Organizations all over the world, across every sector, and of all sizes are united by a common goal: to move faster, streamline operations, cut out the noise of systems, and get straight to the heart of work. To break free from the legacy technologies that hold them back.
If only it were so simple. Legacy systems have long posed a devious problem: Enterprises rely on them to perform essential activities, but they’re also held captive by them and the bygone technologies they utilize. Imagine you want to convert a failing combustion vehicle to an electric drivetrain, but without taking the car off the road.
There’s a temptation to kick the can down the road and keep using the systems and processes you have in place. Maybe the mainframe running your business applications is old, but it’s still running. This is a flawed mindset for two reasons:
- Legacy systems won’t work forever, and as they age, they decay – upkeep becomes more expensive and time-intensive, and gaps in functionality pose mission-critical risks.
- New technologies increasingly call for more advanced and resilient underpinnings. Realizing the full benefits of AI and automation, for example, is impossible with an outdated platform supporting them.
But the history of legacy transformation projects has not always inspired confidence. Some 70% of such undertakings fail as IT teams lack the resourcing and timelines required to finish the job while business teams press for a fast solution. As a result there is no migration to new, better systems; there is no legacy retirement; and there is no appetite for another round of modernization to accomplish those objectives.
Or at least, that was the case.
Now, generative AI can unstick the legacy transformation journey, enabling unprecedented speed, efficiency, and thoroughness.
Legacy systems represent outdated technological infrastructure that organizations continue to maintain despite their obsolescence. These systems, which can include outdated hardware, software applications, and programming languages, pose significant challenges for enterprises.
Research by Forrester and MongoDB found that 60% of CTOs surveyed describe their legacy tech stack as too costly and inadequate for modern applications. Security vulnerabilities present another critical concern, exemplified by the 2017 WannaCry attack that exploited legacy system weaknesses, affecting over 200,000 computers across 150 countries. Additionally, integration limitations with modern cloud services and mobile applications create operational bottlenecks, while the scarcity of qualified maintenance professionals is an increasing concern.
The complexity of legacy transformation stems from several interconnected factors. Legacy systems often form intricate webs of dependencies, where changes to one component can trigger unexpected ripple effects throughout the organization. Business logic tied to legacy applications can be hard to uncover or replicate, lengthening the process of discovery and execution even more.
Data migration presents another significant hurdle, as historical data often exists in outdated formats that don't easily translate to modern systems. These technical challenges are often compounded by human factors, including resistance to change and resource constraints. What’s more, many legacy transformation projects leave the original application or system intact, instead of retiring it once and for all.
So what’s different now?
Legacy systems remain an obstruction to agility, innovation, and progress. But AI makes the path to legacy retirement and transformation far more navigable.
In the discussion around the ways AI will revolutionize how work gets done, its impact on process transformation has gone somewhat overlooked. But this capability might be the most impactful application for today’s organizations. It simplifies, automates, and accelerates the work of requirements gathering, data ingestion, process design iteration, and even data migration, revolutionizing the way legacy transformation happens.
Here's what the new process for AI-led transformation makes possible for the enterprise:
- Near-immediate fixes to broken processes in the form of reimagined applications and workflows = Short-term wins
- Pave the way toward legacy system retirement, resulting in less upkeep, more bandwidth, and higher resiliency = Long-term sustained excellence
- Every organization is trying to break away from legacy systems and applications; some will fail, some will get there in decades, and some will succeed fast using an AI-led approach = Competitive advantage
- Future state: Open the door to agentic AI and automation tools that require a modern foundation to reach peak output = Embrace the autonomous enterprise
Once you’ve migrated processes, workflows, and applications away from legacy systems, that also means you can retire those systems and pivot to the cloud. Moving data from a mainframe to a cloud environment is easier than ever with gen AI, which can map old structures, objects, and fields onto an auto-generated virtualization layer to power workflows.
This is a gamechanger in cloud migration and transformation, where rationalizing and refactoring data has traditionally been a massive stumbling block that devours IT bandwidth. Decoupling process data from on-prem legacy structures means evolving your business from a monolithic tangle of interdependent rules and logic to a streamlined, platform-oriented structure built around the customer journey.
Pega is THE ENTERPRISE TRANSFORMATION company. We help organizations progress on the path to becoming an autonomous enterprise by breaking free from legacy, automating the customer journey, and personalizing every interaction.
Use Pega GenAI to reimagine any workflow application in minutes with no cost or commitment by going to www.pega.com/blueprint.