Page 8 - Red Hat PR REPORT - MARCH 2024

Navigating AI landscape: Fostering digital agility and resilience

By Adrian Pickering, Regional General Manager MENA, Red Hat

In an era of rapid technological advancements, organisations are grappling with the challenges
of executing AI and machine learning (AI/ML) projects efficiently. As the digital landscape
continues to evolve, the need for agility and resilience becomes paramount. Numerous hurdles
are faced by organisations, which has necessitated innovative strategies to foster digital agility
and resilience through enterprise intelligence.

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
consistency in production deployment and monitoring capabilities. It further ensures that
customers can build and deploy intelligent applications seamlessly.