The Future of Digital Transformation: Embracing AI and Observability in Cloud-Native Environments
The Future of Digital Transformation: Observability at the Core of AI and Cloud-Native Workloads
Mexico City, Mexico — As the digital landscape undergoes a seismic shift, the adoption of cloud-native platforms and the scaling of artificial intelligence (AI) technologies are at the forefront of this transformation. A recent report by Gartner predicts that by 2025, over 95% of new digital workloads will be running on cloud-native platforms, a significant leap from just 30% in 2021. This rapid evolution necessitates a unified approach to managing complexity, risk, and performance, according to Carmen Nava, Senior Strategic Enterprise Account Executive at Dynatrace, who spoke at the Mexico Business AI, Cloud & Data Summit 2025.
“Digital acceleration has outpaced our ability to manage complexity,” Nava stated. “Observability is no longer a technical nice-to-have; it is the foundation that connects data, AI, and business outcomes.”
The Imperative of Observability
For organizations navigating the complexities of cloud and AI workloads, effective observability is crucial for achieving three key business outcomes:
- Accelerating Deployments: Streamlining the rollout of cloud-native workloads.
- Ensuring Success and Governance: Supporting AI initiatives while maintaining compliance and control.
- Enhancing Developer Experience: Boosting productivity and overall satisfaction among developers.
Nava emphasized that data alone is insufficient; the real challenge lies in intelligently integrating it to generate actionable insights that drive decision-making, automation, and innovation. In multicloud environments, each layer of the technology stack tells a different story. “Observability provides a single, unified narrative — one source of truth that allows leaders to innovate without losing control,” she added.
The Role of AI Observability
AI observability is vital for ensuring that Generative AI, Large Language Models (LLMs), and other advanced AI initiatives meet their objectives. Key metrics such as total requests, average request duration, costs, and guardrail executions help detect issues like personally identifiable information (PII) leaks or model toxicity. Beyond infrastructure monitoring, observability is essential for application performance and enhancing the end-user experience.
Operating AI systems without observability, Nava warned, is akin to “flying a plane without radar.” Organizations must have clarity on their direction, identify risks, and ensure that every model aligns with strategic goals.
A Unified Approach to Complexity and Security
End-to-end observability and security form the bedrock of modern business operations, enabling organizations to reduce complexity, optimize costs, and protect against threats. This unified approach not only transforms business operations through innovation and risk reduction but also enhances cloud and vendor expenditure management.
A consolidated platform offers real-time insights for executives, continuous compliance for IT teams, and automated root cause analysis for engineers. Developers benefit from autonomous intelligence tools like Davis CoPilot, which provide in-Integrated Development Environment (IDE) guidance, resolve root causes, and suggest code fixes to enhance productivity.
“Technology should enable people, not overwhelm them,” Nava asserted. “When developers spend less time troubleshooting and more time creating, that is when innovation truly scales.”
Looking Ahead: The Future of Observability
As organizations look to the future, observability is expected to evolve into a more powerful tool. “The future of observability is not just visibility — it is intelligence,” Nava concluded. “When systems can see, understand, and act in real time, organizations gain the confidence to evolve faster than ever before.”
As the digital landscape continues to evolve, the call for robust observability solutions will only grow louder, shaping the future of AI and cloud-native workloads in unprecedented ways.
