Interview With Andrew Henderson, Chief Technology Officer At OneAdvanced On Embedding AI Into Workflows

Tell us about IQ

IQ is a connected, trusted Intelligent System of Work, that brings together people, data and AI on one sovereign platform, so work moves faster, decisions are clearer and innovation happens with confidence.

IQ combines deep domain expertise with secure and contextual AI intelligence across workflows for organisations within highly regulated and essential service sectors. 

It is engineered to power the world of work, providing a single sovereign system for organisations to execute their most critical work with confidence, encompassing intelligent services, user experience, and workflows delivered on a platform which manages data, security and resilience. 

When our customers’ systems work smarter, their organisations work better.

Why does embedding AI into the flow of work matter more than adding standalone tools?

The last few years have seen an explosion of standalone AI tools; chatbots, copilots, assistants and point solutions. They’re impressive, but they often sit outside the systems and processes where work happens. That creates friction. Users are required to switch context, copy and paste data, or manually reconcile outputs. The result is that adoption stalls, and the promised productivity gains never fully materialise.

Embedding AI into the flow of work solves this. When intelligence is integrated directly into your system of work, it becomes part of the natural rhythm of the job. A finance professional doesn’t need to open a separate tool to analyse cashflow; the insight appears in the ledger. A caseworker doesn’t need to ask a chatbot for a summary; the summary is generated automatically when they open the file. A manager doesn’t need to run a separate forecasting model; the forecast is surfaced in the scheduling workflow.

This approach also ensures that AI is grounded in the right data. Standalone tools often operate on incomplete or ungoverned information. Embedded AI has access to the full, contextualised dataset of the system it lives within, which dramatically improves accuracy and relevance.

Finally, embedding AI reduces risk. When AI is part of the platform, it inherits the platform’s security, auditability and compliance controls. Organisations don’t have to worry about shadow AI or data leakage through unmanaged tools. Everything is governed, monitored and aligned with organisational policy.

In short, embedding AI into the flow of work turns intelligence from a novelty into a dependable, everyday capability.
 

How is data sovereignty shaping the way organisations approach AI today?

Data sovereignty has become one of the defining issues of enterprise AI adoption. Organisations want the benefits of AI, but they cannot compromise on where their data resides, how it is processed, or who has access to it. This is especially true in regulated sectors such as government, healthcare, legal services and education, areas where OneAdvanced has deep roots.

The rise of generative AI has intensified these concerns. Many organisations are rightly cautious about sending sensitive information to external models or global cloud services without clear guarantees around data isolation, retention and usage. They need assurance that their data will not be used to train public models, that it will remain within their jurisdiction, and that they retain full control over access and governance.

This is reshaping the enterprise AI landscape. Organisations are increasingly adopting hybrid and sovereign cloud models that combine the flexibility of the cloud with greater control over their data. Demand is also growing for private, domain-specific AI models that can deliver more relevant and reliable outcomes. 

At the same time, customers are holding technology providers to higher standards of transparency, expecting clear visibility into data flows, retention policies and model boundaries. Compliance, too, has become more than a regulatory requirement; it is now a key differentiator, with trust, governance and accountability playing an increasingly important role in AI adoption.

IQ was built with these realities in mind. It gives organisations the ability to choose where their data is processed, how models are deployed, and what governance controls are applied. AI cannot be transformative if it compromises trust, and sovereignty is now a core component of that trust.

Why build governance directly into the platform?

Governance is the backbone of responsible AI adoption. Without it, organisations risk inconsistent outputs, biased models, data leakage and regulatory breaches. Too many organisations try to retrofit governance after deploying AI, but that approach is both inefficient and unsafe. By embedding governance at the platform level, we ensure that every AI capability (no matter how small) is subject to the same standards of oversight, transparency and control.

Building governance into the platform also makes AI scalable. When governance is centralised and consistent, organisations can deploy new AI features across departments without reinventing the wheel each time. Model versioning, data lineage, access controls, audit trails and ethical safeguards are all applied automatically. Our certification to ISO 42001, the new global standard for AI management systems, reinforces this approach. It demonstrates that our governance framework isn’t just well-designed but meets the highest internationally recognised benchmarks for responsible AI.

Most importantly, embedded governance builds confidence. Employees trust AI more when it is explainable and accountable. Leaders invest more readily when they know risks are managed. Regulators engage more constructively when compliance is demonstrable. Governance isn’t a barrier to AI adoption, it’s the enabler that allows organisations to use AI safely, responsibly and at scale.