AI in Software Development 2026: Over 80% of Devs Use AI and the Job Market Shifts

A RunSafe Security survey on embedded software development reveals that more than 80% of respondents already use AI for tasks like code generation, testing, or documentation, and 83% say they have deployed AI-generated code into production. But this shift brings profound consequences for the job market and required skills.

Current State: Omnipresent AI

AI-generated code already runs in critical systems:

• Power grids
• Medical equipment
• Vehicles
• Industrial plants

This isn’t the future—it’s the present. And it raises serious questions about security and governance.

The Job Market Transforms

Pressure on Entry-Level Profiles

The data gathered by IEEE Spectrum is stark:

Metric	Change
Entry-level hiring at the 15 biggest tech firms (SignalFire)	-25% from 2023 to 2024
U.S. “programmer” employment (BLS)	-27.5% from 2023 to 2025
U.S. “software developer” employment (BLS)	-0.3% in the same period
Job market rating for new graduates (NACE)	Most pessimistic since 2020

Hugo Malan from Kelly Services describes it as “a tectonic shift”.

Not Replacement, Realignment

AI agents don’t replace workers 1:1. What changes is:

• Which roles are needed
• What those roles look like

While programmer employment falls, roles such as information security analyst and AI engineer are growing.

Skills That Matter in 2026

Simply knowing how to write code is no longer enough. What employers and the sources consulted highlight:

1. Higher-order thinking and knowledge of the software development life cycle
2. System design and architecture
3. Code review and quality judgment
4. AI tool proficiency (now an unwritten expectation)
5. Problem solving and communication

The Marginal Cost of Code Dropped

The main impact of LLM tooling:

The marginal cost (in time and dollars) of producing high-quality code has gone down significantly

But producing code is only part of the job of software engineering. According to Ben Congdon, bottlenecks shift to:

• Code review
• Architecture and abstractions
• Systems design decisions
• CI infrastructure quality

Tools Heading Into 2026

Cursor Debug Mode

Cursor 2.2 (December 2025) introduced a mode that lets AI agents work with the runtime state of a program:

• Agent instruments the code with logging
• Captures execution while the user reproduces the bug
• Analyzes the logs to propose a fix

Z.ai’s GLM-4.7

Open-source model released in December 2025, focused on:

• Long-running task execution
• Stable tool calling
• Multi-step reasoning

Security Risks

Dark Reading warns that in 2026, as more coders adopt AI agents, security pitfalls lurk:

• The quality and security of generated code varies significantly
• A rush to adopt agentic AI can lead to deploying insecure code
• The development pipeline and security need to be prioritized

Recommendations

✓ Review all AI-generated code
✓ Validate suggested dependencies
✓ Implement automated security pipelines
✓ Keep humans in the loop for critical decisions

The Year of Agentic CLI

According to The New Stack, 2025 was the breakout year for agentic AI tools, especially the Agentic CLI. 2026 will be about securing that ground:

Developers don’t need to be convinced about what LLMs can achieve, but they do need to be convinced that the available products can be trusted to support their workflows over time.

Implications for Businesses

For Development Teams

1. Invest in upskilling: Design, architecture, security
2. Redefine junior roles: More mentorship, less mechanical coding
3. Establish AI policies: Which tools, how to use them

For Technical Leaders

1. Evaluate real productivity: Not just code velocity
2. Monitor quality: More code doesn’t mean better code
3. Plan the transition: Change is gradual but inevitable

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