By Rackspace Technology
AI adoption across the NHS is no longer theoretical. Organisations are already using AI to reduce administrative burden, improve access to insights, and support more efficient healthcare delivery.
New research conducted by Coleman Parkes Research for Rackspace Technology shows that AI adoption is advancing across NHS organisations, although maturity levels remain varied. 51 percent of organisations plan to enhance existing technologies with AI capabilities, while 41 percent plan to invest in new AI-enabled technologies. At the same time, 37 percent report reduced clinician workload through AI adoption, and 33 percent cite faster access to insights through data analytics and visualisation.
The operational value is already visible. AI is helping NHS teams work more efficiently and make better use of healthcare data. But as organisations move beyond experimentation and into operational deployment, another challenge is becoming increasingly important: how to scale AI safely while maintaining control over patient data, governance, and operational resilience.
Only one percent of organisations report that AI is fully embedded into business strategy, while 33 percent describe AI usage as minimal or ad hoc.
That gap matters because scaling AI in healthcare depends heavily on trust, governance, and operational control.
NHS organisations are balancing innovation with risk
AI systems increasingly rely on access to sensitive patient records, clinical notes, and operational data. As these tools move further into day-to-day healthcare environments, organisations need confidence in how that data is accessed, governed, and protected.
The survey findings suggest many organisations are still building that confidence.
According to the research:
- 44 percent identify security risks and vulnerabilities as a key concern
- Only 12 percent describe their organisation as cyber resilient
- 44 percent lack confidence in protecting data from cyberattacks
Alongside security concerns, many NHS environments remain operationally complex. 70 percent describe their technical debt as moderate to high, while only 20 percent are very confident in interoperability across systems.
This creates a difficult balance. Organisations want to accelerate AI adoption, but they also need to maintain governance, resilience, and accountability around highly sensitive healthcare data.
As a result, many NHS organisations are progressing cautiously. AI is often introduced through targeted use cases where value can be demonstrated quickly, but scaling beyond those early deployments can become more difficult when governance frameworks, operational models, and security controls are still developing.
Sovereign AI means bringing the AI to the data
One of the biggest questions facing NHS organisations is not whether AI can deliver value. The research already shows it can. The challenge is how to apply AI to sensitive healthcare data while maintaining governance, operational control and trust.
At Rackspace Technology, we increasingly see sovereign AI as an operational model built around a simple principle: bring the AI to the data, not the data to the AI. For NHS organisations, that distinction matters.
Traditional AI approaches often rely on moving large volumes of sensitive data into external platforms or shared AI environments for processing and model interaction. In healthcare, that can quickly introduce governance, compliance, and operational concerns around where patient data resides, who can access it, and how it is controlled.
Sovereign AI takes a different approach. Instead of moving sensitive healthcare data into external AI ecosystems, AI capabilities are deployed closer to the data itself, within governed environments where organisations maintain operational visibility and control.
This allows NHS organisations to apply AI capabilities while maintaining stronger control over:
- Patient records and clinical data
- Data access and permissions
- Governance and auditability
- Operational oversight
- Compliance requirements across hybrid environments
From our work across healthcare and the wider public sector, we’re seeing growing recognition that AI adoption cannot scale sustainably if governance is treated as an afterthought.
As organisations move beyond isolated pilots and begin operationalising AI more broadly, maintaining control over how data is handled becomes critical to building trust in AI outcomes.
Scaling AI requires more than deployment
One of the biggest challenges facing NHS organisations is that deploying AI is only one part of the journey. Operationalising and scaling AI across healthcare environments requires ongoing governance, operational support, and performance management.
At Rackspace Technology, our approach focuses on supporting the full AI lifecycle:
- Develop
- Operate
- Scale
That starts with creating secure environments where organisations can experiment with AI while maintaining control over patient data and governance requirements. From there, AI workloads can be operated within managed environments that provide visibility, access control, and operational oversight. Finally, organisations can scale AI more confidently across healthcare environments while maintaining resilience and governance consistency.
Through our work with NHS and public sector organisations, we help customers not only design and develop AI solutions with strategic partners, but also operationalise and manage those environments over time. That includes supporting the infrastructure, governance, operational controls, and day-to-day management needed to run AI securely at scale.
Importantly, sovereign AI environments should ensure organisations maintain visibility and control over how patient data is handled, how AI systems are operated and how environments are governed across hybrid infrastructure.
For NHS organisations, that level of operational control is becoming increasingly important as AI adoption matures.
The future of NHS AI will depend on governance and operational control
AI is already becoming part of day-to-day healthcare operations across the NHS. The benefits are measurable, and adoption will continue to grow.
But the organisations that scale AI most successfully are likely to be those that establish strong foundations around governance, resilience, and operational control from the beginning.
Sovereign AI provides a framework for doing exactly that. It enables NHS organisations to modernise and innovate while maintaining trust in how patient data, AI models, and operational environments are governed.
The next phase of NHS AI adoption will not simply be defined by access to AI capabilities. It will be defined by how securely, responsibly, and confidently organisations can apply those capabilities while maintaining control over patient data and operational environments.
For many NHS organisations, that increasingly means bringing the AI to the data, not the data to the AI.
Reference: https://go.rackspace.com/en-gb/lp/dl/healthcare-survey-26
