AI ambition often runs aground on legacy reality

AI ambition often runs aground on legacy reality. Across the Middle East and the Global South, many enterprises are eager to move from pilots to production-grade AI, but their operating core is still constrained by mainframes, COBOL estates, brittle integrations and decades of undocumented business logic. In that environment, AI cannot simply be layered on top. Modernization becomes the prerequisite for scale.

That is why the fastest route to enterprise readiness is not treating modernization as a separate IT program, but as the foundation for agentic AI. Before organizations can deploy intelligent agents across critical workflows, they need trusted context, modern architectures and a clear understanding of how their systems actually work. Publicis Sapient helps clients build that foundation with Sapient Slingshot, then accelerate into enterprise AI use cases with Sapient Bodhi.

Legacy systems still run mission-critical operations in banking, healthcare, energy, retail and the public sector. They contain the logic that powers claims processing, payments, pricing, inventory, customer records and compliance workflows. But they also create drag. They are costly to maintain, difficult to change and often understood by only a shrinking group of specialists. Years of patches, workarounds and partial documentation leave organizations dependent on fragile systems that limit innovation.

For leaders pursuing AI, this creates a practical challenge. Agentic systems depend on accurate business context, connected data, clear process logic and reliable integration points. If the enterprise core is opaque or unstable, AI initiatives slow down, risk increases and value remains trapped in pilots. Modernization, then, is not a back-office exercise. It is how organizations make their business usable by AI.

Sapient Slingshot is designed to modernize and build core enterprise software at scale. It uses AI to read, interpret and extract business rules from legacy environments, helping organizations preserve decades of institutional knowledge while reducing modernization risk. Rather than forcing teams to reconstruct intent manually from aging codebases, Slingshot turns existing systems into verified specifications with full traceability.

This matters especially in environments where business logic is buried across mainframe applications, batch feeds, copybooks, subroutines and point-to-point integrations. Slingshot can generate program overviews, flowcharts, field mappings, specifications, user stories and test assets, creating a clearer path from current state to target architecture. Its Enterprise Context Graph provides a living map of the software estate, connecting code, architecture and data to business rules, operational dependencies and human knowledge. That gives organizations more than migration speed. It gives them an enterprise context layer they can reuse long after the first modernization milestone is complete.

The results are measurable. Sapient Slingshot delivers up to 99% code-to-spec accuracy and can accelerate delivery timelines by as much as 3x. Publicis Sapient has also demonstrated 75% faster modernization, 50% cost savings and up to 80–100% test coverage in AI-enabled delivery environments. For enterprises facing years of technical debt, these gains can turn stalled transformation programs into executable roadmaps.

The challenge in legacy transformation is not just rewriting code. It is protecting the business value embedded in those systems while creating a modern, cloud-ready architecture that can evolve. Publicis Sapient uses Slingshot to help clients extract what matters most: rules, dependencies, specifications and operational knowledge. From there, teams can move with greater confidence into migration, re-platforming and software delivery.

In healthcare, Publicis Sapient used Sapient Slingshot to help modernize a leading healthcare company’s claims platform, transforming legacy COBOL into maintainable Java and React, auto-generating specs and test cases, and enabling cloud-native deployment. The effort modernized more than 10,000 screens and delivered 3x faster migration speed, with significant cost reduction.

In financial services, Publicis Sapient helped a major bank modernize complex COBOL-based mainframe programs supporting financial and payments operations. By analyzing hundreds of files and nearly half a million lines of code, the team accelerated code-to-spec work, improved specification accuracy and increased migration speed. What would have been a slow, manual discovery effort became a much faster, more reliable path to modern architecture.

In energy, Slingshot helped rebuild a critical decades-old application in just 48 hours, accelerating code generation and testing while removing long-term operational risk. In retail, it standardized code generation and built-in testing during re-platforming, improving consistency, reducing rework and lowering development effort.

Across these outcomes, the pattern is clear: AI-led modernization reduces dependency on tribal knowledge, lowers transformation risk and creates reusable artifacts that support faster delivery.

Once modernization creates a stable, traceable and cloud-ready foundation, organizations can move more confidently into AI use case development. This is where Sapient Bodhi extends the value of modernization.

Bodhi is Publicis Sapient’s enterprise-scale agentic AI platform, designed to help organizations develop, deploy and scale AI solutions and products with the orchestration, governance and context required for real business workflows. It helps enterprises simplify complex workflows, deploy AI rapidly, improve decision-making and maintain security and compliance while scaling solutions across the organization.

The connection between Slingshot and Bodhi is strategic. Slingshot unlocks the business context trapped inside legacy systems. Bodhi uses enterprise context to power AI agents and workflows that can operate with greater relevance, control and value. Instead of building isolated proofs of concept on fragmented data, organizations can move from modernization into enterprise AI on stronger footing.

This approach is especially important for markets where growth, resilience and sovereignty matter. In the UAE and across the Global South, enterprises and governments are moving from AI experimentation toward deployment at scale. Publicis Sapient’s AI platforms are built to help organizations modernize legacy technology, build agentic solutions and automate operations in ways that are specific to their industries, environments and business goals.

Publicis Sapient helps clients move through this journey in a connected way: identify where AI can add value, assess readiness, modernize the technical core, reduce delivery risk and then scale solutions through a more sustainable operating model. That end-to-end approach is grounded in deep expertise across strategy, product, experience, engineering, data and AI.

For enterprises burdened by technical debt, the message is simple: the road to agentic AI does not begin after modernization. It begins with modernization. By extracting specifications, preserving institutional knowledge and accelerating migration into modern architectures, Sapient Slingshot turns legacy estates into a launchpad. With Sapient Bodhi, that foundation becomes the basis for reusable enterprise context, faster AI delivery and lower-risk transformation.

AI at enterprise scale requires more than models. It requires systems that are understood, connected and ready to change. Publicis Sapient helps organizations build exactly that—so they can move from fragmented systems and technical debt to operational readiness, measurable outcomes and AI that delivers.

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