Gartner’s latest forecast and Deloitte’s 2026 Global Software Industry Outlook examine how AI is changing software engineering organizations, software development, and software products.
While AI coding assistants have received much of the attention, the research shows that AI is becoming part of everyday software engineering and changing how organizations build and maintain software.
Organizations are integrating AI into engineering workflows while redefining how software teams operate.
Routine development tasks are moving to AI, giving engineers more time to focus on architecture and governance. AI-native companies continue introducing new products and delivery models, prompting established software vendors to adapt engineering practices, talent development, and product roadmaps.
Why It Matters: Now that AI is becoming part of everyday software engineering, organizations are finding that success depends less on adopting AI tools and more on building engineering practices that allow people and AI to work together effectively. The research also suggests that organizations gaining the most value from AI are treating it as part of everyday software delivery instead of a standalone capability. Integrating AI into engineering workflows, workforce development, and product planning can help improve execution while supporting long-term growth.
- Software Delivery: Deloitte expects AI to influence the entire development lifecycle. Instead of serving only as a coding assistant, AI is helping teams plan projects, automate testing, and support deployment. Organizations that redesign engineering workflows around AI could realize productivity gains of 30% to 35%, improve software quality, shorten release cycles, and reduce technical debt.
- Team Structure: Gartner predicts that by 2029, 60% of organizations will use AI-augmented “tiny teams,” up from 15% today. The goal is to create teams that can deliver more work with fewer handoffs. AI handles repetitive development work, allowing engineers to focus on innovation and customer outcomes. Success depends on how work is coordinated across people and AI.
- Engineering Talent: Engineers are spending less time writing routine code and more time reviewing AI-generated work, designing systems, and strengthening governance. Gartner cautions against reducing junior hiring because doing so can weaken future leadership pipelines and institutional knowledge. Deloitte also stresses continuous AI training so engineering teams can continue building expertise as AI capabilities mature.
- AI-Powered Products: Deloitte expects generative AI and agentic AI to become embedded in software offerings, opening new opportunities to differentiate products. AI-native companies continue introducing specialized products while established vendors invest in AI platforms and new capabilities to remain competitive.
- Organizational Execution: The reports make it clear that AI alone will not determine outcomes. Organizations that update engineering practices, invest in talent, and establish effective governance are more likely to improve software delivery while adapting to changing business needs.
2026 Global Software Industry Outlook – Deloitte
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