Clear definitions of every term used on Xtell — from displacement risk to SOC codes.
A role where AI software agents handle most of the cognitive work and humans act as supervisors who monitor outputs and intervene when needed. Displacement risk is high for those performing tasks the agent now handles. Examples include automated content curation and automated customer service functions.
A role where AI agents and robots work together to complete tasks with minimal human intervention. Human roles are reduced to high-level oversight, system management and edge-case resolution. Examples include fully automated supply chain fulfilment.
The degree to which a professional role involves tasks that AI could perform or significantly assist with. A role with high AI exposure has a large proportion of its typical task composition within reach of current or near-term AI capabilities. AI exposure does not automatically mean displacement — it can also mean amplification.
A measure of how deliberately and strategically a professional uses AI tools in their work. Research by KPMG and the University of Texas published in Harvard Business Review in March 2026 found that only around 5% of professionals use AI sophisticatedly — treating it as a reasoning partner rather than a shortcut. AI sophistication is assessed in the Xtell profile and is distinct from basic AI familiarity.
A five-dimension assessment of how a professional is wired to navigate the AI era. Generated by the Xtell Career Navigator Quiz, the profile scores across Awareness, Adaptability, Ambition, Anchoring and Autonomy and displays results as a unique pentagon radar chart. Free to take at /quiz.
The process by which professionals working in tracked roles contribute their own assessment of Xtell's scores. Through the Add Your Professional View feature on every role page, professionals can validate or challenge the displacement risk score, select the McKinsey archetype that best describes their role, and assess the extension score and human primacy index based on lived experience.
A UK Government classification for occupations with substantially higher demand than usual across multiple indicators. Classifications are published annually by the Department for Education in the Occupations in Demand release. In 2025, 62 occupations were classified as Critical demand, covering 5.1 million workers.
A classification of current employer demand for workers in a given occupation, published annually by the UK Government Department for Education. Xtell displays demand level classifications on role pages where a reliable SOC 2020 code match exists. Three levels: Critical demand, Elevated demand, Not in high demand.
The proportion of a role's typical task composition that AI, automation or robotics could perform, expressed as a percentage. A score of 0% means the role has no tasks currently automatable by AI. A score of 100% means every typical task in the role could be performed by AI. Scores are directional assessments informed by published research and calibrated against the UK Government DSIT AI Occupational Assessment methodology.
The UK Government's Department for Science, Innovation and Technology official assessment of AI's impact on UK occupations, published in January 2026. The most comprehensive government assessment of AI capabilities and UK labour market impact to date, published under Open Government Licence v3.0. Xtell's displacement risk methodology is calibrated against this assessment.
A UK Government classification for occupations with above average demand across multiple indicators, but below the threshold for Critical demand. In 2025, 125 occupations were classified as Elevated demand, covering 10.9 million workers.
A proprietary Xtell score measuring how much AI amplifies the capability and productivity of a skilled professional in a given role. A high Extension Score means professionals who embrace AI tools can do significantly more, faster and to a higher standard. The Extension Score recognises that AI is not only a displacement threat but a capability multiplier. Proprietary to Xplorient Limited, first published March 2026.
A proprietary Xtell score measuring how important it is that a role remains distinctly human, ethically, practically or commercially. Accounts for the fact that technical capability to automate does not equal social or ethical appropriateness of automation. A score of 100% means the role should remain distinctly human regardless of what AI could technically do. Proprietary to Xplorient Limited, first published March 2026.
A framework developed by McKinsey Global Institute describing how AI and automation are changing the balance between human workers, AI software agents and physical robots in different roles. Xtell classifies every tracked role against one of seven archetypes: People-Centric, People-Agent, People-Robot, People-Agent-Robot, Agent-Centric, Robot-Centric and Agent-Robot-Centric.
A UK Government classification for occupations where demand indicators are at or below average levels. This does not mean a role is in decline — it means current employer demand signals are not elevated relative to the workforce size.
The status assigned to Xtell roles that have no reliable ONS SOC 2020 code match. This applies primarily to emerging roles that postdate the SOC 2020 framework, including Prompt Engineer, XR Developer and AI Ethics Lead. Xplorient Limited submitted evidence to the ONS SOC 2030 consultation in March 2026 calling for dedicated classification codes for these roles.
An annual UK Government publication by the Department for Education assessing demand levels across 368 UK occupations. Uses five indicators: online job advert density, visa grant density, wage premium, annual change in hourly wage and annual change in hours worked. Xtell displays demand level classifications sourced from this dataset on individual role pages.
A role where humans work alongside AI software agents that provide real-time guidance, recommendations or automation of specific subtasks. The human leads and the agent assists. Examples include knowledge workers using AI copilots and customer service representatives with AI-assisted resolution tools.
A role where humans handle most of the work, using AI as a supporting tool rather than a replacement. Human judgment, relationships and presence remain central. Examples include complex sales roles and senior advisory positions.
A role where humans work alongside physical robots that handle specific tasks, particularly repetitive or physically demanding work. The human provides oversight, judgment and adaptability. Examples include maintenance technicians and hospital workers.
A role where humans manage both AI software agents and physical robots. The human role shifts toward coordination, oversight and exception handling. Examples include surgeons using robotic assistance and advanced manufacturing operators.
A role where robots perform most of the physical work. Humans manage, maintain and oversee the technology rather than performing tasks directly. Examples include automated production lines and warehouse picking systems.
Xtell's assessment of how a role's McKinsey archetype is likely to shift based on current market signals and near-term trajectory. Displayed on every role page and the user dashboard. Directional intelligence to inform career planning, not a definitive prediction.
A classification of how a role is changing in response to AI and automation. Four statuses: Role Evolving (changing significantly but surviving), Role Shifting (transforming into something meaningfully different), Stable (limited change expected near-term) and Growing (increasing demand driven partly by AI adoption).
A UK Government body responsible for identifying and addressing skills gaps in the UK workforce. Xtell integrates data from the Skills England public API to populate role overviews and green job classifications on role pages.
The UK's official occupation taxonomy, published by the Office for National Statistics. Classifies all UK occupations into unit groups using four-digit codes. Xtell maps all tracked roles to SOC 2020 codes to enable integration with government datasets including the Occupations in Demand publication and ONS ASHE salary data.
The next revision of the UK Standard Occupational Classification, currently in development by the ONS. SOC 2030 is expected to include classification codes for occupations that emerged after SOC 2020 was published, including AI-adjacent and immersive technology roles. Xplorient Limited submitted evidence to the SOC 2030 public consultation in March 2026.
Xtell's proprietary three-dimensional framework for understanding AI's impact on professional roles. Tracks Displacement Risk, Extension Score and Human Primacy Index simultaneously, displayed as three horizontal gauge bars on every role page and as a triangle visualisation on desktop. Developed by Xplorient Limited and first published March 2026. The Extension Score and Human Primacy Index are proprietary to Xplorient Limited.
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