How AI is quietly rewriting software delivery

Since 2022, Agentic AI has transformed software delivery. What began with generative AI writing user stories and fixing code has quickly advanced today. Autonomous AI systems are reshaping delivery models and speeding up every stage of development.

From Human-Centricism to Adaptability and Autonomy

The Software delivery model is evolving rapidly from being human-centric to AI assisting humans to Agents autonomously performing critical delivery tasks. Traditional Software delivery processes, despite being well defined, more often than not produce inconsistent outputs for projects with the same archetype, due to the human element involved – the delivery output is dependent on human skills and judgment.

According to Gartner, by 2028, 90% of enterprise software engineers will use AI code assistants (up from just 14% in early 2024), while 33% of enterprise applications will contain agentic AI, and 15% of daily decisions will be made autonomously. This demands automation-first operating models, with human supervision reserved for handling exceptions.

The move is clear: Software delivery is moving from tool-assisted work to AI-driven systems that plan, decide, and act within defined guardrails—building the path toward adaptability and autonomy. As delivery becomes more autonomous, ethical AI and transparency are critical for adoption and long-term success.

Making this shift needs organisational change management. Socialising the platform, processes and upskilling talent to work in the new era are critical for organisational success.

Compounded Speed Through Interconnected Systems

AI excels not only in task speed and accuracy (e.g., code generation, testing, optimisation) but can also execute tasks that are difficult for humans - like reverse engineering codebases spanning millions of lines of code, and performance tuning. This accelerates the time for market of software products, thereby providing businesses with the opportunity to drive growth, cost optimisation and faster realisation of ROI.

Agentic AI enables compounding speed across workflows. Connecting AI across backlog triage, coding, testing, release, and run phases yields multiplicative productivity gains, especially when underpinned by platform engineering. Gartner projects 80% of large engineering organisations will form platform teams by 2026 to standardise best practices, policies, and telemetry, amplifying the impact of every new AI tool or agent in the pipeline.

Organisations on their modernising journey to get their data ready for AI, are seeing timelines for engineering initiatives shrink from 18-24 months to less than 8-12 months. Multi-agent systems now reverse engineer legacy code, document functionality, generate design specs, code new solutions, test, and deploy—becoming the de facto way of working in modern software delivery.

New Core Competencies in System Engineering

Developers' roles are evolving: today’s software engineers must focus less on implementation and more on orchestrating complex, interdependent AI systems. The priority is no longer simply coding but engineering robust, resilient systems where AI delivers targeted outcomes and humans supervise and refine. Strong problem-solving skills to handle AI-driven decision-making exceptions will differentiate top engineers.

Coding, testing, debugging, and documentation skills will be less important as AI can do it better and faster than humans.

Apart from AI/Machine Learning, Cloud Computing, DevOps, key skills software engineers will need to master include model-aware architecture design, agent orchestration, data-product management, AI safety and governance, and continuous validation/observability.

Soft skills such as continuous learning, collaboration and the ability to work in a Human-AI model are critical.

Modern talent models must pivot from “writing code” to “system engineering”—leveraging AI to scale human expertise and maximise impact.

We are just starting - Agentic AI is set to redefine software delivery. Organisations that embrace autonomous, adaptable, and automation-first models will unlock unprecedented speed, quality, and innovation, positioning themselves as leaders in the future of software engineering.

Written By - Sreeja Achuthan, Global Head - Data & Insights Circle, Ascendion

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