Introduction
The programme “16th Annual Human Resources Technology Conference: Artificial Intelligence Strategies in Recruitment and Training” develops professional practice in Conferences. It connects the subject with workplace challenges by examining existing evidence and practices and choosing methods appropriate to the organization and its available resources.
The learning progresses from recruitment, selection, and candidate experience to strategy formulation and prioritization, with practical work on training design and measurement of learning transfer, artificial intelligence applications and controls, applied research, evidence development, and recommendations. Participants prepare outputs to support workplace application and review the quality and results of implementation.
Learning objectives
- Design a selection process based on job requirements and consistent assessment evidence in an application related to “16th Annual Human Resources Technology Conference: Artificial Intelligence Strategies in Recruitment and Training”.
- Design a training intervention that begins with a performance gap and ends with evidence of application.
- Design an AI use case with verification criteria and human review.
- Prepare an applied study connecting the research question, data, analysis, and recommendation.
- Translate strategic direction into actionable objectives and initiatives.
Learning areas
1. Recruitment, Selection, and Candidate Experience
- Translate the job description into observable selection criteria, separating essential requirements from attributes that can be developed.
- Prepare a clear job advertisement and recruitment plan targeting appropriate sources, avoiding requirements unrelated to the work.
- Design a structured interview, behavioral and situational questions, and a standard template for recording evidence and evaluating answers.
- Select appropriate assessment tools and work samples, and review fairness, privacy, and permissions for accessing candidate data.
- Document the selection decision, its rationale, communication steps, and onboarding, and measure quality of hire and candidate experience after implementation. The application examines a case related to “16th Annual Human Resources Technology Conference: Artificial Intelligence Strategies in Recruitment and Training”.
2. Training Design and Measurement of Learning Transfer
- Analyze performance gaps at organizational, job, and individual levels, and verify that training addresses a cause related to knowledge or skill.
- Write observable learning objectives, define entry requirements, and link each objective to a training activity and assessment evidence.
- Build a sequence of content, activities, and practical cases, balancing explanation, experimentation, and feedback within the available time.
- Select suitable learning methods, face-to-face delivery, and digital learning, and ensure accessibility, material quality, and delivery instructions.
- Design pre- and post-learning assessments and a follow-up plan with the line manager to measure application and identify additional support needs.
3. Artificial Intelligence Applications and Controls
- Identify a task that AI can support, and separate inputs and human decisions from outputs produced by the tool.
- Prepare suitable test data and examples while respecting confidentiality, privacy, and permissions, and use de-identified training exercise data.
- Write clear instructions covering the task, context, constraints, and output format, and compare multiple formulations using a fixed set of examples.
- Check outputs for errors, bias, and unsupported information, and identify cases that require specialist review.
- Assess the feasibility of use in terms of quality, time, cost, and risk, and document controls for approval, monitoring, and stopping when failures occur.
4. Applied Research, Evidence Development, and Recommendations
- Frame a research question or practical problem suitable for study, and define the subject boundaries, context, and outcome the research will support.
- Review sources relevant to the question, assess their reliability and currency, and distinguish direct evidence from opinion and inference.
- Select an appropriate method, instrument, and sample, explaining limitations and obtaining approvals and protecting privacy when collecting data from people.
- Organize and analyze data and relate findings to the question, avoiding generalizations unsupported by the sample or causal conclusions based only on correlation.
- Write specific, actionable recommendations with responsibilities, resources, and indicators, and include source documentation and limitations of conclusions in the applied report.
5. Strategy Formulation and Prioritization
- Analyze the internal and external environment using available data, and distinguish opportunities from assumptions that require verification.
- Define a specific strategic problem and connect it to the organization's mission and the value sought by beneficiaries and stakeholders.
- Set measurable objectives with a baseline, target, and time horizon, and assign a clear owner to each objective.
- Prioritize initiatives according to impact, feasibility, resources, risks, and interdependencies, explaining the reasons for the trade-offs.
- Build an implementation roadmap covering phases, owners, resources, review gates, and a mechanism for adjusting priorities when circumstances change.
Practical outputs
- A selection matrix, interview guide, and candidate scorecard.
- A needs analysis, concise learning package, and application evaluation plan.
- A use case brief and a test template for the quality of AI outputs.
- An applied research plan, data collection tool, and findings and recommendations report.
- A strategy map and a priority matrix for proposed initiatives.
Who should attend
- Practitioners, specialists and supervisors whose work relates to the programme subject.
- Managers and teams working in conferences, according to their practical responsibilities.
- Professionals responsible for applying the outputs of “16th Annual Human Resources Technology Conference: Artificial Intelligence Strategies in Recruitment and Training” within their organizations.
Prerequisites
- Working familiarity with the programme field and the ability to discuss a professional case or challenge.
- Confirm the suitability of your experience and any specialist prerequisites with the Union before participation.
Conclusion
The programme “16th Annual Human Resources Technology Conference: Artificial Intelligence Strategies in Recruitment and Training” brings together concepts, case review and a practical application. Participants prepare steps that can be adapted to their responsibilities and organizational resources, with an indicator to follow application and review results after returning to work.
Participation arrangements and any special requests are specified in the confirmation issued by the Union.