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      A new currency for work

      For decades, job titles were the shorthand for value in the workplace. They dictated where people sat, what they did, and how they moved. But in a climate where markets shift overnight, technology changes the rules mid-game, and new skills emerge faster than old one's fade, titles are starting to feel… outdated.

      Skills are quickly becoming the true measure of capability. They provide a more accurate, flexible view of what someone can contribute—both today and tomorrow. This shift is already in motion: forward-looking organisations are redesigning workforce planning, learning strategies, and even reward systems around capability frameworks and task-based allocation—allocating tasks to resources, not people to jobs.

      louise-scott-worrall
      Louise Scott-Worrall

      Head of Learning Services

      KPMG in the UK

      Why the shift can’t wait

      The urgency is real. Workforce studies suggest that by 2030, as much as 22% of current roles could be significantly reshaped or disappear entirely. This isn’t a slow drift—it’s an accelerating trend driven by automation, AI, and changing customer needs. Some leaders are already preparing for it by rethinking operating models and creating internal talent marketplaces. These digital ecosystems let them allocate tasks to the most suitable resource, whether human or AI agent, in days rather than months. The outcome? More agility, less dependency on external hiring, and stronger engagement because people see a pathway to growth without having to leave.

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      The pressures driving change

      • Technology’s fast track

        Automation handles repetitive work, putting a premium on capabilities like problem-solving, creative thinking, and relationship-building.

      • Shorter market cycles

        Consumer behaviours and competitive pressures evolve in months, requiring faster redeployment of talent and task allocation.

      • Employee expectations

        Many professionals now value varied experience, skill-building, and cross-functional exposure over climbing a single career ladder.

      • Talent scarcity

        Skills audits often reveal existing employees with untapped potential, allowing organisations to allocate tasks internally rather than hire externally.

      One major research organisation applied this thinking when facing over 600 specialist vacancies. By mapping existing skills, they discovered that more than 150 roles could be filled immediately from within, while another 300+ could be met through targeted upskilling—slashing external hiring needs by more than half.

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      What a skills-based organisation looks like

      At its core, a skills-based organisation is fluid. Project teams aren’t formed around job titles—they’re tasks and the capabilities needed to deliver them.

      A team solving a market-entry challenge, for instance, might combine data storytellers, regulatory navigators, and customer experience designers—drawn from different departments but united by capability. Skills are continuously mapped, updated, and linked directly to development opportunities so that the workforce is always “deployment ready.”

      With the advent of AI, organisations are now experimenting with agentic workforce models, where tasks are dynamically allocated between humans and AI agents. For example, an AI system might prepare insights from complex datasets, while human talent applies judgment, storytelling, and stakeholder influence. This granularity beyond skills—deciding not only which skill is needed, but whether a human or AI is best suited to complete the task—marks the next evolution of workforce agility.

      The four building blocks

      • Speak the same language

        Establish a shared skills-and-task taxonomy to avoid ambiguity.

      • Know your strengths

        Use diagnostics that assess both human and AI readiness at the task level.

      • Enable with tech

        Implement platforms that connect task data with learning, mobility, and AI orchestration.

      • Change the culture

        Reward adaptability, task agility, and collaboration between human and digital colleagues.

      The pitfalls to avoid

      Enthusiasm alone doesn’t guarantee success. Common missteps include:

      • Governance silos

        Without alignment across HR, operations, and tech, skills data sits unused.

      • Legacy systems

        Older HR platforms may not support task-level allocation or AI collaboration.

      • Cultural resistance

        Titles can be tied to identity; shifts require careful change management.

      • Overcomplication

        Taxonomies with hundreds of skills overwhelm both managers and employees. A phased approach—focusing first on 50–100 strategically important capabilities—often drives better adoption and builds momentum for expansion.

      Proof it works: Real-world examples

      Facing critical shortages in research roles, a life sciences organisation audited its workforce. The findings were revealing: 157 employees could step into open roles immediately, 339 could do so with targeted upskilling, and only 111 needed external recruitment. The approach reduced cost, accelerated delivery, and boosted morale.

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      One UK university transformed its student service model by mapping staff skills to service needs, integrating digital tools, and retraining in priority areas. The results included faster response times, improved student satisfaction, and more efficient service delivery.

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      In some corporate programmes, new analyst training has been reimagined as immersive, real-world simulations. These initiatives have achieved satisfaction ratings above 90%, boosted productivity, and improved retention—demonstrating that hands-on, skills-focused learning works far better than static classroom training.

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      Looking ahead: The AI factor

      Generative AI and agentic technologies are expected to reshape nearly half of all workers’ core tasks within five years. The challenge is no longer just about identifying skills—but about deciding which resource—human or AI—is best suited to deliver each task.

      Organisations prepared for this shift are already running capability assessments, planning reskilling programmes, and setting up internal “gig” markets so employees can test new skills on short-term projects.

      Organisations already preparing for this shift are:

      • Running task-level capability assessments.
      • Designing reskilling programmes focused on human-only skills such as creativity, ethics, and strategic judgment.
      • Deploying AI agents for repetitive, high-volume or analytical tasks.
      • Establishing internal “gig” marketplaces where tasks are dynamically distributed between humans and AI.

      Making the shift happen

      Transformation requires more than enthusiasm—it demands structured workforce design, robust diagnostics, and enabling technology. The right partner can help:

      • Design workforce architecture

        Aligned to task and capability needs.

      • Run diagnostics

        That measure both human and AI readiness.

      • Implement enabling platforms

        Such as LEAP (Learning Enablement & Analytics Platform), which connects tasks, skills, and learning in the flow of work.

      • Apply ethical AI frameworks

        To build confidence in human-AI collaboration.

      • Guide cultural change

        To embed adaptability and agentic teamwork.

      Your next move

      The shift to skills and task first organisation is no longer optional—it’s essential. Those that act now will be better equipped not only to withstand disruption but to thrive because of it.

      If you’re ready to explore your capability roadmap and understand how to allocate tasks across people, roles, and AI agents, start the conversation today.

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