needs may increase. Microsoft is well positioned due to Azure, Copilot, productivity suites, hybrid cloud management, and automation application scenarios. Salesforce, ServiceNow, Google, Amazon, Snowflake, Databricks, and others also benefit in different areas.
Analysis framework
The report combines CIO survey data, conference call expert commentary, and vendor share/priority charts, and summarizes by IT budget, software growth, AI vendor selection, automation use cases, data platforms, and competitive advantages across key vendors. The analysis is focused on enterprise IT procurement direction and changes in software-industry demand structure rather than valuation of any single company.
Methodology notes
CIO Budget and Vendor-Choice Survey
Tracks IT budget growth, AI/ML priorities, vendor-type preferences, and automation use cases across U.S. and EU CIO samples, to assess demand direction in the software industry.
Minutes of Three CIO Interviews
Supplementary commentary on buying packaged solutions, in-house tools, process automation, Copilot deployment, data platforms, and AI agent implementation to provide implementation logic behind the survey data.
Ranking of AI and Automation Beneficiary Vendors
Compares the relative positioning of Microsoft, Google, Amazon, ServiceNow, Salesforce, Snowflake, Databricks, and others in AI applications, automation, and data management.
Asset mapping & comparison
Structured mapping from thesis to named assets (strengths, weaknesses, peers, risks).
- Microsoft (MSFT.O)Core Beneficiary
- Strengths
- Azure, Copilot, productivity tools, hybrid cloud management, and automation scenarios all receive strong positive CIO feedback; Microsoft leads in multiple AI application and automation surveys.
- Weaknesses
- Actual productivity gains from Copilot still need quantification, and demonstrating return on investment for continued monthly subscriptions remains a challenge.
- Comparison
- Compared with Google, Amazon, and ServiceNow, Microsoft is stronger in productivity tooling and enterprise workflow entry points.
- Risks
- AI feature monetization may fall short, deployment pace may be slower than expected, and cautious budgets could limit expansion.
- ServiceNowWorkflow Automation Beneficiary
- Strengths
- Has a platform foundation in ITSM and workflow automation, and is viewed as a key participant in AI automation and agent workflow initiatives.
- Weaknesses
- Cross-platform interoperability and cost issues may cause customers to seek alternatives or build custom orchestration layers.
- Comparison
- Stands alongside Atlassian, Helix, and Moveworks in enterprise workflow automation discussions.
- Risks
- If it cannot support open collaboration or integration with other systems, customers may reduce reliance on it.
- SalesforceApplication Software and AI Spending Beneficiary
- Strengths
- Has advantages in generic AI-related spending, custom AI application deployment, and automation workflows.
- Weaknesses
- CIOs noted the risk that older system functions may be gradually replaced by newer automation tools, potentially leaving only a data role.
- Comparison
- Together with SAP, it is an enterprise platform category into which intelligent functions can be embedded.
- Risks
- Price, interoperability, and process redesign could weaken customer lock-in.
- SnowflakeData Management Beneficiary
- Strengths
- Well suited for multi-team data analytics, business reporting, scenario analysis, and P&L-related work; the toolchain lowers ETL and platform adoption complexity.
- Weaknesses
- CIOs have not yet seen significant direct impact from combining AI with Snowflake; AI influence is still mostly seen in indirect scenarios such as report automation.
- Comparison
- Compared with Databricks, it is more focused on business data analytics and shared platforms, while Databricks is more focused on processing platforms and building production systems.
- Risks
- Unclear direct AI-native value, data platform cost control, and competitive pressure.
- DatabricksData and AI Processing Platform Beneficiary
- Strengths
- Seen as a data processing platform used to build production systems, handle ERP-related tasks, and support model/agent operations.
- Weaknesses
- The report provides fewer descriptions of direct commercial tailwinds for Databricks than for Microsoft and Snowflake.
- Comparison
- Also a data platform alongside Snowflake, but positioned more toward engineering processing and AI system build-out.
- Risks
- Enterprise data architecture choices are fragmented, and budget priorities may be captured by application-layer vendors.
- Amazon / AWSCloud and AI Infrastructure Beneficiary
- Strengths
- Large cloud vendors are still used by enterprises for infrastructure, model deployment, and cloud migration services.
- Weaknesses
- AI spend is expanding from infrastructure to application development, AI applications, and data management, which may reduce pure-infrastructure incremental share.
- Comparison
- Along with Microsoft Azure and Google Cloud, it is part of the hyperscale cloud vendor group.
- Risks
- AI budgets may shift toward application software and data management vendors.
- GoogleCloud and AI Application Beneficiary
- Strengths
- Ranks highly in AI applications and automation vendor selection.
- Weaknesses
- The report provides fewer instances where Google leads decisively relative to Microsoft.
- Comparison
- Ranks behind Microsoft in custom AI application charts.
- Risks
- Weaker enterprise productivity and workflow entry points than Microsoft may limit share gains.
Key data
- Expected 2026 IT Budget Growth3.7%Slightly above 3.6% in 2025, but below the 10-year average of 4.1%.
- Expected Software Spending Growth4.1%The main text says software is the fastest-growing IT area over the next year; chart methodology shows expected 2026 software growth of 3.8%.
- AI/ML Priority Share17.7%In the 1Q26 survey, it ranked highest among CIO spend-growth priority items, versus 16.3% in 4Q25.
- AI/LLM External Vendor PreferenceHyperscale cloud 22%, application software vendors 21%, AI application developers 13%, data management vendors 11%Indicates AI spending is expanding from infrastructure into application, data, and workflow layers.
- Microsoft Automation Application Share42%Charts show Microsoft leading among vendors used to achieve automation operating goals.
- Microsoft Custom AI Application ShareCurrently 32%, 48% in three yearsCharts show enterprises are more inclined to use Microsoft technologies to build customer-facing AI applications.
- Copilot Cost FocusUSD 30 to 35 per user per monthCIOs focus on how to monitor Copilot benefits and justify ongoing subscription economics.
Impact & implications
For the software industry, improving enterprise IT budgets and rising AI priority support medium-term demand for application software, cloud platforms, data management, and automation vendors. In the near term, incremental spending is more likely to concentrate among larger vendors already embedded in enterprise workflows and data environments rather than across the broader IT market. Over the longer term, vendors that can integrate data across systems, orchestrate multi-agent workflows, and reduce interoperability costs are likely to gain share.
Risks
- IT budget growth remains below the long-term average, so overall spending expansion is not aggressive.
- AI/ML is the highest priority, but limited budget adjustment magnitude indicates enterprises remain cautious.
- The buy-versus-build choice may shift due to pricing and interoperability changes, affecting visibility of software-vendor revenue.
- Productivity gains from AI tools such as Copilot are difficult to quantify, which may affect renewals and rollout expansion.
- Cross-platform data integration, system interconnection, and agent orchestration complexity is high, potentially slowing AI automation execution.
- The report contains significant investment bank conflict-of-interest disclosures; investors should assess it alongside the full report and their own circumstances.
What to watch
- Whether 2026 IT budget growth actually reaches the 3.7% level implied by the survey.
- Whether software spending can continue to remain the fastest-growing major IT category.
- Whether AI/ML budgets translate from priority into actual orders and renewals.
- The rollout impact of Microsoft Copilot across admin, marketing and sales, accounting, human resources, and legal workflows.
- Interoperability and pricing strategy of enterprise app platforms such as ServiceNow, Salesforce, and SAP.
- Actual adoption of data platforms like Snowflake, Databricks, Cribl, and Axonius in AI agents and data governance.