Page 31 - Red Hat PR REPORT - OCTOBER 2025

Blog Post

with or without IT teams’ authorisation. This introduces new risks and underscores the need for
internal education and guardrails, supported by platforms that are accessible, governed, and
designed with users in mind.

The solution: a platform approach built on open source

Overcoming these barriers requires moving from a collection of fragmented tools to a unified
platform strategy. IT leaders and AI developers in EMEA already recognise the path forward, as
6
92% agree that enterprise open source is important to their AI strategy . An enterprise open
source AI platform can offer the consistency and control needed to build, deploy, and manage AI
across any hardware and any cloud.

Organisations need a security-first, governed environment where teams can access the tools
they need to experiment and build with confidence. Rather than spinning up lots of different
7
systems in departmental silos (the top-rated barrier to AI adoption ), the use of an open source
platform helps replicate success rather than reinvent the wheel. This approach allows IT to
2
enable innovation, not block it, helping to fulfil a major AI priority for 75% of respondents:
transparency and openness. Open source provides this transparency as well as increasing
standardisation, helping enterprises retain control over AI and data decision-making. This
2
control and flexibility is also vital to provide AI sovereignty, which is a priority for 74% of
respondents.

An enterprise open source platform like Red Hat OpenShift AI also helps address the skills gap.
By providing data scientists and developers with common tools and streamlined MLOps and
LLMOps workflows, it boosts productivity as well as allowing organisations to tap into the
broad range of talent and innovation within the open source ecosystem. It also simplifies
connecting models to enterprise data to help solve the integration challenges that are top of
7
mind . Meanwhile Red Hat AI Inference Server optimises inference for faster, more cost-
7
effective model deployments, which helps surmount the cost barrier cited by 29% of
respondents.

By standardising on robust, open platforms, leaders can better control and govern AI, de-risk
scale, and turn transparency into a competitive advantage.

From ambition to value

To close the AI value gap, organisations must match their ambition with an IT platform strategy
that prioritises innovation, choice and scale – much as hybrid cloud platforms have borne out to
be the most sustainable model for the cloud world. The path from pilot to production relies on
the flexibility to adapt and the ability to scale when ready.