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3/19/24, 1:55 PM Navigating AI landscape: Fostering digital agility and resilience – Dubai Iconic Lady
Companies can adopt strategic approaches to leverage AI/ML, such as enabling scale for AI-enabled
applications. This involves providing a consistent cloud application platform across multiple private and
public clouds, facilitating building, training and deployment of AI-enabled applications. Moreover,
collaborations with the ISV & SI community to offer AI tools, models and services accelerates the
development and deployment of AI solutions. Also, the adoption of containers in AI workloads is gaining
prominence, with 94 per cent of AI adopters leveraging or planning the utilisation of containers in the coming
year. This further underscores the increasing significance of containerisation in developing and enhancing AI
workloads.

The hype surrounding AI/ML has sparked interest in new use cases and possibilities. However, effective
governance of data, applications and IT systems remains a key priority. According to the 2023 Enterprise
Cloud Index, organisations are leveraging multiple types of IT infrastructure, indicating a shift toward
diverse and hybrid environments. Building the optimal AI-ready infrastructure has the potential to expedite
AI/ML initiatives, but companies should prioritise sustainability, cost management, security and other IT
governance compliance aspects.

The integration of AI into the open hybrid cloud is a significant step forward. To drive this transformation,
open-source artificial intelligence and machine learning (AI/ML) platforms like Red Hat OpenShift AI offers
a unified platform for data scientists and developers to design, train, serve, monitor and manage the life cycle
of AI/ML models and applications across diverse environments. The platform aims at meeting the demands
of foundation models and ensures consistency in production deployment and monitoring capabilities. It
further ensures that customers can build and deploy intelligent applications seamlessly.

For instance, tech giants like Intel play a significant role in the AI ecosystem, showcasing their investments
in semiconductor manufacturing to strengthen supply chain resiliency. Intel’s strategic investments in various
fields aim to cultivate robust epicentres of technology and thriving ecosystems for semiconductor
manufacturing.

Furthermore, Intel’s AI Everywhere Portfolio extends from the data centre and cloud to the client and edge.
Its strategic investments in semiconductor manufacturing contribute to supply chain resiliency, supporting
diverse-owned suppliers and fostering innovation within the global supply chain.

A diverse and inclusive supply chain, including diverse-owned suppliers, enhances resilience and introduces
healthy competition, driving innovation. In light of this, Intel’s Smart Capital strategy is a testament to its
commitment to long-term growth, aiming to drive development while ensuring flexibility and delivering
higher returns on investments.

The successful deployment of AI necessitates organisations to integrate it seamlessly into their core business
operations. By prioritising data quality, training employees, and modernising technology infrastructures,
businesses can successfully deploy AI. Innovative strategies and collaborations empower enable
organisations to adeptly manoeuvre through the intricacies of implementing AI, promoting digital flexibility
and robustness in a constantly evolving environment.

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