OneAdvanced's CTO on Embedded AI and Fragmented Systems

OneAdvanced is a UK company providing software and SaaS solutions that reach millions of people daily. 

On its website, OneAdvanced claims to manage 1.5 million calls for NHS 111 every month, which is the non-emergency telephone number of the UK's health service. 

The company says it is working with 4,000 legal practices, helping their clients with the important matters in life. 

In April, the company announced IQ – which it calls "the intelligent system of work".

The company says it brings together processes, data, policies and AI on a sovereign platform. Work, it says, can be augmented with AI and agentic capabilities, across multiple workflows and datasets, all whilst complying with policy and corporate guardrails. 

AI Magazine spoke to its Chief Technology Officer, Andrew Henderson, to discuss IQ, whether AI tools are delivering impact yet and whether AI can improve productivity and decision-making. 

Many organisations are investing heavily in AI but are still struggling to achieve meaningful impact. Why is that?

Many organisations have treated AI as a layer they can simply “add on” to what they already have, rather than rethinking how work happens with AI at the core.

You see significant investments in pilots, proofs of concept and isolated use cases, but they sit on top of fragmented systems, inconsistent data and disconnected workflows – often without a clear definition of the outcome that will deliver value to end users.

The result is that AI solves localised problems in pockets of the business, without changing how work flows end-to-end. Until organisations address the underlying architecture – how data, applications and processes are connected – it's difficult to move from experimentation into meaningful, scalable impact.

Many organisations have added more tools to try to address this. Why is this not delivering the results they expect?

Adding more tools into an already complex environment usually makes the problem worse, not better. Each new AI tool comes with its own data connections, permissions, interfaces and governance requirements.

If those tools aren't orchestrated through a single platform, you end up with a sprawl of capabilities that don't work together.

For users, that means more context-switching and more friction. For leadership, it means higher costs with limited visibility or control.

The value doesn't come from the number of tools you have, but from how well they're connected, how they safely share data and how effectively they support the workflows that matter to the organisation.

OneAdvanced has recently launched a new platform – IQ – which you describe as an “intelligent system of work”. Does this reflect a broader shift in how organisations need to approach AI and enterprise systems?

We're seeing a clear shift across the market: organisations are moving away from thinking in terms of individual applications and towards systems of work – how processes run end to end across an organisation.

Leaders are asking less about what a product does in isolation, and more about how it supports entire workflows, from lead-to-cash to patient pathways.  

That shift requires platforms that bring together data, workflows and AI onto a unified platform, so that intelligence is embedded into the flow of work rather than bolted on top.

Our approach with IQ reflects that thinking – connecting our own applications and third-party services, and then layering in AI in a way that is secure, governed and context-aware.

What does it mean to embed AI into the architecture of systems, and how does that improve productivity and decision-making?

Embedding AI into the architecture means AI isn't just a feature in one screen or a chatbot – it's woven into the data fabric, the workflow engine and the user experience.

The platform understands roles, permissions, processes and context, allowing AI agents to operate across the whole environment rather than being confined to a single task.

That changes productivity and decision-making in a few important ways:

• Proactive insight: Systems surface relevant signals at the right time, tailored to their role, rather than relying on users to go looking for information
• Context-aware automation: Workflows adapt based on real conditions – data, exceptions and constraints, rather than following rigid, predefined paths
• Democratised expertise: Complex analysis or specialist tasks can be made accessible through natural language and guided experiences, so more people can make high-quality decisions without needing deep technical training.

When AI is part of the architecture, it stops being a novelty and becomes part of how the organisation thinks, decides and executes every day.

Your customers operate in sectors such as healthcare, government and education. How can a platform like IQ improve real-world outcomes in these environments?

In critical sectors such as these, the stakes are very real. It's not just about efficiency – it's about patient outcomes, public services and learner success.

A platform like IQ can make a difference because it connects day-to-day operations – the operational reality, appointments, caseloads, budgets, staffing, compliance – with intelligent insights and orchestration.

For example, in healthcare, that can mean coordinating patient journeys across multiple systems, surfacing earlier risk indicators and supporting clinicians with better information at the point of care. In government, it can support streamlined case management, reduce duplication and give frontline teams a clearer view of needs.

In education, it can bring together data on attendance, performance and well-being to support more timely interventions.

Crucially, IQ is designed with governance, security and data autonomy at its core. That's essential in regulated environments where trust, auditability and control are non-negotiable.

Does the move towards more connected, AI-enabled systems signal a broader shift in SaaS and the emergence of a new model for enterprise platforms?

Yes, I think we're seeing the next phase of SaaS.

The first wave was about moving individual applications to the cloud. The next wave focused on connecting those applications into coherent platforms.

Now we're entering a phase where intelligence is the organising principle: platforms are expected not just to host applications, but to orchestrate data, workflows and AI in a unified way.

In this model, organisations are no longer looking for standalone products, but for an operating backbone that can support how their business operates.

That backbone needs to be open enough to integrate other services, intelligent enough to adapt and learn, and effectively governed enough to be trusted with their most critical processes.

IQ is our expression of that new model: an intelligent system of work that can evolve with an organisation's operating model, rather than forcing them to bend their business around the limitations of individual tools.