By: Bernd Schaefer, Dan Martino, Shawn D’Souza
You can’t replace real-world experiences with observations made from a distance. Some truths are only discovered in the trenches.
To gain a deeper understanding of how the business applications landscape is evolving, we asked three experts from Kyndryl’s Applications, Data and AI practice to share some lessons learned while partnering with enterprises across industries to design, build and manage future-ready application ecosystems.
We encourage you to use these insights as foundations for building application strategies to outmaneuver the competition, now and in the future.
What forces are shaping the applications sector now, and how will they impact the market moving forward?
Bernd Schaefer: Agentic AI. The technology is growing and will dominate the landscape for years. Teams will use it to create, customize and modernize applications and the business processes these applications support.
Dan Martino: AI — it isn’t just a buzzword anymore. Manufacturers are baking the technology directly into ERP, CRM and other core platforms. Agentic AI will take things up a notch by automating workflows, making autonomous decisions, and providing conversational interfaces for business processes. Basically, apps will start “thinking” for you. Advanced analytics, cloud-native architectures, hyper-automation and low-code/no-code platforms are also becoming major forces in the applications space.
If the new application frontier is experience-driven, how can organizations rethink their strategies to make apps more intuitive, adaptive and seamless?
Martino: Old-school, monolithic architectures are out. The future is all about modular, composable architectures that let you plug in new features without breaking the whole system. Micro-frontends and atomic services make this possible. Add event-driven architectures to the mix, and apps start reacting in real time — context-aware, adaptive and personalized.
Schaefer: I’m not sure it’s about experiences in the traditional sense. The experience change I see coming is more of an iterative and non-deterministic interaction between business users and applications. For example, instead of writing specs for an application and then giving them to someone to implement, users may sit down and chat with an application to get to a desired outcome.
“Old-school, monolithic architectures are out. The future is all about modular, composable architectures that let you plug in new features without breaking the whole system.”
Dan Martino
Senior Vice President
Applications, Data and AI
What advice do you have for CIOs trying to future-proof their application strategies?
Schaefer: I’ve never seen a platform outperform open architecture, and I don’t think that will change. So, instead of obsessing over which platform is the best, focus on open and intelligent architectures because agility and flexibility are more important than ever. Also plan to take users with you on the agentic AI journey and provide them the applications they need to get things done.
Martino: Think business-first over tech-first. Position IT as a growth engine. Every tech initiative should tie back to clear business outcomes, whether that’s boosting revenue, cutting costs, improving efficiency or making customers happier. You’ll also want to scale AI beyond the hype and bake in security and governance everywhere. Go composable and be data driven. Invest in people. Obsess over experience.
How do AI-enabled and AI-native apps differ, and what operational impacts will this eventually have?
Shawn D’Souza: With AI-enabled applications, AI features are added to existing functionality to improve performance, but the architecture doesn’t change fundamentally. AI-native applications are built from the ground up with AI as a core component. The core logic of the application is expressed through AI models instead of relying on fixed, rules-based programming. This capability enables AI-native apps to make complex, real-time decisions, learn continuously, and evolve. Intelligence is embedded into every part of the system, allowing for smarter, faster and more adaptable performance.
What happens to app architecture when experience replaces function as the core product?
Martino: When experience takes center stage, architecture stops being about rigid functionality and starts acting like a flexible, experience-first ecosystem. Headless architectures and micro-frontends let you deliver consistent, omnichannel experiences and tweak user interface (UI) components. APIs become the glue for seamless integration, while event-driven architectures enable apps to react to user actions and context in real time. It’s all about responsiveness and adaptability.
“AI-native apps make complex, real-time decisions, learn continuously, and evolve. Intelligence is embedded into every part of the system, allowing for smarter, faster and more adaptable performance.”
Shawn D’Souza
Senior Vice President
Kyndryl Consult
How must team roles and skills evolve as the use of AI agents for app development increases?
Schaefer: Everyone will eventually need to know how to have smart interactions with AI through prompting or by using agentic AI solutions. No role will be excluded from this requirement. But for now, the agentic AI colleague is a junior developer with a few years of experience. The meritocracy principle still applies, with AI raising the bar for developers and, quite possibly, raising it a couple more levels in the years to come.
What new data or governance challenges will CIOs face as AI becomes deeply embedded in enterprise apps?
Martino: AI isn’t neutral — it can amplify human bias and lead to legal issues. To remain compliant with constantly changing privacy laws, you’ll need to monitor and audit your systems continuously. Your teams should own every AI-driven decision and keep humans in the loop for critical calls. You’ll need infrastructure that scales and systems that deliver data at lightning speed. And since AI is only as smart as the data it learns from, you’ll have to eliminate silos to create a single source of truth.
How does Kyndryl design architecture that meets customers’ specific needs?
Schaefer: We start with an enterprise mindset and use proven frameworks and real-world insights from our integration platform (Kyndryl Bridge) to drive decision-making. We then design modular, scalable systems that thrive in cloud-native environments and balance business goals with IT necessity. And we do it all while minimizing interruptions to existing operations.
“Agentic AI is growing and will dominate the landscape for years. Teams will use it to create, customize and modernize applications and the business processes these applications support.”
Bernd Schaefer
Senior Vice President
Applications, Data and AI
What makes this strategy unique?
D’Souza: We approach transformation holistically, focusing on people and processes as much as tech modernization. Our design philosophy, which is grounded in hybrid architecture and Kyndryl’s mission-critical expertise, prioritizes the user experience. And our change management strategy helps organizations adapt as technology evolves.
How does Kyndryl work with customers to accelerate their AI journey?
D’Souza: Instead of simply bolting AI onto old systems, we use Kyndryl’s AI Agentic Framework to design intelligent applications infused with generative and agentic AI capabilities. We also integrate data across systems and put guardrails in place to govern AI usage. These are building blocks for becoming AI-native.
