As Artificial Intelligence rapidly moves from experimentation to becoming a core business capability, enterprises are grappling with a critical challenge – scaling AI securely and consistently across complex hybrid and multi-cloud environments. While adoption is accelerating, true AI readiness demands far more than pilots; it requires strong security foundations, architectural alignment, and ecosystem collaboration. In this interaction with Express Computer, Pratik Shah, Managing Director – India & SAARC, F5, shares insights on how organisations can bridge the gap between AI ambition and execution, leverage partnerships across infrastructure and cloud, and enable Indian CIOs to future-proof their AI strategies through governance, zero trust, and adaptive, AI-ready infrastructure.
How can enterprises move from AI experimentation to secure, scalable deployment through ecosystem alignment?
As AI becomes central to business strategy, the gap between experimentation and scalable deployment is becoming increasingly visible. AI readiness goes far beyond experimentation, it requires a robust foundation built on security, scalability, and architectural alignment. Our 2025 State of AI Application Strategy Report shows that while adoption is accelerating, only 2% of global organisations are prepared to scale AI securely across their operations.
To further scale adoption, enterprises need an ecosystem-driven approach that delivers security, performance, and consistency across environments. This means embedding security and policy controls early into the application lifecycle enforcing uniform controls across environments, and ensuring alignment between infrastructure, applications, and security to deliver reliable AI on a scale.
Why partnerships across infrastructure, cloud, and security providers are key to building resilient AI architectures?
AI workloads span across APIs, data stores, and inference endpoints across distributed hybrid and multi-cloud environments. This complexity introduces challenge because each cloud or infrastructure layer comes with its own performance characteristics, security controls, and data requirements.
By working closely with cloud providers, infrastructure partners, and security ecosystems, organisations can build resilience to drive consistent performance that is optimized across every layer. F5 enables this by securing application delivery, adaptive traffic management, and integrated security controls that enable businesses to confidently deploy AI wherever it runs.
How multi-cloud networking, Zero Trust, and adaptive infrastructure can help organisations operationalise AI securely?
Organisations have an opportunity to modernize hybrid and multi-cloud environments, but traditional architectures and siloed IT infrastructure often lack interoperability. This challenge intensifies with AI applications pushing the boundaries for performance and innovation. To operationalise AI securely, businesses need multi-cloud networking for seamless, policy-driven connectivity, Zero Trust for continuous verification, least privilege controls across users, devices, apps and APIs, and adaptive infrastructure for real-time agility and security.
F5 delivers these capabilities through Distributed Cloud Services, enabling orchestration, security, and observability across environments. This integrated approach ensures resilience, compliance, and performance for empowering organisations to innovate with AI confidently and securely.
What must enterprises do to move from AI pilots to secure, scalable adoption through automation, governance, and AI-ready infrastructure?
While many enterprises are exploring AI, the real opportunity lies in establishing the governance, security, and infrastructure required to scale it responsibly. Enterprises are building intelligent AI-driven services that utilise the unparalleled amount of data to deliver insights and power automation that will enable customers to make more informed decisions and take quicker actions.
In our recent report, the biggest barriers include inconsistent cross-cloud security, weak data classification, and manual processes that fail to keep pace with AI workloads. To overcome these challenges, organisations need strong governance frameworks with clear ownership, well-defined policies for model usage and data handling, and continuous monitoring to maintain oversight.
What can Indian CIOs do today to future-proof their AI strategies and accelerate enterprise-wide readiness?
As AI adoption accelerates, Indian CIOs must balance innovation, efficiency, and risk management to adapt to changing business dynamics. Our study shows that globally nearly two-thirds of survey respondents use two or more paid models such as GPT-4, and at least one open-source model with the average organisation uses three models.
For instance, future-proofing AI strategies means securing new attack surfaces created by automation and autonomous agents, while modernising infrastructure and optimising costs to manage complex IT landscapes.
Hence, by enabling secure multi-cloud connectivity and adopting adaptive infrastructure, CIOs can mitigate sophisticated risks, improve operational resilience, and unlock competitiveness that ensures AI delivers innovation, efficiency, and sustainable business value across the enterprise.