Behind the scenes: How the ScriptRunner Migration Suite outperforms generic AI in Cloud migrations

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“I'll bet AI can write that script for you…” 

I'm sure you're hearing this more and more regularly. And maybe, like us, you are curious about whether generic AI tools really hold up not just for writing scripts, but for more intricate tasks too.

While the ScriptRunner Migration Suite is much more than a script converter - it spans the entire ScriptRunner for Jira migration journey - the Migration Agent is a custom-built tool that uses AI to help convert scripts from DC to Cloud.

We tested how the Migration Agent stacks up against generic AI tools. 🕵️ Let’s take a look at the stats:

Benchmark data puts the gap in numbers

The table below uses Pass@k—the industry-standard metric for the probability that an AI model produces at least one functional script within a given number of attempts–to compare the specialist Migration Agent tool from ScriptRunner Migration Suite with a generic AI tool.

The Migration Agent significantly outperforms general-purpose coding agents. Even when public documentation is included in the prompt, the off-the-shelf setups still lack the same migration-specific context that the Migration Agent has built up through analyser output, prompt hardening, field-shape guidance, and failure analysis.

With generic AI, you can't control the information or output it pulls from. Maybe the answer it gives you is from a Stack Overflow answer from 2015? Maybe that solution solved a problem in a different environment on a version that no longer exists. The Migration Agent was created for your environment, for your scripts, for your migration, by the people who understand it best. 

So let’s revisit that statement: “I'll bet AI can write that script… but it probably won’t work first try, and it may not work even after five tries.” 

Every time generic AI gets it wrong, someone has to go back and fix it manually. Across a large migration, that's a significant amount of extra work that lands back on the team. 
 

But why is the Migration Agent better?

Cloud rewrites are full of product-specific factors that generic AI simply lacks the context for. This isn't a copy-paste type of job. 

The Migration Agent is a specialised AI chat agent grounded in product knowledge and validation steps specific to ScriptRunner migrations. The agent researches current API documentation, performs recursive API lookups, validates generated code automatically, and prioritises HAPI over raw REST API calls whenever possible. 

Why this matters for a ScriptRunner Migration 

A migration is so much more than converting scripts, and that's why the ScriptRunner Migration Suite covers every stage of a ScriptRunner migration. First analysing and assessing scripts and configurations for Cloud-readiness, then converting scripts where possible, before deploying scripts to Cloud instances and answering many questions along the way.

This brings benefits to many users:

For ScriptRunner users, the value is simple: lower migration risk and less time wasted correcting errors. 

For Solution Partners and consultants, faster script rewriting means shorter project timelines and more capacity for new work. This allows you to have more confident migration conversations with your clients, as they can set realistic timelines and budgets based on a predictable, automated process. By reducing manual effort, the migration becomes faster and more reliable. 

For technical and operations teams, the value is control. Deterministic analysis, product-aware generation, and a path into staged deployment are all easier to govern than a migration process built from ad-hoc prompts and manual patching.

But does the gap really matter if generic AI will get it right eventually?

Why the gap will matter more over the next year

Many teams initially succeed with general-purpose AI tools because early experiments are simple: borrowed scripts or quick manual checks. The real complexity emerges when migration shifts from exploratory trials to a structured, sustained programme of work. That’s when the harder questions start:

• How do we assess thousands of scripts and configurations quickly?
• Which items are blocked by parity gaps?
• Where do Jira Expressions or Behaviours force a different language target?
• How many manual fixes should we expect at scale?
• How do we move from draft code to tested deployment artefacts?

The ScriptRunner Migration Suite has been built around those questions, while generic AI tools have not. And that gap is the differentiator. It is also the part that teams should pay attention to before a migration plan is built around generic tooling that may well perform in demos, but ultimately pushes too much of the difficult work back onto the delivery team.

Final thought

The ScriptRunner Migration Suite starts with deterministic analysis, uses specialist AI only where AI adds value, measures output against behaviour-preserving benchmarks, and carries the work forward into deployment. That combination is why it looks different from generic AI migration tooling, and why it belongs in a migration toolkit.