The 18th State of Agile Report – Key Insights

The 18th Edition of the State of Agile Report, published by Digital.ai, outlines a critical turning point for Agile practices as they intersect with macroeconomic pressures, data management challenges and the rapid expansion of Artificial Intelligence (AI). 25 years after the creation of the Agile Manifesto, modern enterprises are shifting away from rigid, framework-led approaches toward highly adaptive, custom operating models. While software delivery infrastructure and tool visibility have dramatically improved, organizations continue to face a measurement crisis and shallow overall Agile maturity. Simultaneously, AI is rapidly moving from an experimental side project into the core of software development and planning, creating a strong need for robust governance alongside technological automation.

Key Insights

Agile Adoption and Investment Trends

• Shallow Maturity: Only 13% of respondents report that Agile is deeply embedded across business, technology, and supporting functions with work aligned to strategic outcomes.
• Horizontal Plateau: 42% of practitioners describe their organization’s Agile culture as “better than nothing, but could be more effective,” indicating horizontal scaling without depth.
• Funding Adjustments: Over the past 12–24 months, 41% of organizations increased their scaling investments, 27% maintained flat funding, and 24% decreased their investments.
• Framework De-escalation: A combined 74% of organizations now utilize hybrid or homegrown approaches (up from 50% in Year 16 and 52% in Year 17), moving away from strict pure play Agile frameworks. Specifically, 48% rely on a blended/hybrid model and 26% use a homegrown framework.
• Top Investment Drivers: The leading external and business forces affecting investments and role shifts include cost control/efficiency focus (79%), leadership and structural reforms (78%), customer expectations for reliability and security (78%), and demands for faster innovation (77%).

Shifting Roles and Management Disconnects

• Strategic Expansion vs. Coaching Retreat: 29% of Agile practitioners are now held accountable for tying work directly to business outcomes, while 26% are doing less framework coaching and evangelism.
• Leadership Vacuum: Only 15% of respondents state that business and executive leaders are actively involved in shaping and sustaining Agile practices across the organization. Instead, 33% report Agile is treated strictly as a delivery function, and 24% state it is driven bottom-up with minimal executive oversight.
• The Product Management Gap: Less than half (49%) of respondents agree that Product Managers can effectively manage the full product delivery pipeline and accurately measure business or customer value.

The Visibility and Quality Paradox

• High Tool Visibility: 55% have complete visibility across the software development lifecycle (SDLC). Furthermore, 64% of Agile teams have visibility into the DevOps pipeline, and 64% of DevOps teams have insight into development planning.
• Integration Progress: 65% agree that Enterprise Agile planning tools successfully align their teams, and 53% report that their Agile and DevOps toolchains are well-integrated to minimize manual work.
• Worsening Outcomes: Despite pipeline automation and tool integration, 63% of companies state they are actively struggling to deliver reliable, high-quality software—marking a 12-point increase since the prior report.
• Operational Friction: 53% of organizations struggle with prioritizing the right work, and 52% find it difficult to track real business impact.

Data Gaps and Measurement Maturity

• Success Metrics: Customer satisfaction or retention remains the primary indicator used to measure Agile success at 52%, followed by cost reduction/efficiency at 40%.
• Reliance on Manual Analytics: 44% of organizations still rely on manual analysis (status reports, spreadsheets, and slide decks) for half or more of their delivery insights.
• Modern Pipeline Adoption: Only 22% use ETL pipelines into business intelligence tools at scale, and just 6% utilize AI-powered analytics to surface predictive trends and insights. Meanwhile, 21% of practitioners outright lack trust in their delivery data.

AI and Agentic Automation in Agile

• Rapid Tool Expansion: 41% of organizations are actively exploring or implementing AI tools across teams or embedding them into workflows, up from roughly one-third in the previous report.
• Governance Deficit: While 61% feel prepared to responsibly adopt AI, only 49% have established clear guidelines or guardrails for how AI is utilized across teams.
• Current AI Tool Usage: Among those adopting AI, 65% utilize general-purpose LLMs manually, 57% deploy AI code assistants (e.g., GitHub Copilot), 43% use AI copilots integrated directly into delivery tools, and 43% utilize custom in-house AI assistants.
• Primary Drivers for AI: Teams utilize AI to save time or reduce manual effort (77%), accelerate planning/development tasks (41%), and improve software quality (35%).
• Agentic AI Frontier: 28% of AI users are already experimenting with or adopting Agentic AI—systems capable of autonomous decision-making and cross-tool coordination. The primary active test areas for Agentic AI are workflow execution across tools (39%), risk detection/response (27%), and compliance enforcement governance (24%).
• Barriers to AI Adoption: Security, privacy, or compliance concerns are cited as the top barrier to AI deployment at 61%, followed by a lack of skills or training at 46%, and a lack of trust/confidence in AI outputs at 35%.
• Optimistic Outlook: Software professionals lean toward a collaborative outlook rather than fear of displacement; 28% believe AI will change how they work but not replace what they do, and 26% state it will directly enhance their productivity and decision-making.

Conclusion

The 18th State of Agile Report highlights that modern agility is undergoing a necessary evolution from “doing Agile” through compliance-driven ceremonies to “being Agile” via outcome-oriented operating models. Faced with tightening economic scrutiny, teams are dismantling rigid structures in favor of custom, hybrid models that blend Agile, DevOps, and automation. However, accelerating pipelines with AI and automation will only widen existing organizational flaws unless foundational data trust and leadership alignment are corrected first. Ultimately, the enterprises that thrive in this next era will be those that establish rigorous governance, bridge the metric gap between delivery outputs and business outcomes, and treat AI not as a siloed task patch, but as an accountable orchestrator of strategic flow.

You can check out the full report here.