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3/19/24, 1:55 PM Navigating AI landscape: Fostering digital agility and resilience | iHeartEmirates
With the digital economy constantly advancing, agility and flexibility are not just desirable

attributes, but are key pillars for organisational success. Navigating the complexities of digital
transformation requires a deep understanding of agile principles and the pivotal role of effective

data management. Data, often referred to as the currency of the digital economy, plays a key

role in enabling organisations to thrive.

However, several challenges stand in the way of seamless AI/ML project execution. A significant

obstacle is the shortage of talent with key skills, making it challenging to find and retain qualified

professionals. Additionally, the lack of self-service access to AI/ML tools and infrastructure

impedes the workflow of data scientists and developers. Operationalising AI projects further

adds to the challenge, with slow, manual and siloed operations hindering the swift execution of
AI lifecycle. Acknowledging these challenges is crucial, and constant vigilance is necessary to

mitigate these setbacks to achieve success in AI/ML initiatives.

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

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