BUSINESS RESEARCH

Project Roles, Planning and Stakeholders: Using AI and RACI to Strengthen Delivery

Effective projects rely on clear roles, strong planning and purposeful engagement with stakeholders. This Hot Topic shows how Artificial Intelligence tools and principles can enhance each stage. It explains how stakeholder analysis and a RACI matrix support clarity and accountability, while AI improves forecasting, communication and decision-making. It also highlights ethical and responsible AI use, helping professionals strengthen delivery today and build confidence for future leadership roles.

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Project Roles, Planning and Stakeholders: Using AI and RACI to Strengthen Delivery
  1. Roles and responsibilities in the project environment, supported by AI Projects typically involve sponsors, project managers, technical specialists and delivery teams. Clear responsibilities reduce duplication and confusion, enabling smoother delivery. AI now supports this clarity by mapping workflows, identifying resource bottlenecks and highlighting overloaded roles, strengthening operational awareness (Salimimoghadam et al., 2025). AI‑enabled tools such as predictive resource modelling and automated task allocation improve visibility, although AI adoption varies widely and requires upskilling, with only 21 percent of project professionals regularly using AI (2023). Importantly, AI tools must be used responsibly. Studies highlight that AI can misinterpret data or oversimplify human capability unless decisions remain human-led (Mariani & Mancini, 2024). Ethical practice ensures AI enhances, rather than replaces, professional judgement.
  2. Planning with the Kipling questions, enhanced by AI insight The Kipling structure (who, what, where, why, when, how, how much) provides a clear foundation for project planning. AI enhances each component by improving data interpretation, forecasting, and modelling.
    • Who: AI identifies skill gaps and predicts resource needs (2023).
    • What: Natural language tools help define scope and interpret requirements more precisely, improving clarity (Mariani & Mancini, 2024).
    • Where: AI models operational impacts across systems or locations, supporting cross-functional planning (Salimimoghadam et al., 2025).
    • Why: Data-driven insight strengthens benefit modelling and value prediction.
    • When: Predictive analytics improve milestone forecasting and schedule reliability (Salimimoghadam et al., 2025).
    • How: AI assists in identifying the most efficient delivery methods using historical patterns (2023).
    • How much: Cost estimation models use patterns to improve budget accuracy (Salimimoghadam et al., 2025).

    Despite these advantages, researchers emphasise that human oversight must validate automated outputs to ensure transparency and fairness (Geraldi et al., 2024).

  3. Stakeholder analysis and communication supported by AI
    Stakeholder engagement is fundamental to project success. Research shows that AI supports stakeholder analysis by identifying patterns, analysing sentiment and mapping communication behaviours (Joshi, 2025). AI‑powered chatbots can improve communication by providing immediate, personalised responses, increasing stakeholder satisfaction and reducing response delays (Joshi, 2025). Similarly, AI can analyse stakeholder interactions to identify those requiring more engagement or support (Salimimoghadam et al., 2025).
    However, scholars warn that AI‑enabled communication tools pose risks when handling sensitive data. Ethical considerations such as data security, transparency, and consent must be followed to maintain trust (Geraldi et al., 2024).

    4.  

  4. Translating insight into a RACI matrix with AI support
    The RACI matrix clarifies responsibility, accountability, consultation, and information. AI enhances the development of a RACI by identifying task dependencies, highlighting unclear ownership, and analysing historical patterns to suggest likely responsibility allocations (Salimimoghadam et al., 2025). Strong links between RACI and stakeholder analysis are well established and widely recommended (2025).
    Still, studies show that AI can misinterpret process logic, meaning teams must validate AI output to maintain accuracy and fairness (2023).

    5.  

  5. AI, RACI and planning as leadership capability
    AI is increasingly seen as a critical capability for project professionals. PMI research highlights that 82% of senior leaders expect AI to significantly change project delivery in the next five years (2023). When practitioners combine AI‑supported insights with planning tools like the RACI matrix, they demonstrate governance awareness, decision-making capability and strategic thinking (Mariani & Mancini, 2024). Responsible AI use also reinforces leadership behaviours such as ethical judgement, risk awareness and accountability (Geraldi et al., 2024). These skills are increasingly essential as organisations adopt more complex project environments and digital capabilities.

    6.  

  6. Practical next steps Professionals can begin integrating AI ethically by using AI assistants to summarise meetings, draft plans or review RACI structures for consistency. AI can also highlight risks, detect stakeholder themes and suggest communication priorities (Joshi, 2025). However, research stresses that transparency and human oversight remain crucial to prevent bias, ensure accuracy and maintain trust (Geraldi et al., 2024). A gradual approach allows teams to adopt AI safely and build confidence in using advanced tools.

Referenced techniques

Technique

Stakeholder Analysis and Management

Outlines stakeholder analysis practice, benefits, and implementation guidance. Highlights the shift from narrow management to inclusive stakeholder engagement, noting sceptical or marginalised groups and digital channels for dialogue (Aaltonen et al., 2024).

Technique

Project Roles and Responsibilities

In any project environment, various roles and responsibilities contribute to its success. From project managers overseeing tasks to team members executing them, each role plays a crucial part in achieving project objectives efficiently and effectively.

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