Centric Says Its New AI-Driven Process Can Slash App Modernization Time — Here’s What That Means

Centric’s fast promise and why it landed in front of buyers

Centric Consulting this week rolled out a new pitch: use its AI-augmented development framework to modernize business applications roughly four times faster than conventional approaches. The firm says the change is immediate and repeatable — a shift meant to cut long, expensive modernization projects down to a fraction of their former timelines.

The announcement frames the move as a productized blend of machine intelligence and Centric’s consulting teams. The company positions the framework as a practical fix for organizations that have been stuck with aging apps and long migration timelines. For IT leaders, the promise is simple: less time in project limbo, faster delivery of new features, and lower program overhead.

What Centric says happens inside its new framework

At the center of Centric’s message is a hybrid model that pairs automated code work with hands-on engineering and program management. The release describes an “agentic AI” layer that can generate code, suggest refactors, automate repetitive testing and create migration plans, while human developers and architects supervise, validate and integrate the results.

Centric’s statement highlights three practical pieces: automated discovery of legacy code and dependencies, AI-assisted code modernization and accelerated testing and integration. The company frames the process as a workflow: the AI speeds up repeatable, time-consuming steps and people handle judgment-heavy tasks like design decisions, security checks and stakeholder coordination.

To back the headline figure, Centric points to aggregated internal measurements that compare its new framework to past engagements. The firm uses the term “80% faster” to describe a typical reduction in elapsed project time when the framework is applied versus earlier, more manual approaches.

What the company’s evidence shows — and what it doesn’t

The announcement includes references to client examples and internal benchmarks to support the speed claim. In several of the cited case examples, Centric says teams that used the framework moved from assessment to production far quicker than comparable projects run previously by the same clients or by Centric in the past.

Those case notes are useful as directional proof: they show the framework can cut waste and accelerate clearly automatable parts of work. But the release leaves several important validation questions open. It does not provide a full methodology for how the “80%” number was calculated across projects, it offers only a handful of client snapshots rather than a large, independent dataset, and it does not include third-party audits or peer-reviewed benchmarking results.

In short, the evidence in the release suggests real gains on routine tasks, but it does not yet show the full range of outcomes you would need to judge the approach everywhere — for instance in highly regulated systems, complex integrations, or legacy environments with poor documentation.

Why speed matters today — and where Centric fits in the market

Application modernization is one of the busiest parts of enterprise IT. Companies want to move old systems off end-of-life platforms, containerize services, improve security, and unlock cloud economics. The longer each project takes, the longer business units operate around limitations and the higher the cost of keeping legacy gear running.

That pressure has created a crowded market: global consulting firms and offshore providers sell migration programs, while software vendors and platform specialists offer automation tools and low-code platforms. On top of that, the arrival of AI-powered coding helpers from major cloud and tool vendors has opened a new front — teams can now automate code generation, testing and refactoring at scale.

Centric’s offering sits between those worlds. It is not a pure software tool nor a traditional, fully manual consulting engagement. Instead, it packages automation plus consulting people into a repeatable service. For buyers who want speed but still need customization and governance, that middle ground is attractive — provided the quality and risk controls hold up.

Where to be cautious: quality, risk and marketing stretches

There are a few clear reasons to be cautious about any fast modernization claim. First, speed and quality can trade off. AI can accelerate routine coding and test tasks, but subtle logic errors, architectural mismatches or security holes can remain if human oversight is light or rushed.

Second, agentic AI — systems designed to take multi-step actions — can make mistakes or produce outputs that look plausible but are wrong. That raises questions about how Centric validates AI suggestions, how it prevents downstream defects, and how it manages regulatory and compliance checks.

Third, measuring “project time” can be done in different ways. Is the company measuring calendar days from kickoff to production, pure engineering hours saved, or just the time spent on certain phases? Without a clear, repeatable measurement approach, headline percentages are hard to compare across vendors or projects.

Practical takeaways and what to watch next

Centric’s announcement is meaningful because it reflects how mainstream consulting firms are now combining AI automation with human teams to speed delivery. For many organizations, that hybrid model will be a useful path to modernize faster than traditional programs allow.

But the claim of “80% faster” needs fuller context. The most useful next disclosures from Centric would include a clear explanation of the metric (what exactly is being timed), a larger set of client outcomes with before-and-after detail, and independent or third-party benchmarks that test the framework across different types of legacy systems and regulatory scenarios.

Buyers and observers should also watch for practical indicators of quality: defect rates in production after modernization, security and compliance audit results, and whether the firm publishes standardized case studies with reproducible baselines. Those will show whether the speed gains come with acceptable trade-offs.

For now, Centric’s announcement is a credible signal that AI-augmented modernization is moving from pilot projects into commercial services. It looks promising for routine, well-understood migrations — but it leaves open questions for more complex or regulated work until broader, verifiable evidence arrives.

Sources

• prnewswire.com