Modern apps brought tech agility. Intelligent apps bring business adaptability.

Modern application design helped organizations move faster in software development and delivery. Cloud-native foundations, modular architectures, and DevSecOps pipelines gave teams the agility to release quickly and scale efficiently.

But a new ambition has emerged: intelligence.

Intelligent applications bring personalization, prediction, and automation into every layer of how systems operate and evolve. They respond in real time and learn from interaction. They create new ways to engage both customers and teams.

Intelligence is no mere tech upgrade. It’s a shift in how software is imagined, built, and experienced. And the gap between early adopters and hesitant movers is widening.

Which brings us here: to a moment where businesses need to think in layers. The foundation is speed, scalability, and security. The evolution is intelligence — systems that personalize, automate, and adapt in real time.

We used to build systems. Now we shape experiences.

For much of the digital era, applications were built as structured, bounded systems. Client-server models, APIs, and microservices architectures defined clear handshakes between services. They kept interactions organized, but often rigid.

But the way users engage with technology is evolving—and so must the systems underneath. Today’s applications can’t limit themselves to completing transactions or accessing services. They need to deliver fluid, seamless experiences that feel personalized, continuous, and connected across every touchpoint.

Users move effortlessly between web, mobile, extended reality, and physical environments, often without even thinking about it. Hyper-personalization powered by continuous connectivity, enabled by cloud-native architectures, is blurring the traditional lines between systems, applications, and interactions. In this landscape, the boundaries are no longer defined by system architecture—they’re defined by how well you can meet users where they are, anticipate what they need, and evolve as they do.

What modern apps are built to do.

Modern applications are the result of decades of lessons learned from clunky architectures and rigid systems. They’re designed to be lean, cloud-native, modular—built to change, not just to handle change. They move fast, scale easily, and stay secure through DevSecOps pipelines and API-first integrations. They’re easier to maintain and quicker to evolve, and they’re primed to support continuous delivery.

Today, many of these apps are already being built using low-code tools and Gen AI-augmented platforms like Microsoft Power Platform and Azure, which speed up delivery while preserving enterprise-grade governance and control. Developers—and increasingly, business teams—can co-create and ship new features faster than ever. They can rapidly prototype, test, and roll out applications across multiple channels. As interactions become more diverse and immersive, apps need to adapt fluidly across all touchpoints to meet customers where they are.

Modern apps deliver:

• Shorter release cycles with fewer handoffs
• Consistent performance across platforms and touchpoints
• Built-in governance, resilience, and scalability
• A platform for experimentation, without the drag of legacy

But there’s still more value to drive. Modern apps are the baseline for the next stage: intelligent applications. Modernization gets your apps ready to take advantage of AI, making it possible to create smarter, more responsive user experiences.

What are intelligent apps?

If modern apps help you move faster, intelligent apps help you move smarter. They analyze, learn, and improve how work gets done.

Intelligent apps leverage Generative AI (Gen AI), the Agentic AI framework, and rule-based systems to enhance predictability. That includes everything from embedded copilots and autonomous agents to machine learning models that personalize user experiences, automate complex workflows, or make predictive decisions in real time.

Intelligent apps are shaping everyday experiences.

We already see intelligent experiences in everyday life—whether it’s Netflix suggesting your next favorite show before you even search for it, banking apps flagging unusual transactions instantly, or navigation apps rerouting you in real time based on traffic conditions.

These days, a simple online store has evolved into an intelligent shopping experience—powered by algorithms that anticipate what you might need, make personalized recommendations, and even automate reordering for frequently purchased items. Behind the scenes, AI models analyze browsing behavior, purchase history, and contextual data to shape every customer interaction. It’s a continuously learning system designed to meet you where you are and nudge you toward what’s next.

Banking apps are also evolving quickly. They used to be simple interfaces for checking balances or making transfers, and now they’re transforming into intelligent financial tools. Many banks offer real-time fraud alerts, automatic spending categorization, and proactive budgeting insights—features that help users understand and manage their money with more confidence. Increasingly, institutions are experimenting with predictive tools that can flag potential shortfalls before they happen, or recommend savings goals based on past behavior and upcoming expenses. Such intelligent features are powered by AI models trained on transaction histories, behavioral data, and contextual signals.

As more organizations take this direction, the competitive advantage is becoming clear: customers expect more than access—they want insight, control, and experiences that evolve with them. And app teams want to deliver smarter, more responsive experiences that build trust and empower users.

Build intelligence in layers

The apps don’t need to be built from scratch. Many are layered onto modern application foundations—using the same low-code platforms, APIs, and cloud services—but with intelligence infused at every step. That infusion might look like:

• AI-powered chat interfaces that assist users in natural language
• Recommendation engines that adapt based on context
• Automation flows that learn and optimize over time
• Smart integrations between business systems and data sources

Again, platforms like Microsoft Azure, Copilot, and Power Platform are leading the way in intelligent capabilities. Teams can now build smarter features faster. They can scale intelligence across apps, users, and experiences—and high-complexity use cases are literally at their fingertips.

Where Gen AI fits in: Beside, Inside, Outside

Gen AI presents a new way of thinking about application value. At Sogeti, we use a simple but powerful lens—Beside, Inside, and Outside—to help organizations understand where and how Gen AI can drive the greatest impact:

• Beside: Using Gen AI to improve current projects—application modernization, cloud-native builds, or in-flight app development. Copilots and intelligent automation boost productivity across the full software lifecycle.
• Inside: Building AI-powered applications from the ground up. Apps with Gen AI or large language models embedded directly into the experience—enabling faster time to market, more personalized services, and differentiated business value.
• Outside: Going beyond single applications to orchestrate entire workflows and connect systems using intelligent agents. This is where businesses can unlock operational excellence, scale automation, and reduce complexity across the board.

Our interaction models help organizations tap into Gen AI across three key priorities: innovation, productivity, and customer experience. Whether you’re experimenting or scaling, we help teams apply the right Gen AI model at the right time, so that the foundation is ready to support what’s next.

👉 Curious where to start? Our Intelligent App Feature Assessment helps identify quick wins across your current app portfolio—and lays out a clear roadmap to scale.

Build forward—with modern foundations.

Not every app needs AI. But every app needs to be ready for it.

Modern applications use cloud-native patterns, e.g. microservices, containers, API-first design, to make it possible to test new features quickly, scale intelligent capabilities safely, and integrate seamlessly across environments. When you start layering in AI—natural language interfaces, copilots, smart agents—it’s that modern app structure that keeps everything moving.

Think about building forward from what currently works. That starts with understanding how your applications are built today—where modern foundations already exist, where legacy constraints remain, and where intelligent opportunities are emerging. Tech maturity has—matured. Think readiness: architectural readiness, data readiness, team readiness.

Think AI Readiness.

We help organizations assess where they stand, and where to act first. Our AI Readiness Assessment evaluates your application landscape for both modernization and intelligence potential—so you can make informed decisions and prioritize where to act first.

When the groundwork is clear, the opportunities are immediate:

• Replatform or refactor legacy systems that block agility or integration.
• Enable low-code environments like Power Platform to extend innovation across business teams.
• Embed intelligent features into specific workflows—onboarding, approvals, self-service, and more.
• Establish a secure AI platform layer for models, agents, and copilots to run reliably at scale.

With the right foundation in place, developers release faster. Product owners test and iterate intelligently. Business teams create apps that reflect real needs—without needing to rebuild from scratch.

How do you want to evolve?

Innovation is unfolding on multiple fronts. We see it happening across two dimensions: the way applications are built, and the way they operate in the world. The possibilities are ready to be realized—by those with the vision and foundations to move forward.

Modern apps are that foundation. Intelligent apps are the evolution. Built on cloud-native, modular architecture, modern systems make it possible to integrate AI at scale—and transform static tools into adaptive, data-driven engines of innovation.

Microsoft’s platforms make this evolution real. Azure provides the foundation. Power Platform and Copilot bring intelligence to life—helping teams move faster, respond smarter, and build systems that learn and adapt.

But tools alone aren’t the differentiator. The path you choose—and the partner guiding it—makes the difference.

At Sogeti, we help growing organizations align strategy with action, modernize with purpose, and bring intelligent apps into production with confidence.

Key Takeaways

• Intelligent apps are evolving beyond static systems to become adaptive, real-time experiences—shaping how businesses engage users, deliver value, and operate internally.
• Modern apps are the prerequisite for intelligent ones. Cloud-native foundations, modular architecture, and API-first design make it possible to integrate AI capabilities safely and at scale.
• Intelligence doesn’t require starting over. With the right architecture, teams can layer in copilots, recommendation engines, and automation flows on top of existing systems.
• Strategic adoption depends on readiness—architectural, data, and team maturity. Sogeti’s AI Readiness Assessments and GenAI App Evaluators help businesses prioritize where and how to act first.

Where do you want to go next?

🔹 Get a snapshot of what’s possible
→ [Download the Before & After Modernization infographic]

🔹 Take the Intelligent App Assessment
→ [Explore our AI App Jumpstarts]

🔹 Have a roadmap in mind already?
→ [Talk to us about building your first intelligent app]