Who Should Attend
Professionals, specialists, supervisors and managers whose responsibilities involve ai for research and knowledge work or who need to build practical capability in this area.
Five days of practical AI application, governance and implementation for Research And Knowledge Work.
This five-day Kaizen European Academy programme is specifically about AI for Research and Knowledge Work; AI is the core subject throughout all five days. Participants learn how artificial intelligence and generative AI can be applied to Research And Knowledge Work, design practical workflows, evaluate tools and outputs, manage governance and risk, and build an implementation roadmap supported by hands-on exercises.
Explain the AI, generative AI and automation concepts most relevant to Research And Knowledge Work.
Identify and prioritize high-value AI use cases in Research And Knowledge Work.
Design practical human-AI workflows and validate AI outputs for Research And Knowledge Work.
Manage privacy, bias, security, governance and human-oversight risks when using AI in Research And Knowledge Work.
Build a practical AI pilot and implementation roadmap for Research And Knowledge Work.
Professionals, specialists, supervisors and managers whose responsibilities involve ai for research and knowledge work or who need to build practical capability in this area.
Instructor-led explanation, facilitated discussion, subject-specific case studies, practical templates, individual and group exercises, simulations or technical scenarios where appropriate, peer review and a final implementation workshop.
Explain the AI, generative AI and automation concepts most relevant to Research And Knowledge Work. Identify and prioritize high-value AI use cases in Research And Knowledge Work. Design practical human-AI workflows and validate AI outputs for Research And Knowledge Work. Manage privacy, bias, security, governance and human-oversight risks when using AI in Research And Knowledge Work. Build a practical AI pilot and implementation roadmap for Research And Knowledge Work.
No formal prerequisite is required. Relevant professional experience is helpful; technical courses may assume basic familiarity with the operating environment.
AI capabilities, limitations and business value
Machine learning, generative AI and large language model concepts
Selecting high-value AI use cases
Data requirements and model inputs
Prompt design and interaction patterns
Human-AI workflow design
AI-assisted analysis and decision support
Automation and intelligent agents
Evaluating accuracy, hallucination and output quality
AI governance and accountability
Bias, fairness and responsible AI
Privacy, confidentiality and information security
Model risk and human oversight
AI adoption and change management
AI value measurement and ROI
Building an AI implementation roadmap
Vendor and platform evaluation
AI policy and acceptable-use controls
Practical AI workflow prototyping
Scaling AI safely across teams
Choose one of the next planned European dates, or create a private delivery around your own schedule.
No public date is currently displayed for this programme. Choose the programme, preferred city and approximate dates. We will organise the venue, trainer and delivery format around your requirements.
This programme can be scheduled across our European training destinations. Venue and trainer are confirmed separately for each session.
Final venue, dates and trainer are confirmed when the session is scheduled.