The intelligent cloud era is here, and enterprises cannot afford to overlook the AI shift

By Ganesh Jayaraman, Senior Director & Global Head of Cloud Operations, Pegasystems

With the rise of generative and agentic AI, the cloud is no longer just where data lives; it’s where intelligence happens. In the past few years, cloud computing has redefined enterprise IT by delivering the agility, scalability, and cost efficiency that businesses have needed to excel in a digital world. These benefits, once seen as the pinnacle of transformation, are now considered foundational. The next leap isn’t just about faster infrastructure; it’s about smarter systems.

AI is accelerating that shift. With generative AI and agentic AI advancing rapidly, the cloud is no longer just a destination for workloads; It has become a thinking partner. From storing and scaling to detecting and strategising, cloud platforms are evolving into intelligent systems that can learn, predict, and act in real time. This shift is reflected in enterprise priorities. According to an IDC report, more than 60% of businesses are expected to have modernised up to half of their cloud architecture by 2027, aiming to boost infrastructure efficiency, and more than 80% see cloud modernisation as a top priority. From infrastructure and development to security and compliance, AI is not just supporting cloud operations; it’s beginning to lead them.

From Scalable to Self-Optimising: AI in Cloud Infrastructure Management

The move toward intelligence begins with infrastructure. Traditional cloud systems are reactive by design as they respond to spikes, scale on demand, and rely on preset thresholds. Meanwhile, AI changes that foundation entirely. By embedding intelligence into the core of cloud platforms, enterprises gain systems that not only observe and analyse usage patterns but also correlate them with business trends to anticipate future demand.

This is where agentic AI comes into play. These autonomous agents act as sentinels within the cloud environment, constantly scanning performance indicators, identifying inefficiencies, and fine-tuning compute, storage, and network resources in real time. They transform the cloud from a static resource pool into a dynamic, self-optimising ecosystem.

For instance, consider a global enterprise deploying AI-powered CRM and case management across markets. As a product launch triggers a spike in customer interactions, embedded AI agents monitor system loads and identify the surge as campaign-driven. They reallocate compute and network resources proactively, ensuring uninterrupted service for critical workflows. This is more than reactive scaling; it’s intelligent workload alignment, where infrastructure aligns with business priorities to deliver enterprise agility and strong customer engagement.

Accelerating developer velocity through generative AI

Just as AI agents are optimising infrastructure in real time, they are also transforming developers’ productivity. Developers are now building faster by leveraging better tools and smarter infrastructure. For instance, with AI, a simple prompt like ‘create a backend for a logistics app’ can generate a complete cloud-native architecture, including APIs, security configurations, Infrastructure-as-Code scripts, and CI/CD pipelines, delivered within seconds.

This shift is reshaping how teams architect, deploy, and iterate. As GenAI becomes embedded into development environments, developers are no longer writing every line of code from scratch. Instead, they are collaborating with AI systems that understand context, suggest structures, and Automate repetitive tasks, allowing teams to focus on innovation and business logic.

Embedding AI in security and compliance

As enterprises expand across hybrid and multi-cloud environments, securing distributed systems and maintaining compliance have become strategic imperatives. Traditional perimeter-based approaches and static control frameworks are increasingly being complemented by more adaptive models that are better suited to the speed, complexity, and scale of today’s cloud-native operations.

To address this, cloud-native security is evolving into something far more intelligent. Cloud platforms embedded with intelligent systems continuously analyze patterns, detect anomalies, and initiate real-time mitigation. From enforcing access controls to triggering multi-factor authentication and isolating suspicious activity, these actions happen dynamically without requiring manual oversight.

Additionally, the compliance layer is evolving in parallel. AI capabilities within cloud environments now enable dynamic interpretation of changing regulations, assessment of organisational readiness, and early detection of potential risks. This ensures that security and compliance operate as proactive, integrated functions, resulting in a governance model that is responsive, contextual, and aligned with the pace of cloud-native innovation.

The Rise of Industry Clouds: Tailored Intelligence at Scale

AI is revolutionising every facet of the cloud ecosystem, from core infrastructure to application development, security, and compliance, ushering in a new era of industry-specific cloud platforms. These purpose-built environments are tailored to address the unique operational demands and regulatory standards of sectors such as healthcare, finance, and retail, enabling organisations to harness AI with precision and scale.

Industry-aligned cloud solutions meet this demand by embedding sector-specific intelligence into the core architecture. Built for domains like healthcare, financial services, and retail, these platforms combine pre-trained AI models, compliant data structures, and contextual workflows. Whether it’s AI-assisted diagnostics in healthcare or real-time transaction monitoring in finance, industry clouds are designed to deliver results quickly and securely.

By aligning cloud capabilities with sector priorities, these platforms reduce integration overhead, accelerate time-to-value, and provide a smarter foundation for innovation, tailored from the start.

A New Operating Model for the Enterprise

As generative and agentic AI redefine what’s possible, businesses that embrace this shift will unlock unprecedented agility, resilience, and innovation. From infrastructure to industry-specific intelligence, the cloud is now a strategic co-pilot, not just a platform.

To lead in this new era, enterprises must rethink their cloud strategies by investing in AI- native architectures, training AI agents to co-manage operations, and embracing intelligence as a business function. As AI reshapes the cloud, those who architect for autonomy, not just agility, will be the ones leading.