Nov 7, 2025
From the Unconscious Mind to Intelligent Systems
Psychology has evolved dramatically over the last century. Early thinkers like Sigmund Freud focused on the unconscious, exploring hidden drives and early childhood experiences. Later, humanistic psychologists like Carl Rogers, Abraham Maslow, and Erik Erikson shifted the lens toward conscious experience, personal growth, and human potential. Their work reframed the question: instead of merely understanding what drives us beneath awareness, how can we help people realize their fullest potential?
Today, artificial intelligence is at a similar inflection point. AI systems are no longer simple tools; they are complex decision-making entities. Yet, much like the early psychoanalytic “black box” of the unconscious mind, modern AI can feel opaque, reactive, and disconnected from human values.
The challenge we face now mirrors psychology’s past: how do we design AI that is conscious — not in the sense of sentience, but in the sense of being aware, ethical, transparent, and aligned with human goals?Driving Organizational Culture
At the heart of good leadership lies the ability to shape organizational culture – the collective values, beliefs, and behaviors that define how individuals within the organization interact and operate. Good leaders set the tone for the organization, embodying its values and fostering a culture of accountability, transparency, and inclusivity. They cultivate a sense of purpose and belonging, aligning individual efforts with the organization's mission and vision.
AI’s Evolution Mirrors Psychology’s
Early AI: Like Freud’s unconscious, early AI operated in a hidden, deterministic fashion — rule-based systems processing inputs without transparency.
Machine Learning & Deep Learning: More sophisticated, these models resemble the middle stages of psychology — predictive, capable of learning from past data, but still limited in interpretability and human alignment.
The Agentic Enterprise / Conscious Machine: The next stage is AI that behaves proactively, ethically, and in service of human needs — systems that can act with awareness across organizational touchpoints and augment human decision-making.
In other words, AI’s evolution mirrors psychology’s journey: from opaque forces we could not control to systems designed to enhance conscious, intentional action.
Why Designers Must Lead
Designers are uniquely positioned to guide this transition. Here’s why:
Empathy as a Compass
Human-centered designers understand people’s needs, frustrations, and motivations. Just as humanistic psychologists centered the individual, designers ensure AI serves human goals, not just business metrics.Systems Thinking Bridges Frontstage and Backstage
Modern organizations operate across complex layers: customer interactions (frontstage) and operational processes (backstage). Designers visualize, map, and optimize these systems, ensuring AI aligns both human experience and operational intelligence.Ethics, Transparency, and Trust
AI is powerful, but opaque systems erode trust. Designers embed explainability, transparency, and ethical guardrails, turning AI into a reliable partner rather than a mysterious “black box.”Proactive, Agentic Systems
Designers think beyond reaction — they create frameworks for AI to anticipate needs, make informed recommendations, and act autonomously when appropriate, improving efficiency while keeping humans in the loop.
The Role of the Designer in the Conscious Machine Era
Think of designers as the humanists of technology. Just as Carl Rogers and Maslow emphasized conscious growth and self-actualization, designers today emphasize conscious AI: systems that are aware, aligned, and adaptive.
Organizations that embed designers at the forefront of AI development will:
Build systems that anticipate human needs rather than simply respond.
Ensure transparency and trust across all customer and employee interactions.
Connect intelligence from “backstage” operational data with “frontstage” human experiences.
Enable AI to become a force multiplier for human potential — not a replacement.
Conclusion
The evolution of AI is not just a technical challenge — it is a human challenge. Just as psychology matured by bringing the unconscious into the realm of conscious understanding and growth, AI must evolve from opaque, reactive systems into conscious, agentic technologies.
Designers are the natural leaders in this evolution. By combining empathy, systems thinking, and ethical foresight, they ensure AI serves humans first — augmenting our decisions, amplifying our potential, and creating organizations that are aware, adaptive, and aligned.
The future of AI isn’t about machines replacing humans. It’s about machines enhancing our humanity — and designers are the architects of that future.
Explore how we can design the Agentic Enterprise with conscious AI systems in my case study: “The Agentic Enterprise: Connecting Frontstage & Backstage with Agentforce 360.”
References
Foundations of Psychology & Human Potential
Freud, S. (1915). The Unconscious. Standard Edition, Vol. 14.
Rogers, C. (1961). On Becoming a Person. Houghton Mifflin.
Maslow, A. (1943). “A Theory of Human Motivation.” Psychological Review.
Erikson, E. H. (1950). Childhood and Society. W. W. Norton.
AI Transparency, Ethics & Human-Centered Design
5. Norman, D. (2023). “Design, Ethics, and the Future of Human–AI Interaction.” Nielsen Norman Group.
6. World Economic Forum (2023). “Human-Centered Artificial Intelligence: Principles and Recommendations.”
7. Russell, S., & Norvig, P. (2020). Artificial Intelligence: A Modern Approach (4th ed.). Pearson.
Agentic AI, Proactive Systems & Organizational Intelligence
8. OpenAI. “Agents and Autonomy: Responsible AI Development.”
9. IBM Research. “The Shift Toward Agentic AI Systems.”
10. McKinsey & Company (2024). “AI Adoption: Moving from Reactive Automation to Proactive Intelligence.”
Design, Systems Thinking & Service Blueprinting
11. Bitner, M. J., Ostrom, A. L., & Morgan, F. N. (2008). “Service Blueprinting: A Practical Technique for Service Innovation.” California Management Review.
12. Kalbach, J. (2020). The Jobs To Be Done Playbook.
13. Stickdorn, M., Hormess, M., Lawrence, A., & Schneider, J. (2018). This is Service Design Doing. O’Reilly.
Industry Examples Mentioned (Siemens, GE Healthcare, Rockwell)
14. Salesforce Industry Solutions. “Siemens Launches Teamcenter SLM on AppExchange.”
15. Salesforce Customer Stories. “GE Healthcare Uses Salesforce to Manage Global Medical Assets.”
16. Rockwell Automation. “The Connected Enterprise: Bridging IT and OT for Scalable Transformation.”