While the use of artificial intelligence (AI) in the workplace has nearly doubled over the last two years, its best days undoubtedly still lie ahead.
No longer just associated with technology roles, AI is now entrenched in a variety of tasks, applications and professions, heralding the start of a new IT era. Our own research found that 56% of UK project-based firms have reached a mature or advanced stage of digital transformation, up from just 32% last year. Further, over a third list AI adoption and effective implementation as their top strategic priorities for the years ahead.
The benefits are ironclad. The long-term AI opportunity is estimated at $4.4 trillion in added productivity growth potential from corporate use cases. Unlocking this vast potential and shifting from experimentation to enterprise-level scaling, however, has uncovered a new skills gap, and one that cannot be filled by traditional technical roles alone.
As AI becomes ever-more embedded, organisations are realising that its momentum depends on human oversight, judgement, and coordination. The professionals at the helm – ‘AI orchestrators’ – are adept at guiding digital ecosystems rather than executing individual tasks. This capability is poised to define the next wave of competitive advantage.
From do to direct
The next era of AI will not be about automating tasks, but transforming how the work itself is structured. Rather than executing individual activities, employees increasingly sit above digital workflows, steering outcomes, validating context, co-creating, ensuring close alignment with business priorities, and exploring entirely new opportunities.
To illustrate, instead of manually updating schedules, reconciling data or tracking project milestones, staff are increasingly validating AI-generated insights, resolving exceptions and making judgement calls when context is required. They’re still accountable for outcomes, but the way they influence those outcomes is changing. For example, in project reviews that once took days of manual preparation, teams are now spending their time interrogating AI-generated insights, sense-checking anomalies and making forward-looking adjustments. The work hasn’t disappeared, but moved upstream, where human expertise has a greater impact on outcomes and expands on what is possible.
This shift is happening because automation is increasingly a part of everyday operations. As workflows become more interconnected, someone has to ensure that actions taken by different systems make sense together: that decisions align with client expectations, that data reflects reality on the ground, and that automated handoffs don’t drift from project goals. That responsibility naturally falls to the people who understand the work best.
In the most practical terms, this shift means project managers spending less time on administrative burden and more time directing delivery. Operations teams, meanwhile, may identify where AI should intervene and where human judgement is essential, while client-facing teams will use AI insights to shape conversations rather than simply report on past performance. These are the early signs of the orchestrator-style roles that will soon become standard across organisations embracing AI at scale. In time, orchestrators will unleash industry-tuned intelligence at every step of project lifecycle, creating context-aware insight right where it’s needed.
Why reskilling beats recruiting
As this evolution unfolds, organisations face a choice: compete in an already strained talent market or build the capabilities they need from within. Our research strongly supports the latter. While 40% of firms are prioritising AI to streamline project processes, they also perceive difficulty in attracting and retaining talent as holding back progress, with 49% stating it to be the second biggest employee-related issue.
To advance, businesses must combine AI investment with upskilling their people. This means expanding responsibilities within existing project management, operations and client teams, and embedding AI-orchestration tasks in day-to-day roles, rather than creating siloed specialist positions. Equally important is providing access to advanced technologies alongside structured learning, and fostering cultures of collaboration and innovation to support mindset change.
Orchestration emerges organically when people closest to the work are empowered to guide the technology shaping it. These individuals already understand project context, client nuance and organisational priorities, all areas in which AI alone cannot reliably judge or coordinate. Early indicators from research into agentic organisations shows non-technical staff often learn to manage AI-driven workflows as quickly as engineers once did.
Come 2026, organisations that create AI orchestrators will be able to coordinate complex projects at scale, personalise client engagements in real time, and shift resources dynamically as conditions change. As many predict what’s next for AI, evidence points to a future not defined by building more models, but by empowering people to direct them with greater confidence and creativity. As automation becomes the backbone of project delivery, organisations must move to empower their workforce to orchestrate intelligent systems with confidence, clarity and purpose.
The rise of the AI orchestrator is underway. And for those prepared to embrace it, it marks the beginning of the most significant productivity leap of the decade. Those who prepare their people to orchestrate AI, not merely adopt it, will define the next generation of architectural practice and help shape the next generation of practitioners.
