Benefits of Modernizing Applications

AI field note: Modernization is one of the most underappreciated forces for innovation (Southwest Airlines shows us why). When legacy systems finally get updated, two big things happen: 1️⃣ You can start improving services that were effectively frozen in time. 2️⃣ The cost and complexity of running those services drops—freeing up time, money, and focus for what’s next. But for a long time, modernization just wasn’t worth it. The juice wasn’t worth the squeeze. Projects kicked off with long planning cycles, manual analysis, and a lot of upfront investment—often without a clear path to value. That’s starting to change. AI is shifting what’s possible. It can help teams understand legacy code faster, accelerate planning, and reduce the rework that usually slows things down. With that, modernization becomes more viable, more targeted, and more focused on outcomes. It’s not just about updating systems—it’s about unlocking capacity, reducing friction, and making space for the next wave of innovation. Take Southwest Airlines. They needed to modernize their crew leave management system—a critical platform for scheduling, time off, and operations. Over time, the system had become harder to update. Technical debt made it difficult to plan changes, and documentation was limited. Each update required hours of manual analysis just to understand what the system was doing—slowing delivery and tying up valuable resources. But the pressure to modernize was growing. As operations evolved and employee needs changed, the system needed to be more flexible, more reliable, and easier to maintain. PwC partnered with Southwest to take a different approach. Using GenAI, we analyzed the legacy code and generated user stories—effectively mapping the system’s behavior and identifying what needed to change. That work: ⚡️ Cut backlog creation time by 50% 🌟 Produced user stories accepted 90% of the time without major rework 💫 Freed up 200+ hours across teams More importantly, it gave the team clarity and momentum—turning a slow, manual planning process into a faster, more focused path forward. Less time untangling the past. More time building what’s next—for their teams and their travelers. There’s never been a better time to modernize.

The Quantum Leap From Legacy Systems to Cloud-Native During a chilly autumn morning when I met with the leadership team of one of our longstanding clients. They spoke with a mix of pride and frustration about their legacy systems—once the engine of their success, now a heavy anchor in a fast-paced digital world. Their story resonated deeply with me. It wasn’t just about technology failing to keep pace; it was about the human struggle to adapt in an ever-changing landscape. Recent research reinforces this urgency. Gartner’s 2024 forecast predicts that by 2025, over 80% of enterprise workloads will operate on cloud-native platforms. This shift promises not only faster deployment cycles and enhanced scalability but also a reduction in operational costs by as much as 30%. For companies burdened by outdated systems, these figures offer hope and a clear path forward. At Devsinc, we embarked on our own journey towards cloud-native solutions driven by our commitment to our clients’ futures. I recall countless late nights spent brainstorming and re-engineering our processes. We embraced agile methodologies, established continuous integration and delivery pipelines, and reimagined our infrastructure to unlock new levels of efficiency. One memorable project involved a major retail client whose legacy systems were stifling innovation. After migrating to a cloud-native platform, their time-to-market was reduced by 40%, and defect rates dropped by 35% within just six months. Their renewed agility not only improved customer satisfaction but also reinvigorated their competitive edge. Yet, this transformation isn’t solely about technology; it’s about people. Shifting from legacy systems to cloud-native architectures means rethinking workflows, empowering teams, and fostering a culture of continuous improvement. I’ve seen firsthand how this change can inspire creativity and resilience, transforming operational challenges into opportunities for growth. Embracing cloud-native is more than a technical upgrade—it’s a lifeline in today’s digital era. It offers the promise of agility, responsiveness, and long-term success. At Devsinc, we are dedicated to guiding our clients through this evolution with empathy, expertise, and unwavering support. The journey from legacy to cloud-native is challenging, but every step forward builds a future where technology truly serves us all. Let’s embrace this change together and create a landscape where innovation and human ingenuity drive us to new heights.

#Cloud + #AI: The CxO Playbook for Mainframe Modernization Despite all the innovation buzz, IBM reports that ~70% of global business transactions (by value) still run on mainframes. Mainframes are the dependable backbone in banking, insurance, healthcare, government, and logistics, to name a few. But now dependability isn’t enough in an era of macroeconomic volatility, accelerated tech disruptions and everchanging customer expectations— it’s time to modernize mainframes. As competition increases, new ecosystem collaborations form and businesses evolve, mainframe modernization needs to be become a C-suite imperative. Three Options to Mainframe Modernization 1) Review Contracts: to identify cost-savings, negotiate terms, reduce OpEx 2) Optimize on the Mainframe: continue to drive efficiency on legacy 3) Modernize to the Cloud: enhance flexibility, scalability and innovation Let’s focus on the boldest move, 3) Modernize to the cloud. So why can’t you afford to wait any longer? 💣 Talent Crisis = Talent Debt Most COBOL experts are 50–70 years old and retiring fast according to AFCEA. New developers aren't learning legacy programming languages, creating a dangerous skills gap that threatens mission-critical operations. 💸 Mainframes OpEx Costs Rising SW licenses, HW costs, and support contracts. These costs bleed budgets and block reinvestment in innovation. 🐘 Lack of Agility Creates a Speed-to-Value Issue Mainframes lack the agility to respond quickly to market shifts or regulations, making speed-to-value a major challenge. Cloud + AI: The Modernization Power Duo ☁️ Cloud provides the ecosystem partner community, flexibility, scale and economics. 🤖 AI (including GenAI + Agentic AI) decodes legacy systems, reverse engineers COBOL, and finds smarter migration paths. 🔐 Together, they enable continuous delivery, improve security, and unlock trapped mainframe data - helping businesses shift from survival to reinvention. Modernizing isn’t just a tech decision. It’s a CxO mandate. CEOs, CFOs, and CROs are realizing this isn’t just an IT problem - it’s about resilience, agility, and future growth. So mainframe modernization isn’t optional. With Cloud + AI, it’s finally feasible, safe to deliver and strategic. Stay tuned for our next post / video with my good friend Sridhar (Sri) Narasimhan who talks to us about The Urgency of Mainframe Modernization from #SanFrancisco Accenture #CloudFirst #MainframeModernization #Innovation Andy Tay | David Parker | Michael Abbott | Rob Pinkham | Ram Ramalingam | Jeff Emerson | Seeju Kumar | Steve Murphy | Jon Hart | Herman Eggink | Joel Rosenberger | Robin Wooley | Christine Disco | Valerio Romano | Duncan Eadie | Sid Nair | Chris Howarth | Sanjay Mehta | Jennifer Jackson | Chris Wegmann | Scott Alfieri | Chetna Sehgal | Shivani Vora | Max Furmanov | Melissa Besse | Susan Whitehouse

An interesting perspective from McKinsey which highlights the need for biopharma companies to modernize their clinical development IT infrastructure to improve efficiency, reduce costs, and accelerate the delivery of innovative therapies. Key challenges include outdated IT systems with fragmented data, rising clinical trial costs, and decreasing success rates. McKinsey also emphasizes the transformative potential of artificial intelligence (AI) and digital technologies in streamlining clinical trials, improving patient outcomes, and enabling real-time insights. 💡Challenges in Biopharma R&D: Long timelines, high costs, and outdated IT systems hinder productivity and innovation in clinical trials. 💡Benefits of Modernization: •Faster Trials: Streamlined workflows and AI-driven optimizations can reduce trial start-up times by 15-20% and trial lengths by 15-30%. •Higher Productivity: Modern IT applications enable near-real-time information flow, increasing productivity by 15-30%. •Improved Success Rates: Advanced analytics help identify patient subpopulations, increasing trial success rates by 10%. 💡Modern Clinical Tech Stack: The ecosystem includes four layers i.e analytics, applications, data, and infrastructure working to support seamless trial execution 💡Strategic Approach to Modernization: • Define the scope of modernization. • Identify areas for differentiation. • Choose between platform-based, best-of-breed, or hybrid architectures. • Select vendor combinations that align with business goals. • Foster joint ownership between business and IT teams. 💡Critical Success Factors: • Embrace end-to-end process transformation. • Prioritize interoperability across systems. • Define clear value metrics and track progress. • Align vendor selection with long-term goals. 💡 Thus, there is a clear need for integrating AI and machine learning into clinical development processes for predictive analytics, operational decision support, and enhanced patient experiences. Companies that modernize their tech stacks can also attract top digital talent, further driving innovation. #Biopharma #ClinicalTrials #R&D #AI #DigitalTransformation #ITModernization #DataIntegration #NextGenAnalytics #PatientCentricity #Productivity #Innovation #TechStack #PharmaIndustry Source: www.mckinsey.com Disclaimer: The opionions are mine and not of employer's

AI is reshaping app modernization programs. Recently I was involved in two modernization programs and the findings were very surprising. Turns out AI is not just a tool for completing code snippets or individual functions, but if given the right inputs (HL design etc.), it can add to productivity in a whole new way. In both cases, I found that treating our AI agent as a virtual (and supervised) developer who is part of the team, rather than just a developer's assistant, proved critical. The success of any app modernization project hinges on well thought-out UX, architecture, and design phases. And just like we do with a development team, by providing AI with these holistic prompts and let it "own" entire functionalities (using RAG and the right prompts), we could generate substantial savings to the tune of up to 30-50%. 1: Modernizing a SaaS Application Stack --------------- Similar to many legacy enterprise applications, a SaaS application built on older technology needed an upgrade - APIs and a flexible front end were key requirements. The app had medium complexity and traditionally would take about 20-24 weeks to modernize. By defining clear requirements, visual mockups, and architecture and then collaborating with AI as a virtual team member (in addition being a dev assistant), the upgrade itself was completed rapidly, cutting overall time by 30%. 2: SQL to NoSQL Migration ----------- A prep-prod Python application running on MySQL was migrated to MongoDB as a proof of concept. Using Coderbotics AI that uses a mix of automation and generative AI, we achieved 70% migration in 1 week and completed the rest of it as a supervised process in 6 weeks, significantly reducing overall time (by ~30%) and significant cost reduction. Treating AI as a capable developer, and giving the right upfront inputs was the key. Results are likely to vary by application, and it's still supervised, but it's a leg up from the popular code completion use cases. Read more in my blog: [link in comments]

70% of enterprise IT budgets are drained by maintaining outdated legacy systems. The result? Slowed innovation, increased risk, and rising costs. 🚀 But there's a smarter path forward — and it starts with AI-powered modernization. Here’s what SoftServe’s latest white paper reveals about COBOL-to-Python migration: - Speed – AI accelerates code translation, reducing delays. - Flexibility – Python enables rapid development and integration. - Savings – Automation reduces maintenance and vulnerability costs. - Scalability – Future-proof systems ready to grow and adapt. 🔍 Still stuck with COBOL? Then you know the pain of rigid architecture and talent scarcity. One enterprise in the energy sector used AI to shift 82 modules to the cloud — not in months, but weeks. The gains weren’t just technical — they unlocked time, budget, and innovation potential. This isn’t just modernization — it’s reinvention. If you’re leading digital change or guiding tech strategy, this read is your next move.

Balancing AI-Driven Modernization with Human Oversight Two articles from The Wall Street Journal caught my attention today. One article focuses on the enterprise modernization opportunity, while the other emphasizes the importance of human involvement and AI alignment. In my previous post¹, I discussed the challenges faced by enterprises in dealing with complexity. I encouraged enterprises to consider key questions, such as (1) whether AI can simplify business processes and (2) if it offers an easier way to navigate through complexity. Enterprises are at a pivotal moment in how they approach legacy systems and business process modernization. Morgan Stanley’s recent deployment of DevGen.AI², an internal generative AI tool built on OpenAI’s GPT models, exemplifies the power of AI in addressing one of the most challenging problems for large enterprises: translating and refactoring millions of lines of legacy code into modern languages. According to Morgan Stanley’s global head of tech and ops, Mike Pizzi, this initiative has already saved developers an estimated 280,000 hours this year. This can potentially help the company to streamline operations, reduce technical debt, and accelerate transformation without requiring significant manual effort. Morgan Stanley is translating legacy code into plain English specifications, which they can then use to replace COBOL, PERL, and Assembler systems with modern programming languages. This is an intelligent first step in answering the questions I raised in my previous post. The full benefits will only be realized when business processes are redesigned and reimagined using these specifications. Morgan Stanley is also wise in not to overlook the human element. The second WSJ article warns that advanced AI models are beginning to exhibit unexpected autonomy, such as rewriting their own code to evade shutdown commands³. These developments underscore the need for robust human oversight and clear boundaries to ensure that technology remains aligned with organizational goals and ethical standards. The best path forward is to modernize boldly with AI, but always keep humans in the loop. By combining cutting-edge automation with human judgment and accountability, enterprises can achieve both operational excellence and responsible innovation. References: 1.     https://lnkd.in/e7PXM7RN 2.     https://lnkd.in/ee9ycqvy 3.     https://lnkd.in/eFDfVEiy

Modernizing a legacy system doesn’t have to take months. Southwest Airlines and PwC proved it can be done in five weeks. Together, they transformed Southwest’s crew attendance and leave management system using GenAI—turning complex source code into clear, actionable requirements. ✅ 50% reduction in backlog creation time ✅ 600+ high-quality user stories generated by AI ✅ 200+ hours saved across engineering, tech, and business teams This isn’t just a systems upgrade. It’s a new model for how GenAI can transform planning, boost team alignment, and fast-track modernization at scale. As Marty Garza, VP of Air Operations Technology at Southwest, shared: "PwC’s approach gave us a smarter, faster, more accurate way to modernize. Their use of GenAI helped free up our teams to focus on what matters most—solving problems and driving innovation." Read the full story here: https://lnkd.in/eq_sfkSD Tim Mattix, Raymond Hearrell #GenAI #LegacyModernization #AITransformation #PwC #SouthwestAirlines

𝗧𝗟;𝗗𝗥: Canada Life accelerated their application modernization using Amazon Q Developer, 𝗮𝗰𝗵𝗶𝗲𝘃𝗶𝗻𝗴 𝗮 𝟰𝟬% 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝘃𝗶𝘁𝘆 𝗶𝗺𝗽𝗿𝗼𝘃𝗲𝗺𝗲𝗻𝘁 𝗶𝗻 𝘂𝗽𝗴𝗿𝗮𝗱𝗶𝗻𝗴 𝗹𝗲𝗴𝗮𝗰𝘆 𝗔𝗣𝗜𝘀. Canada Life saw significant efficiency gains and cost savings while ensuring security compliance, leading to plans for enterprise-wide adoption. 𝘓𝘢𝘴𝘵 𝘰𝘧 𝘵𝘩𝘦 #𝘖𝘶𝘵𝘤𝘰𝘮𝘦𝘴𝘞𝘪𝘵𝘩𝘈𝘞𝘚𝘎𝘦𝘯𝘈𝘐 𝘴𝘦𝘳𝘪𝘦𝘴 𝘣𝘢𝘴𝘦𝘥 𝘰𝘯 𝘤𝘶𝘴𝘵𝘰𝘮𝘦𝘳 𝘵𝘢𝘭𝘬𝘴 𝘧𝘳𝘰𝘮 𝘳𝘦:𝘐𝘯𝘷𝘦𝘯𝘵 24 𝘧𝘰𝘳 𝘵𝘩𝘪𝘴 𝘺𝘦𝘢𝘳! Founded over 175 years ago, Canada Life is a leading provider of insurance, wealth management, and healthcare benefit products and services in Canada, the UK, Isle of Man, Germany, and Ireland.  𝗣𝗿𝗼𝗯𝗹𝗲𝗺: After onboarding 1M+ new customers to their digital platforms, Canada Life faced stability issues with their legacy platforms. Their APIs were scattered across multiple locations making troubleshooting challenging. A planned $5M modernization project to consolidate on AWS faced additional security requirements to remove pre-existing vulnerabilities in the legacy code base, increasing costs by 50% per API to $10M and extending the timeline to end of 2025. 𝗪𝗵𝗮𝘁 𝘁𝗵𝗲𝘆 𝗱𝗶𝗱: * Piloted Amazon Web Services (AWS) Q Developer for 3 APIs to accelerate their modernization efforts * Collaborated with AWS to be able to address older frameworks and dependencies in Canada Life’s codebase. They successfully upgraded the APIs from Java 8 to Java 17 while updating associated frameworks and remediating security vulnerabilities. They now plan to scale adoption and integrate Amazon Q Developer into their development stack and pipelines. 𝗕𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗢𝘂𝘁𝗰𝗼𝗺𝗲𝘀: • 𝗜𝗺𝗽𝗿𝗼𝘃𝗲𝗱 𝗣𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝘃𝗶𝘁𝘆: Achieved 40% average improvement in upgrade efficiency across all tested APIs • 𝗖𝗼𝘀𝘁 𝗦𝗮𝘃𝗶𝗻𝗴𝘀: Conservative estimate of $250K in immediate savings with potential for more as adoption scales • 𝗘𝗻𝗵𝗮𝗻𝗰𝗲𝗱 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆: Improved security posture by eliminating legacy vulnerabilities during the upgrade process. Watch Amber Bird, AVP Engineering at Canada Life present at re:Invent their experience with Amazon Q Developer https://lnkd.in/eKWhkGyj