Many organisations are moving decisively to shift AI from experimental mode to a core enterprise capability.
In OneAdvanced’s 2026 Trends Report, almost 54% of senior leaders identified AI adoption and integration as their top investment priority, a clear signal that AI is no longer viewed as an optional innovation but as critical infrastructure for competitiveness. Yet despite the ambition many leadership teams are struggling to successfully embed AI across end-to-end processes, highlighting the widening gap between aspiration and execution.
Even companies that consider themselves ahead of the curve are encountering problems when they try to scale AI. The Trends Report highlights this gap clearly: while 59% of leaders believe they are aligned with or outperforming their closest peers on AI maturity, nearly half, 49%, also acknowledge that AI currently supports less than a quarter of their operational activity. This contrast underscores a growing reality for the C-suite: confidence in AI strategy is high, but meaningful enterprisewide adoption remains limited, and the distance between ambition and execution is widening.
This failure to scale AI and truly transform work is not a result of problems with models or lacklustre tools. It’s because of disjointed workflows, poor platform integration, and limited visibility, all of which make it almost impossible to orchestrate AI properly.
Layering more AI tools on top of fragmented IT estates only adds to this complexity. “Some people think AI is a magic bullet that they can just apply across the organisation and everything will miraculously become better,” says Marko Perisic, chief product officer at OneAdvanced. “But when you apply AI across these legacy, disconnected systems – which don’t have good data hygiene, don’t have permissions and security controls – you end up with a mess, which is why it’s so essential to take a structured, platform-driven approach.”
Essentially, organisations need to shift from siloed software systems to a suite of solutions, all operating on a unified platform. They also need to look beyond using AI for specific tasks like summarisation and explore how it can truly generate value across entire processes. To address this, they must stop thinking about individual tools as isolated islands and layer them into an intelligent system that understands the full context of key business processes and workflows, and can also handle all the complexities of a fully integrated software environment.
Unified data, personalised insights
In April, OneAdvanced is introducing IQ, which exemplifies this shift from the delivery of software portfolios to an intelligent system of work. It is designed as an interconnected, scalable architecture for all industries, combining a delivery platform, composable workflows, services and seamless user experiences.
Unified data is effectively the foundation that supports all these capabilities. “With AI, you’re going to value integration over point-to-point functionality – and to realise that, you need to unlock data via a common fabric, with common access and common security controls,” says Andrew Henderson, chief technology officer at OneAdvanced.
Because OneAdvanced’s platform is built around a shared data layer, AI agents can easily access the information they need to operate across workflows, teams and departments. A robust API and integration management layer also supports pre-built connections for both OneAdvanced applications and third-party tools. The result is a system that delivers a single version of the truth, which in turn provides the trust and compliance that is essential for scaling AI.
AI agents can easily access the information they need to operate across workflows, teams and departments
The platform’s interconnected, scalable architecture is also designed around the requirements of each user. “If you’re a CFO, what do you deeply care about? The answer is not, ‘I care about my general ledger posting’,” says Perisic. “What you care about is your entire lead-to-cash process, so a solution that addresses that owns their attention.”
The same logic applies across the C-suite: a CHRO needs visibility of the full hire-to-retire journey; a COO requires real-time operational insight across every function; and a CIO needs to see the integration layer holding it all together. To address all these needs, IQ by OneAdvanced provides a persona-based experience – i.e. role-aware insights that don’t require the user to navigate between different systems. In other words, it’s essentially about making software invisible so that leaders can focus on the big strategic decisions.
AI embedded into an intelligent system of work also supports better access to insights that can generate real business value. Indeed, while AI is often presented in terms of its automation benefits, some of the most significant improvements may come from the democratisation of expertise.
By transforming what were once static interfaces into context-aware, intelligent agents, complex tasks that previously required specialist training or tools can be performed by a wider range of employees, for example. “It enables different functions to do things they could never do before,” says Perisic. He backs up this point with a personal example: “I’m literate on financial P&L, but I’m not a financial expert. Now, when faced with a complicated Excel sheet, I can actually get an opinion about it without having to engage anybody in finance.”
Modelling success
OneAdvanced’s approach to AI does not rely on generic large language models (LLMs) alone. Alongside standard LLMs, the platform features sector-specific small language models (SLMs) purpose-built for the particular language, regulation and workflows of industries such as healthcare, legal and education. Pre-built, deployable agents, designed for immediate use without specialist configuration, are also available through OneAdvanced’s AI agents marketplace, enabling organisations to scale and orchestrate AI based on their specific circumstances, goals and governance requirements.
In February 2026, OneAdvanced also became one of fewer than 100 organisations globally to receive ISO 42001 certification, the international standard for AI management systems. For customers operating in regulated sectors, the certification provides external validation that OneAdvanced meets a recognised standard for AI governance – particularly significant at a time when many organisations face growing regulatory, contractual and ethical pressure to provide evidence of how AI is used. All data is also processed and stored within the UK, providing full compliance with data sovereignty requirements.
Ultimately, good governance is not simply about having “guard rails around what the AI is doing, but also what the humans are doing,” says Henderson. “Access controls, compliance objectives, and more needs to be built into the context as well. You need to control exactly who is doing what, when and how, at quite a fine-grained level of fidelity – down to the micro-process, and all the way up to an end-to-end workflow.”
Despite the speed and efficiency benefits of AI running on an integrated platform, the ultimate responsibility for business outcomes will remain in the hands of human employees. “AI will do a lot of things for us,” says Perisic. “But we will maintain ownership of the results, because AI will not be held responsible for the outcome of a failed process.”
Ultimately, the capabilities of IQ by OneAdvanced will help to shift organisations toward truly valuable agentic workflows, which are very different to traditional automation. “Traditional automation is a very mechanical, rigid process – brittle, because it’s contextually unaware,” says Perisic. “It will just keep doing the same mechanical thing regardless of whatever else happens around it.” AI-driven orchestrated workflows are different because AI understands context. “They can adapt to a situation, understand different data, and adjust along the way. That’s what makes them so magical.”
The digital transformation age wasn’t as impactful as everyone thought it was going to be
As such, organisations that manage to overcome the integration challenges of AI through intelligent orchestration won’t just end up automating rote tasks. Instead, they’ll be able to elevate entire workflows to a new level of performance and purpose. “People today both overestimate and underestimate the power of AI,” Perisic concludes. “They think it’s going to solve everything. But at the same time, they underestimate how much orchestrated workflows can actually change things.”
The real breakthrough will not come from deploying more AI tools, but from orchestrating them within a unified system of work. Organisations that integrate platforms, data and workflows into a coherent whole will move beyond fragmented experimentation – embedding intelligence into everyday operations and unlocking the transformational value AI promises.
Q&A: Navigating the future architecture of work
As AI reshapes how work is done, Marko Perisic, chief product officer, and Andrew Henderson, chief technology officer at OneAdvanced, discuss how intelligent platforms will underpin the next generation of enterprise operations
AI is moving rapidly from pilot projects to core business operations. But for many organisations, progress has stalled at the point of scale, where fragmented systems and disconnected workflows make it difficult to translate early success into enterprise-wide impact.
The next phase of adoption will depend less on individual tools and more on how organisations bring together data, applications and intelligence into a cohesive system. That shift is beginning to redefine how work is structured, how decisions are made and how value is created.
What is your long-term vision for OneAdvanced IQ and the future architecture of work?
Looking ahead, the vision is that we are the intelligent backbone for our customers to run their businesses, whether through our own native services or through the ability to integrate other services into the platform. We should be enabling the operating models of our customers to really scale. Our vision is for customers to trust and rely on us to deliver that with resilient security, and with ease, so they’re not having to worry about long-running upgrades of products. Because the evolution of their own business model is going to be quite profound. They don’t want to be worrying about which LLMs they’re using or which cloud hosting services they rely on.
How do you see the relationship between people, data and intelligence evolving over the next five years?
The digital transformation age wasn’t as impactful as everyone thought it was going to be. But the step to this AI-driven world is much more intuitive for humans than what came before. With natural language interfaces, people can get comfortable enough and confident enough to deploy things at scale within their business. So it’s adding a much more human factor. But we’ve got to really help our customers learn, understand and trust this technology. We also have to recognise that human workers are not going to go away, so how do we make the transition more seamless for them?
What early customer signals give you confidence that the intelligent system-of-work model is the right direction?
The digital transformation age wasn’t as impactful as everyone thought it was going to be. But the step to this AI-driven world is much more intuitive for humans than what came before. With natural language interfaces, people can get comfortable enough and confident enough to deploy things at scale within their business. So it’s adding a much more human factor. But we’ve got to really help our customers learn, understand and trust this technology. We also have to recognise that human workers are not going to go away, so how do we make the transition more seamless for them?
How will embedded AI reshape decision-making and operational performance across industries?
You can accelerate the speed at which you produce content, analyse things, build a piece of code – to the point where it’s near-instantaneous compared to what it used to take. So all the typical behaviours around design thinking, where you’d spend weeks or months thinking about something with a large group of people because you didn’t want to waste that time – that changes. Now you can just give something a go, see what it tells you, and get something back.
So we’re going to move more into the space of safe experimentation: try things out, learn from high-quality signals, and rapidly adjust, rather than the big design-thinking approach. And our platform supports that: you can just try something, see how it works, and adjust.
What does success look like for organisations that fully embrace intelligent orchestration?
It really changes the way we work: we can actually complement each other and develop a deeper understanding of each other’s roles rather than just throwing things over the wall. So it enables different functions to do things they could never have done before. For example, even if I’m not an engineer, I don’t need engineering to build something for me. I can just quickly prompt and build what I need with AI.
Many organisations are moving decisively to shift AI from experimental mode to a core enterprise capability.
In OneAdvanced’s 2026 Trends Report, almost 54% of senior leaders identified AI adoption and integration as their top investment priority, a clear signal that AI is no longer viewed as an optional innovation but as critical infrastructure for competitiveness. Yet despite the ambition many leadership teams are struggling to successfully embed AI across end-to-end processes, highlighting the widening gap between aspiration and execution.
Even companies that consider themselves ahead of the curve are encountering problems when they try to scale AI. The Trends Report highlights this gap clearly: while 59% of leaders believe they are aligned with or outperforming their closest peers on AI maturity, nearly half, 49%, also acknowledge that AI currently supports less than a quarter of their operational activity. This contrast underscores a growing reality for the C-suite: confidence in AI strategy is high, but meaningful enterprisewide adoption remains limited, and the distance between ambition and execution is widening.
