Legacy modernization has always been the project you could safely put off. The business case was real, but it was never urgent. So, year after year, it lost the budget fight to whatever project had a deadline landing next month.
AI ended that logic. It changed the math on how we evaluate legacy systems because waiting is suddenly the most expensive option on the table. The pressure to change is higher, the actual work is faster and cheaper, and the potential payoff is much larger.
The urgency is higher
Oftentimes AI initiatives eventually stall out because an agent can only scale as far as your underlying systems safely allow it to. If you point an LLM at a process that still relies on manual data entry and disconnected applications running 30-year-old software, the system breaks down. The model itself isn't going to do you much good due to the ancient process underneath it.
This limitation is becoming a major problem given the shifts in enterprise technology. Gartner® highlights that this shift toward autonomous business, driven by AI technology, necessitates the modernization of legacy applications. This transformation is crucial for organizations to remain competitive and capitalize on the emerging autonomous business landscape. By 2030, a significant portion of application modernizations required for transformative autonomous business will be late, impacting market share and GDP. Organizations must act promptly to align their modernization efforts with the autonomous business roadmap.¹
In that kind of environment, applications can't sit around waiting to be called. They have to act on their own. If your systems are running operations, supply chains, or other critical processes but can't make or support a decision independently, your highly automated process stops dead in its tracks.
This is why the old habit of deferring modernization is broken. It used to be about upgrading software because it was "good practice," which meant you could always delay it. Modernizing for autonomous systems is different. If you put off updating the foundation, you put off the entire AI roadmap.
The risk is measurable. Gartner expects 40% of the application modernizations required for transformative autonomous business will be late, resulting in significant shifts in market share and GDP.¹ In 2025, 34% of organizations reported leaving applications as is (for now) because it would involve too much effort and risk to modernize them, up from 16% in 2023.¹ Those ignored systems are often the exact ones your future AI plans need to rely on.
The cost and timeline are lower
Modernization used to mean a multi-year, budget-devouring rewrite. That is why everyone avoided it. But AI has actually solved the most expensive parts of its own onboarding problem.
Today, software can read and untangle legacy code, extract the business logic hidden inside, and generate executable, modern designs from what you already have. The manual analysis that used to drag on for months before anyone wrote a single line of new code is now largely automated.
Look at Pega GenAI Blueprint™ as a practical example. It ingests legacy assets and natural-language requirements, then outputs working process and application designs. You start with a functional draft instead of a blank screen. It doesn't erase the work entirely, but it compresses the phase that used to make projects drag on forever. Historically, legacy projects ran 25% to 50% longer than planned.¹ Cutting out the manual design bottleneck completely changes that timeline.
The takeaway here is simple: Don't wait for the technology to "mature" before you start. The groundwork for intelligent applications is already set, and waiting a year won't make the migration process any clearer.¹ The tools to make this cheaper exist today. Waiting just means falling behind.
The payoff is bigger
The final shift is in the actual business case. Old-school modernization was almost always a "lift-and-shift" job. You moved an application to a new platform and ended up with a carbon copy of the old system, just running in a nicer cloud environment. The return on investment was incredibly thin because the process itself never changed.
A real redesign is different. Instead of just rehosting old habits, you build AI and decision-making directly into the workflow. This turns a modernized application into an active building block for automation rather than a slightly cleaner relic of the past.
That is where you get a real return. The same clean processes that allow AI to function in the first place act as the foundation for the revenue and efficiency gains promised by autonomous business. If you modernize with the future in mind, every application you touch does double duty: It gets rid of your technical debt and advances your AI strategy at the same time.
There is a massive difference between automating a broken process and redesigning a better one before you automate. Only the second option pays off twice.
Where to start
Two steps matter more than anything else.
First, stop planning legacy modernization on its own isolated timeline. Connect it directly to the automation plans your business teams are already building. The order in which you update your systems should match the order in which the business wants to automate.
Second, make the outcomes a shared goal between business units and IT. In 2025, 56% of organizations reported sole IT accountability for core system modernization outcomes.¹ Sole accountability resting with IT rather than across IT and the business isn’t optimal if the entire goal of the project is to enable new business capabilities.
Finally, stop assuming your legacy applications are special. Most of what a heavily customized, decades-old system does can be handled by modern platforms out of the box. Treating every old application like a unique snowflake is exactly how the backlog got this deep in the first place.
Pega Named a Leader in the 2026 Gartner® Magic Quadrant™ for BOAT Platforms. Pega recognized as a Leader for the second year in a row. Read the report →
Pega Named a Leader in The Forrester Wave™: AI Platforms, Q3 2026. Pega received the highest score possible in 8 of 19 evaluation criteria. Read the report →
- Gartner, "The AI Reality That Will Force You to Modernize Your Legacy Applications," Graham Wilkins and Tristan Iles, May 13, 2026, ID G00855308 (licensed for distribution).
- Gartner, Magic Quadrant for Business Orchestration and Automation Technologies, By Saikat Ray, Arthur Villa, Sachin Joshi, Adam Briggs, Tushar Srivastava, Mike Warren, 14 September 2026.
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