Painters and decorators
Those working in this unit group apply paint, varnish, wallpaper and other protective and decorative materials to interior and exterior walls and surfaces, paint designs on wood, glass, metal, plastics and other materials, and stain, wax and French polish wood surfaces by hand.
Task Bundle Breakdown
How AI interacts with this occupation's task bundle
Task-by-Task Breakdown
Every task scored individually — sorted highest to lowest AI exposure
mixes adhesive or removes self-adhesive backing and positions covering material on wall, matching up patterns where appropriate and removing wrinkles and air bubbles by hand or brush
Wallpaper hanging is a highly tactile, physical skill; AI-powered room visualisation tools (e.g. Dulux Visualizer) can help with pattern selection but cannot perform the physical application.
prepares surfaces by cleaning, sanding and filling cracks and holes with appropriate filler
Surface preparation is entirely hands-on physical work; AI might assist with identifying surface defects via image analysis apps but cannot perform the sanding or filling.
applies primer, undercoat and finishing coat(s) using brush, roller, or spray equipment
Applying paint coatings requires skilled manual technique and on-the-spot judgement about coverage and finish; robotic painting exists in factories but not in general decorating contexts.
stains, waxes and French polishes wood surfaces by hand
French polishing and hand-finishing wood is a craft skill requiring fine motor control, sensory feedback, and years of experience that current AI and robotics cannot replicate.
erects working platform or scaffolding up to five metres in height
Erecting scaffolding and working platforms requires physical presence, manual dexterity, and real-time safety judgement that AI cannot replicate.
ROI Calculator
Painters and decorators
This is not a pay rise — it's 90 hours of productive capacity that AI could return to you, valued at your current rate.
The portion of your current salary tied to tasks AI can automate or augment. Not a prediction of job loss — a signal of where your role is changing fastest.
How is this calculated?▾
Task weights — each task is weighted by its O*NET frequency rating. Where frequency data is absent, equal weighting is applied.
AI time reduction — tasks scored as "AI Automates" assume 80% time saving; "AI Assists" assumes 40%; "Human-Led" assumes 5%.
Salary equivalent — annual hours saved × (salary ÷ 1,800 working hours/year).
Value at risk — salary × share of role time in AI-automate or AI-assist tasks.
Figures are indicative estimates for planning purposes, not guarantees of productivity gain or job loss risk.