Aging data infrastructure is inflating the technical debt that companies need to pay down before they can move to AI.
Research by Pegasystems found that two-thirds of organizations say “legacy systems and applications” are preventing them “fully embracing more modern technologies.” And almost nine out of ten fret that this is crimping their ability to keep pace with agile, innovative competitors.
Almost a quarter of companies had applications that are six to 10 years old, with almost a third having legacy apps that were 11 to 15 years. But those are just striplings, with 7 percent running apps that were over the quarter century to 30 years mark, and 1 percent ‘fessing up to applications more than 50 years old.
And presumably the underlying data structures and architectures are equally vintage. Almost a quarter of respondents said legacy apps meant “data is locked inside of them that we can’t access.”
Don Schuerman, CTO, Pegasystems, said “Part of the challenge is that legacy systems often mean that business logic – rules, workflows, decision points – are entangled into the data systems.
“Storage and data management challenges come up in virtually every customer conversation about automation and AI projects,” he added. “The reality is that most organizations have their data trapped in silos across multiple systems, which creates significant barriers to implementing effective automation or AI solutions.”
(No) viva aging software
This leaves tech leaders tasked with delivering new digital experiences on the front end whilst simultaneously maintaining their backend systems that hold core business data and transactions. This means “trade-offs between being agile or stable because legacy systems slow them down through data replication, batch processing, and siloed architectures.”
Pega’s answer is live data integration which it claims delivers the right data to the right process steps at the right time, managing data requests behind the scenes and adapting easily to new data sources without requiring custom code.
Schuerman said companies need to focus on the processes and experiences they want to transform, and then pull the required data along and into the cloud. “Trying to tackle the data problem outside of specific customer processes and engagement strategies can lead to science projects that run long and never lead to value.” Hence the low percentage of AI projects that have actually made it into production.
Pegasystems unwrapped the research at its PegaWorld conference in Las Vegas, where it also announced its Pega Agentic Process Fabric, which it describes as an “open agentic fabric” to orchestrate “all AI agents and systems”.
The fabric registers AI agents, workflows, and, critically, data across both Pega apps and third party systems. It supports standards including Model Context Protocol and Agent-to-Agent.
Looked at another way, Pega Agentic Process Fabric supersedes the vendor’s Pega Process Fabric, with the new service taking the key capabilities of its predecessor and adding Agentic AI support.
The Fabric switch up coincides with the addition of Agentic AI enhancements to the vendor’s Infinity App Studio. These include an enhance AI developer agent, which works as a “mentor” to devs. It also delivers automated testing and accelerates UX configuration. The new features will appear in the Q3 release of Pega Infinity.
