From AI adoption to an AI-literate workforce.
Mexty AI Literacy for Business
Help every employee use AI productively, critically and responsibly — with editable learning paths, hands-on experimentation, company-grounded knowledge and meaningful assessments.
The challenge
Using AI every day doesn't mean understanding it.
Employees may be fast with a chatbot while still overlooking inaccurate answers, sensitive data, biased recommendations or the limits of automation. AI literacy turns access to technology into informed workplace capability.
Reliability, not just speed
Know how to recognise hallucinations, inspect sources and validate important claims before they affect business decisions.
Responsible use
Practise privacy, confidentiality, fairness, workplace integrity, and appropriate human oversight.
Productivity with judgment
Choose appropriate tools, write purposeful prompts and apply AI where it adds value in the employee's actual role.
Learning progression:
Learning paths that fit your organisation
One shared foundation. Different learning for different roles.
Start with an editable core curriculum, then tailor examples, experiments and assessments to functions, seniority, policies and approved tools.
AI Foundations for Everyone
Establish a common standard for using AI effectively, critically and safely across the organisation.
- Generative AI and LLM basics
- Prompting and context
- Hallucinations and source verification
- Confidentiality and data protection
- Responsible use and human oversight
AI Literacy for Sales & Marketing
Use AI to support research and communication without compromising evidence, customer information or brand integrity.
- AI-assisted research and messaging
- Verification of market and competitor claims
- Customer and prospect data safety
- Brand, copyright and content review
- Approval and human accountability
AI Literacy for HR & People Teams
Explore workplace AI while protecting employee privacy and recognising the risks of high-impact recommendations.
- Appropriate AI assistance in HR
- Recruitment and screening bias
- Personal and sensitive information
- Policy-grounded communication
- Human oversight and fair decisions
AI Literacy for Finance & Operations
Build confidence in AI-supported workflows without losing traceability, accuracy or control.
- AI-assisted document and data analysis
- Checking calculations and unsupported facts
- Confidential reports and approved tools
- Exceptions, controls and review steps
- When to escalate to human experts
AI Literacy for Managers & Leaders
Understand how to guide responsible adoption and evaluate where AI supports — or should not replace — human decisions.
- AI opportunity and limitations
- Governance and accountability
- Workforce capability and change
- High-stakes decision review
- Measuring learning and workplace outcomes
Illustrative learning-path architecture. Content and scope are editable to fit company requirements.
AI Literacy Lab
Don't just tell employees about AI risks. Let them experience and investigate them.
Turn abstract concepts into structured, workplace-relevant experiments that invite participants to compare, check, explain and decide.
Experiment 01 — Same task, different AI
Compare outputs from different models. What assumptions, evidence, gaps and levels of certainty change?
Experiment 02 — Find the hallucination
Review an AI-generated competitor brief and identify claims that need independent verification.
Experiment 03 — General answer vs. company policy
Explore the difference between a plausible generic response and one grounded in approved internal documents.
Experiment 04 — Human judgment in the loop
Examine an AI recommendation affecting a customer, colleague or supplier. What should a person review?
Additional topics:
The Mexty learning infrastructure
Everything L&D needs to create, deliver and assess employee AI literacy.
Connect learning content, experiential activities, relevant company knowledge and evaluations in one editable programme.
Editable learning paths
Organise lessons, exercises and evaluations into coherent programmes for teams and departments.
AI-assisted authoring
Create and adapt courses from learning objectives and existing resources while maintaining human editorial control.
Interactive activities
Make policies and concepts tangible through branching decisions, quizzes, sorting tasks and practical challenges.
Trusted knowledge sources
Bring selected internal policies and documentation into learning experiences using knowledge bases and grounding.
Evaluations
Combine scored formats such as quizzes, decision paths, categorisation, visual tasks and confidence checks.
Progress visibility
Assign learning, monitor participation and use evaluations to see where further enablement is needed.
Turn your AI policy into employee capability.
Use your approved documents, processes and examples to make training relevant — not generic.
A practical rollout
Start focused. Learn from the pilot. Scale with confidence.
- 01
Define
Identify target groups, approved AI tools, policies and learning objectives.
- 02
Adapt
Tailor editable paths to roles, internal resources and company-specific scenarios.
- 03
Pilot
Run practical labs and evaluations with an initial team or department.
- 04
Expand
Use feedback and learning evidence to refine and roll out across the workforce.
Frequently asked questions
Plan the right AI literacy programme.
Is this only a prompt-engineering course?
No. Prompting matters, but AI literacy also covers model limitations, output verification, company data, bias, responsible use and human oversight.
Can we tailor training to our internal AI policy?
Yes. L&D can edit the programme and incorporate selected internal policies and reference documents into learning activities.
Does every department need the same training?
A shared foundation creates consistency. Role-based modules then address the real tasks and risks faced by Sales, HR, Finance, Operations and leaders.
How do we assess practical understanding?
Use a mix of knowledge checks, scenario-based decisions, classification, confidence checks and tasks requiring participants to examine and verify outputs.
Can we start with a small pilot?
Yes. Begin with one team or department, collect learner and facilitator feedback, then adapt the learning path before extending it more widely.
Give your people the confidence to use AI — and the judgment to question it.
Editable learning paths. Role-based training. Practical experimentation. Company-grounded knowledge. Evaluations and progress tracking.
