top of page

About Us

Quantifying the Unquantifiable 

We didn't set out to build a consulting practice; we set out to solve a mathematical problem. Our journey began with the realization that 75% of enterprise AI scaling failures weren't due to poor algorithms, but to organizational friction—the hidden costs of skill gaps, lack of trust, and manual governance. Traditional metrics only measure model speed; they ignore the human penalty.

Machine Leadership_David Swanagon_edited.png

Dr. David Swanagon

Founder, Machine Leadership

The journey of Machine Leadership began in 2022. Dr. Swanagon noticed that most of the patent applications for data science and artificial intelligence were driven by a specific type of personality. These individuals were different than traditional C-Suite executives. They enjoyed unbounded creativity, refused to accept artificial boundaries, had excellent memories, and presented themselves as introverts. Their relationship with the digital world exceeded the one they maintained with the physical world. Despite leading the largest transformation in human civilization, these "AI Engineers" were humble, shy, and curious. They had a unique set of cognitive processes and leadership traits. Moreover, their vision for the future was quickly becoming the reality for everyone. A new type of leader was born: The Machine Leader. 

​

So with a new type of leader came a new set of challenges. Traditional leadership frameworks did not account for the unique perspective of these AI engineers. Likewise, the AI engineers lacked the engagement with the C-Suite to understand how traditional leadership was exercised. There was a disconnect between both audiences, one that would grow larger the more sophisticated the AI tools became. Through research and interviews, Dr. Swanagon realized that AI adoption would be limited if the skills of the AI engineer were not aligned with the C-Suite and customerf functions. This meant a new type of methodology was needed. One that tracked the cognitive processes and leadership skills that were critical for building machines, while incorporating the traditional leadership principles of motivation, trust, and sense making. Machine Leadership reflects that emerging thinking. Moving forward, professionals looking to succeed in the age of AI will need to lead machines, lead people that build machines, and lead organizations that adopt AI.

Our Mission

The Machine Leadership Framework was born from proprietary research, which was recently recognized by Columbia University as a best practice in AI adoption. This research proved that the misalignment of Autonomy, Trust, and AI Competencies creates a quantifiable financial penalty. This insight led us to create the AI Friction Index (AFI) platform. 

​

Our Core Mission: SaaS, Not Service

​

AFI is the first patented SaaS platform designed specifically to help CIOs and CHROs maximize their AI ROI. We transform abstract organizational friction into a single, actionable financial metric: the Tailored Scaling Constant. We are a software company committed to scale and precision. While our Journal, Courses, and Remediation Services build market credibility and capture necessary data for our formula, our value lies entirely in the software’s ability to deliver a real-time, auditable financial diagnosis of adoption barriers. We eliminate the guesswork and expensive consulting engagements, replacing them with a precise equation. 

​

Our Moat: Patented IP and Data Fusion

​

Our technical advantage is our intellectual property, which is protected by a Provisional Patent Application (USPTO).

We solve the technical challenge of data fusion by:

​

  1. Deriving (Claim 1): Uniquely linking a financial input, the budget to the calculated organizational friction score.

  2. Proprietary Inputs (Claim 4): Utilizing a dynamic LLM Assessment Engine to generate high-fidelity, non-obvious data (Leadership Capacity Scores) for the AI Competency variable.

  3. Actionable Output: Using the derived penalty to generate System Penalty Contribution reports, directing executive investment to the highest-cost friction points (e.g., "The Azure AD imbalance costs by XX (USD) annually").

  4. The output results in actionable insights for the CIO and CHRO to proactively intervene to ensure that high-value AI tools, platforms, and systems are fully utilized by their intended audience (i.e., employees and customers). 

​​

The Team and Our Vision

​

We are a lean team of experts in AI research, enterprise architecture, and financial modeling, dedicated to disrupting the traditional consulting model. Our brand, "Machine Leadership," has already achieved an organic following of 5K on LinkedIn—a powerful testament to the market's urgent need for a quantitative solution.

​

Our Vision: To make AFI the mandatory financial operating system for every enterprise navigating the AI adoption frontier. We turn your organizational friction into your clearest path to ROI.

bottom of page