Capability
AI Capability & Enablement
Assess and develop the human capabilities that drive effective, responsible, and value-creating AI use across leaders and teams.
The capability gap
Most organisations have the tools.Far fewer have the human capability.
The gap is no longer access. It is whether people can integrate AI into work, judge outputs properly, and direct it toward real value.
What organisations have
- •AI tools and automation platforms
- •Data pipelines and integration layers
- •Vendor agreements and access licenses
- •Usage policies and governance frameworks
What organisations need
- •Judgement and critical thinking in AI-assisted decisions
- •Adoption discipline and workflow integration
- •Output auditing and accuracy calibration
- •Operating model design for human-AI collaboration
What we assess
Four signals that determine whetherAI use improves performance.
Exploration and integration
Whether people experiment with AI use cases and build repeatable workflows — or default to one-off interactions with limited carry-over.
Critical AI judgement
How rigorously people evaluate AI outputs for quality, logic, and risk before acting on them.
Value targeting
Whether people direct AI effort toward tasks where it creates genuine improvement — and redirect when value does not materialise.
Learning agility
How quickly people improve through use, adapt as tools evolve, and transfer learning across different workflows.
Recruitment application
Strengthen hiring quality for AI-exposed roles.
The AI Capability Index gives hiring teams a sharper read on who can use AI well in real work, not just talk confidently about it.
Compare observable behaviours
Evaluate how candidates verify output quality, structure workflows, and navigate model limits under pressure.
Reduce mis-hire risk
Flag overconfidence, novelty-driven usage, and weak critical evaluation before appointment decisions are made.
Hire for performance readiness
Select people who can convert AI use into measurable outcomes and operational consistency.
Built on LQ AI Capability & Enablement
A structured model for human capability in AI-augmented environments.
LQ AI Capability & Enablement is the framework behind this work. It measures whether AI use strengthens judgement, execution quality, and learning, or simply adds noise.
Explore LQ AI Capability & EnablementHow delivery works
Delivered as a practical enablement layer,not just another training program.
AI orientation baseline using the AI Orientation Survey across leaders and teams
Capability measurement via the AI Capability Index across five capability areas
Risk and gap analysis across judgement, integration, and learning agility
Targeted enablement design aligned to role demands and strategic priorities
Best suited to
- •Executive teams embedding AI across core workflows and decision processes
- •Leaders responsible for quality decisions in AI-augmented environments
- •People and transformation teams building AI capability at scale