Explore legacy risk, technology investment, delivery oversight, and the use of AI under enterprise governance.
Enterprises are deploying AI agents faster than they can govern them. BCG argues for one governance layer above every platform, covering identity, an agent registry, runtime policy and pre-approved deployment paths, so teams can ship compliant agents in a day rather than weeks.
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A modernisation is usually planned as a technology project. Whether it creates value depends on the people who know the old system, run it every day and will have to trust the new one.
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It is easy to spend on AI without being able to show what it returned. Value comes from changing how critical work gets done, not from adopting tools, and it has to be planned and measured like any other investment.
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Many organisations have tried AI. Fewer rely on it for everyday work. The difference is rarely the model. It is whether the task, the rules and the accountability were defined before anything was built.
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New research finds large enterprises spend 28% of their software budgets on vendor-driven upgrades they would not have chosen. The root cause is not the vendor. It is how little most organisations can see of what they run.
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A preliminary review of four legacy modernisations found time and cost around 70% below a commercial estimate for traditional delivery. The sample is small, but the pattern held on every project.
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AI has made writing code dramatically faster, but not delivering working systems. The human work before and after coding still decides the outcome, and that matters for anyone planning a modernisation.
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Paradym Next replaced an ageing Java 8 and Spring Boot monolith with a serverless platform, built while the original system kept running and without losing years of embedded business logic.
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Professional software acquirers have historically avoided large-scale technology modernisation initiatives. Legacy technology stacks have been treated as operational constraints to be managed, rather than strategic liabilities to be eliminated.
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In an outsourced modernisation, the incumbent engineering team is both the most valuable asset and the biggest risk. They hold knowledge the code does not, and they are easily unsettled when work moves to a provider.
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While most executives recognise the direct costs of technical debt—maintenance expenses and sluggish development—the truly dangerous costs remain hidden, silently eroding your company’s foundations.
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For decades, software development has followed a relatively stable trajectory. That paradigm is now collapsing.
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Is your business being held back by outdated legacy systems? You’re not alone. Many successful SaaS companies find themselves trapped by the very software that once drove their growth.
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In the rapidly evolving tech acquisition landscape, a new challenge has emerged for due diligence teams: evaluating the quality, security, and sustainability of AI-generated code.
Read the articleof developers’ time is spent building applications. The rest goes on everything around the code.
IDC, How Do Software Developers Spend Their Time?, Feb 2025lost every week by half of developers to inefficiencies. Finding information is the top cause.
Atlassian, State of Developer Experience 2025, 3,500 developers and managersof IT leaders say the time, money and effort spent maintaining legacy applications could be used more productively.
Pega and Savanta, survey of 500+ IT decision makers, Oct 2025We use only essential cookies, and no tracking. Cookie policy
