Highlights
- Practical communication frameworks that work across feedback, direction, and change contexts
- Specific focus on communicating AI adoption to developers, analysts, and non-technical stakeholders
- Listening and empathy skills that strengthen authority rather than undermining it
- Scenario-based exercises tailored to participants’ real leadership challenges
- Immediate, actionable feedback from facilitators on language, tone, and impact
Course Details
Module 1: Communicate Clearly, Even Under Pressure
- Plan messages for clarity and alignment before delivering them — not in the moment
- Speak with presence and purpose: structure your communication so it lands
- Avoid jargon, waffle, and mixed messages that create confusion or erode credibility
- Communicate decisions, priorities, and direction so people know exactly what is expected
- Adapt your message for different audiences without losing consistency or integrity
AI & Technology Workplace Scenarios
- AI context: Communicating the business rationale for AI tool adoption to a development team without technical jargon or corporate language
- AI context: Explaining clearly what AI-assisted performance monitoring is, how it works, and what it is and is not used for
- AI context: Giving unambiguous direction on AI code assistant policies — what is mandatory, discretionary, or prohibited
Module 2: Deliver Constructive Feedback with Confidence
- Use proven feedback models that foster genuine improvement rather than defensiveness
- Separate the message from the emotion — yours and theirs — so the content lands clearly
- Frame feedback to encourage ownership and forward action rather than blame or excuses
- Calibrate feedback for frequency and specificity — habits that make feedback a culture not an event
- Deliver positive feedback with the same intention and precision as developmental feedback
AI & Technology Workplace Scenarios
- AI context: Giving meaningful feedback to a developer on the quality of their AI-assisted code — distinguishing AI errors from human errors
- AI context: Addressing declining output quality when a team member has over-relied on AI tools without adequate critical review
- AI context: Delivering feedback on professional conduct when a team member passes off AI-generated work as their own
Module 3: Build Connection Through Listening and Empathy
- Practise active listening techniques that make people feel genuinely heard and understood
- Demonstrate understanding without losing your authority, direction, or purpose
- Adapt your communication style to the needs, preferences, and emotional state of different team members
- Use empathy as a leadership tool — building connection that increases honesty and psychological safety
- Listen for what is not being said — the concerns beneath the surface that drive behaviour
AI & Technology Workplace Scenarios
- AI context: Listening to understand genuine concerns about AI adoption — distinguishing rational objections from anxiety or resistance
- AI context: Building connection with a team member who feels their professional identity is threatened by AI tool mandates
- AI context: Adapting communication to developers who want technical depth versus non-technical stakeholders who need strategic framing
Module 4: Develop Skills Through Structured Simulation or Role Play
- Choose between structured role plays with full character briefs or coached scenario simulations
- Practise key leadership conversations in a safe, supportive environment with expert facilitation
- Get direct, actionable feedback from facilitators tailored to your goals and real leadership context
- Work on the specific communication challenges you face — not generic exercises
- Leave with a clear personal development focus and commitment to practise
AI & Technology Workplace Scenarios
- AI context: Scenario: Communicating to a development team that AI coding assistants will become mandatory — managing the Q&A that follows
- AI context: Scenario: Explaining to a high-performing developer that their role is changing as a result of AI capability
- AI context: Scenario: Leading a team meeting where AI monitoring data is discussed for the first time — handling surprise and challenge
- AI context: Scenario: Communicating upward to senior leadership about team resistance to AI adoption — representing your team without undermining the programme
Who should attend
- Team leaders and managers who want to communicate with greater clarity, confidence, and impact
- Technical leads who need to communicate complex or sensitive information to non-technical stakeholders
- Leaders navigating AI adoption who must communicate change, uncertainty, and expectation effectively
- Anyone whose communication style is holding back their leadership effectiveness
Feedback
4.8 out of 5 average
"I thought that the style of creating a backlog of user stories and inputting them into sprints was very helpful and that the practical at the end of the course was excellent. Overall, it gave me a great insight into agile project management."
GW, Project Manager, Scrum, April 2021
“JBI did a great job of customizing their syllabus to suit our business needs and also bringing our team up to speed on the current best practices. Our teams varied widely in terms of experience and the Instructor handled this particularly well - very impressive”
Brian F, Team Lead, RBS, Data Analysis Course, 20 April 2022