Systemic Therapy in Organizations: How Artificial Intelligence Can Enhance Conflict Management

Modern organizations operate as complex systems, where every individual, team, and process is interconnected. Internal conflicts, inter-departmental tensions, and resistance to change are inevitable. Systemic therapy applied to organizations provides a framework to understand and resolve these conflicts in a structured way, promoting collective well-being and productivity. When integrated with artificial intelligence (AI), support tools can enhance understanding of dynamics and facilitate decision-making.

What is Systemic Therapy in Organizations?

Systemic therapy is based on the idea that individual or team problems cannot be analyzed in isolation but must be viewed within the organization’s overall system. This involves:

• Analyzing relationships between people and teams.

• Detecting repetitive patterns that generate conflicts or resistance.

• Identifying imbalances in communication, hierarchy, or processes.

• Seeking solutions that benefit the overall system, not just individual parts.

In organizations, this approach helps improve collaboration, prevent chronic conflicts, and create healthier and more resilient work environments.

Conflict Management from a Systemic Perspective

• System diagnosis: Identify relational dynamics causing tension and determine whether the conflict is symptomatic of a larger imbalance.

• Multi-level intervention: Act on teams, processes, and structures, not just the individuals involved.

• Open communication and mediation: Encourage dialogue between parties, establishing clear norms of respect and collaboration.

• Monitoring and evaluation: Measure the impact of interventions on the overall system and adjust strategies as needed.

How Artificial Intelligence Can Help

AI can enhance the application of systemic therapy in organizations in several ways:

• Relational data analysis: Algorithms can identify patterns of communication, collaboration, and conflict in large teams from emails, chats, and internal reports, providing an objective view of the system.

• Support in mediation and feedback: Tools like Monica AI or Sembly AI can generate summaries, insights, and recommendations based on conversations, helping leaders address conflicts with clear and structured information.

• Simulation of dynamics: Predictive models can simulate the impact of changes in processes or structures before implementation, reducing risks and anticipating resistance.

• Training in emotional skills and leadership: Platforms like Skillsoft can offer personalized programs for emotional development, communication improvement, and conflict management, complementing data analysis with human training.

Benefits of Combining Systemic Therapy and AI

• Better understanding of internal dynamics and conflicts.

• More informed and less subjective decision-making to resolve tensions.

• Reduction of chronic conflicts and increased team cohesion.

• Prevention of future problems through predictive analysis.

• Integration of emotional and rational dimensions in change management.

Considerations and Limitations

• AI is a support tool, not a substitute for human mediation or emotional understanding.

• Confidentiality and ethics must be ensured in data collection and analysis.

• Results interpretation should be supervised by professionals trained in systemic psychology and team management.

Conclusions

Systemic therapy provides a valuable framework for understanding and resolving conflicts in complex organizations. Artificial intelligence does not replace human understanding but provides data, insights, and simulation tools that can accelerate and optimize systemic interventions.

Integrating these approaches allows organizations to resolve conflicts more effectively, improve collaboration, and create a resilient, performance-oriented work environment, combining human insight with the analytical power of technology.