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AI TRAINING PROGRAMME: AI AS A GROWTH ENABLER, TECHNOLOGY AND HUMAN ASPECT, AND ORGANIZATIONAL ENABLEMENT

Disclaimer:
This training topic is currently available for in-house sessions only, with a minimum requirement of 5 participants. Public program sessions are not available at the moment. The public program date will be announced when scheduled.

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Course Overview

AI Training Programme: AI as a Growth Enabler, Technology and Human Aspect, and Organizational Enablement : This programme introduces AI as a practical growth enabler and explores the business, people, and organizational factors required for successful adoption. The programme covers how AI supports productivity, decision-making, customer engagement, and business performance while addressing trust, capability building, responsible use, and organizational readiness. Participants will identify use cases, assess enablement gaps, and draft a realistic adoption action plan for their teams or functions.

Course Objectives

  • Explain how AI supports business growth, productivity, and operational improvement.
  • Identify practical AI use cases relevant to different roles and business functions.
  • Understand the human, cultural, and leadership factors affecting AI adoption.
  • Recognise the organizational conditions needed to support AI enablement across teams and workflows.
  • Develop a practical AI adoption action plan for team or business use.

 

Learning Outcomes

  • Describe AI as a growth enabler in practical business terms and distinguish between hype and useful application.
  • Identify business areas where AI improves efficiency, quality, customer outcomes, or decision support.
  • Assess human factors such as trust, resistance, skills, role changes, and responsible use in AI adoption.
  • Explain organizational enablers such as leadership support, governance, capability building, and workflow integration.
  • Propose practical AI opportunities and adoption priorities for their organization or function.

 

Training Methodology
Trainer-led input, facilitated discussion, case-based learning, innovation tools practice, individual reflection, group exercise, presentation, and feedback.

Course Content

Day / ModuleDurationTopic CoverageLearning OutcomesMethodology
Day 1. Module 1
AI as a Growth Enabler		3 Hours
  • What AI is in a business context
  • AI and business growth
  • AI for productivity, customer experience, decision support, and innovation
  • Examples of AI use across business functions
  • Identifying quick-win opportunities
  1. Explain how AI supports growth and business performance
  2. Identify workplace use cases where AI creates value
  3. Distinguish between hype and practical AI application
Briefing, examples, discussion
Day 1. Module 2
AI Use Cases Across Business Functions		2 Hours
  • AI in communication, reporting, and meetings
  • AI in sales, marketing, and customer service
  • AI in HR, operations, and administration
  • AI in analysis and content development
  • Evaluating use cases by value and readiness
  1. Identify relevant AI use cases across functions
  2. Match AI applications to business needs and tasks
  3. Prioritise use cases based on impact and feasibility
Use case review, exercise
Day 1. Module 3
Technology and Human Aspect of AI		2       Hours
  • What technology enables AI adoption
  • Human concerns around AI
  • Trust, accuracy, ethics, privacy, and bias
  • Job redesign, reskilling, and human judgment
  • Responsible use and review of AI output
  1. Recognise both the technology and people factors in AI adoption
  2. Identify common human concerns linked to AI implementation
  3. Apply responsible-use principles when using AI in the workplace
Facilitated discussion, reflection
Day 2. Module 4
Organizational Enablement for AI Adoption		3 Hours
  • Leadership role in AI adoption
  • Policies, governance, and risk controls
  • Skills development and learning culture
  • Cross-functional collaboration
  • Workflow integration and change management
  1. Explain the organizational conditions needed for AI adoption
  2. Identify leadership, governance, and capability factors that enable AI success
  3. Assess readiness gaps in the current organization
Framework briefing, group analysis
Day 2. Module 5
Building an AI-Ready Team and Workplace		2 Hours
  • Change readiness and employee engagement
  • Building confidence and awareness
  • AI training priorities
  • Human-in-the-loop ways of working
  • Team-level AI adoption practices
  1. Identify actions needed to prepare teams for AI adoption
  2. Recommend learning and engagement approaches for staff readiness
  3. Define practical team practices for safe and effective AI use
Discussion, team planning
Day 2. Module 6
AI Opportunity Mapping and Action Plan		2 Hours
  • Mapping current business pain points
  • Selecting high-value AI opportunities
  • Group discussion and application exercise
  • Drafting an AI enablement roadmap
  • Presentation of team action plans
  1. Identify priority AI opportunities for business functions
  2. Develop a basic AI adoption and enablement plan
  3. Present a realistic next-step roadmap for implementation
Workshop, presentation, feedback

Proposed Two-Day Itinerary

DayTimeSessionRemarks
Day 19:00 AM – 9:30 AMOpening, introductions, programme overview, and expectations settingTrainer-led
9:30 AM – 12:30 PMModule 1. AI as a Growth EnablerInteractive input
12:30 PM – 1:30 PMLunch breakBreak
1:30 PM – 3:30 PMModule 2. AI Use Cases Across Business FunctionsUse case exercise
3:30 PM – 3:45 PMAfternoon breakBreak
3:45 PM – 5:45 PMModule 3. Technology and Human Aspect of AIDiscussion and reflection
Day 29:00 AM – 9:15 AMRecap of Day 1 and briefing for Day 2Trainer-led
9:15 AM – 12:15 PMModule 4. Organizational Enablement for AI AdoptionGroup analysis
12:15 PM – 1:15 PMLunch breakBreak
1:15 PM – 3:15 PMModule 5. Building an AI-Ready Team and WorkplaceTeam planning
3:15 PM – 3:30 PMAfternoon breakBreak
3:30 PM – 5:30 PMModule 6. AI Opportunity Mapping and Action PlanWorkshop and presentation
5:30 PM – 6:00 PMProgramme wrap-up, action commitments, and evaluationClose

Assessment and Evidence of Learning

Assessment MethodDescription
Pre-programme checkShort poll or trainer-led questioning to gauge baseline awareness and expectations.
In-class observationObservation of participant responses during exercises, discussions, and group work.
Group presentationPresentation of team outputs, opportunity maps, or action plans developed during the programme.
Action planningCompletion of an individual or team action plan for workplace application.

AI TRAINING PROGRAMME: AI AS A GROWTH ENABLER, TECHNOLOGY AND HUMAN ASPECT, AND ORGANIZATIONAL ENABLEMENT

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