IT & Software: AI-Driven and AI-Native Development Accelerate IT Service Company Efficiency: AI-Driven Margin Improvement Begins

Research evidence excerpt

IT & Software: AI-Driven and AI-Native Development Accelerate IT Service Company Efficiency: AI-Driven Margin Improvement Begins

FoundationM

Top-Tier Companies Accelerating Company-Wide AI-Driven Development at

Increasing Pace: Various Case Studies Illustrate Future of IT and Software

Industry

• The four leading SIers apply AI-driven development across the entire software development lifecycle, accelerating the transformation of the traditional “person-

month × effort” model.

 Fujitsu demonstrated a 100-fold productivity gain and is shifting to value-based pricing.

 NEC aims to make BluStellar fully AI-enabled and has demonstrated greater efficiency in system development.

 NRI advances a roadmap to achieve a 100% adoption rate for AI-driven development by FY2028 and a 100% deployment rate for fully autonomous AI

agents by FY2030, while also promoting an LLM specialized for financial services.

 NTT Data targets a 70% reduction in development processes by 2030 through a three-stage maturity model.

• The common theme is an irreversible structural shift that places AI at the center of development and changes the human role from “implementer” to “supervisor of

AI and accountable decision-maker.”

Exhibit 2: Changes in Engineer Roles

Traditional Role New Role in the AI Era Shift in Required Skills

Programming → Ability to articulate Coder AI Prompt Engineer

requirements in natural language

Test execution → Quality judgment of AI Unit Tester AI Reviewer

outputs

Writing design documents → AI-Ready SE (System Engineer) AI Architect

Engineering design

Process management → Integration & PM (Project Manager) AI Orchestrator

optimization of AI agents

Subcontracted Programmer (Risk of reduction / elimination) Routine coding → Replaced by AI

Source: Morgan Stanley Research