The conversation around SYNON modernization used to be this:
“We need to convert our SYNON applications, but the process is slow, risky, and labor-intensive. And then we’re stuck maintaining code that nobody understands.”
That conversation is changing in 2026. AI code assistants have introduced a new variable into the equation.
And it’s significant.
What AI Code Assistants Actually Do (For Legacy Work)
There’s a lot of hype around AI code assistants. Most of it misses the real value for legacy modernization.
The real value: they compress the timeline and reduce the risk of doing work that’s tedious but structured.
SYNON modernization is exactly that kind of work.
Here’s what an AI code assistant can do in the context of SYNON-to-RPG conversion:
Understand the legacy code structure. Feed an AI code assistant your SYNON models and generated RPG code. It reads the structure, identifies patterns, and suggests how to refactor the business logic into clean, modern syntax.
Generate clean conversion scaffolding. Rather than starting from a blank slate, the assistant generates the basic structure of converted code—data structures, procedure definitions, error handling—based on what it learned from your original code.
Accelerate the tedious parts. Data type conversions, field mappings, cross-reference updates—these are the kinds of repetitive tasks that eat 60% of a developer’s time in a modernization project. An AI assistant can draft most of this work, freeing your developers to focus on validation and logic review.
Catch edge cases and suggest improvements. The assistant can flag patterns that suggest bugs or inefficiencies in the original SYNON code, and suggest how to handle them better in the modernized version.
Handle documentation and comments. Self-documenting code matters more in RPG Free Form than in legacy RPG. The assistant can generate meaningful variable names, comments, and documentation that make the converted code maintainable.
The Productivity Impact
According to 2025 Gartner data on legacy modernization, code-to-code conversion tools alone deliver 30% productivity improvement. When AI code assistants are paired with conversion tools, you get an additional 20–40% time savings. That cumulative productivity gain reaches 50–70% faster modernization compared to manual refactoring. More importantly, that speedup comes with reduced risk—because the AI-assisted conversion generates cleaner code faster, leaving more time for testing and validation rather than rushed validation at the end.
In practical terms, manual SYNON modernization takes 10 weeks for one mid-size application with 1 developer full-time. The same application with SYNON conversion plus AI assistant takes 6 weeks with 1 developer plus 20% time from a reviewer. You’re not just faster—you’re faster with better quality because the developer has time to review and test rather than grinding through boilerplate.
Where This Actually Works
AI code assistants are most valuable when you have large application portfolios of 5+ SYNON applications to modernize. The time savings across the portfolio are significant—what took 2 years to modernize manually might take 9–12 months with AI assistance. They shine when you have complex business logic with lots of integrations because the assistant helps track cross-references and integration points, reducing the chance of missing dependencies during conversion. If you need to modernize quickly because a key developer is retiring, AI can compress the timeline from 10 weeks to 6–7 weeks. Younger developers can pair with an AI assistant to learn how legacy SYNON code works and how to modernize it, with the assistant accelerating their learning curve significantly. And when testing burden is high, the assistant can generate comprehensive test cases and validate converted code against original behavior.
A Concrete Example
Let’s say you have a SYNON order entry application with:
- 50+ screens
- Complex business logic around pricing, discounts, and inventory reservations
- Interfaces to an ERP system and WMS
- ~10,000 lines of SYNON-generated RPG
Manual modernization approach:
- Week 1–2: Document the current SYNON structure and logic
- Week 3–4: Build the data structure for the modernized version
- Week 5–7: Convert business logic, screen by screen
- Week 8–9: Test and fix regressions
- Week 10: Deploy
SYNON conversion + AI assistant:
- Day 1–2: Run conversion tools, generate base RPG Free Form code
- Day 3–4: AI assistant reviews generated code, flags edge cases, suggests improvements
- Day 5–7: Developer reviews AI suggestions, validates business logic, runs comprehensive test suite
- Day 8: Deploy
Timeline savings: 50% (10 weeks → 8 days of focused work)
That’s not theoretical. That’s what we’re seeing in 2026.
Why This Matters for Your Hiring Problem
Here’s the thing: SYNON expertise is scarce and aging. Free-format RPG expertise is still scarce, but younger developers are actually interested in learning it.
When you pair AI code assistants with SYNON modernization, you create a window where you can onboard junior developers who’ve never seen SYNON before. The AI assistant helps them understand the old code, and they learn by doing the modernization.
That’s a talent multiplier you didn’t have three years ago.
The Cost Equation
Let’s talk real numbers. Modernizing one mid-size SYNON application:
Manual approach:
- 1 developer, 10 weeks: $30,000 in labor
- Conversion tools: $5,000
- Contingency (debugging, rework): $8,000
- Total: $43,000
Conversion tools + AI assistant:
- 1 developer + AI code assistant, 6 weeks: $18,000
- Conversion tools: $5,000
- AI assistant subscription: $100–200/month (let’s say $600 for the project)
- Contingency: $3,000 (less needed because fewer manual errors)
- Total: $26,600
Savings: $16,400 per application (38% cost reduction)
For a portfolio of 5 SYNON applications, you’re looking at $80,000+ in savings.
What This Doesn’t Mean
I want to be clear: AI code assistants are not a replacement for developers. They’re a force multiplier.
You still need people who understand SYNON, who understand the business logic, and who can validate that the conversion is correct. The AI assistant handles the tedious parts; your team handles the judgment calls.
Also: this is not a “fully automated” conversion where you push a button and walk away. That’s not how legacy modernization works. What it is is a dramatic acceleration of a process that was already possible, with better quality and reduced risk.
The Decision Point
If you’re modernizing SYNON applications, you have two choices:
- Do it the old way: hire specialized SYNON experts, spend 10+ weeks per application, hope your knowledge doesn’t walk out the door when they retire.
- Do it the new way: use conversion tools + AI code assistants, compress the timeline, reduce the cost, and position your team for the next phase of modernization.
The tools have matured. The business case is clear. The adoption curve is steep in 2026.
The question is not whether to use AI code assistants for SYNON modernization. The question is: how fast can you get started?
If you’re managing SYNON applications and wondering how AI-assisted modernization could work for your portfolio, let’s talk. We’ll help you assess your applications, model the productivity gains, and design a modernization approach that fits your timeline and budget.