AI Transparency
How artificial intelligence contributes to Hayes research—and where human expertise remains irreplaceable.
Hayes uses AI as a research tool throughout our workflow. This isn’t something to hide or downplay—it’s how rigorous research gets done in 2025. But AI is a tool, not a replacement for expertise, judgment, or original thinking.
This page details exactly where and how AI contributes to our work. Not because we’re required to disclose it, but because transparency about methodology matters when you’re asking decision-makers to trust your analysis.
Our Standard
Every Hayes report carries the founder’s name because every Hayes report reflects human judgment about what matters, human synthesis of complex dynamics, and human accountability for the analysis. AI assists the process. It doesn’t drive it.
Transparency in Every Layer
Here’s exactly how AI contributes across our research and production workflow:
Report topics, research questions, and analytical frameworks are developed entirely by human expertise based on industry knowledge and pattern recognition.
AI helps surface relevant academic papers, regulatory documents, and industry reports. Human researcher evaluates source quality, identifies gaps, and determines what’s actually useful.
AI processes large datasets and identifies potential patterns. Human analyst validates findings, contextualizes results, and determines significance for the research thesis.
All analysis, conclusions, and strategic recommendations are written by the founder. The voice, judgment calls, and synthesis reflect human expertise.
AI suggests improvements to sentence structure and clarity. Human editor makes final decisions on tone, precision, and whether suggestions improve readability.
AI generates concept art and visual elements. Human designer directs aesthetic choices, ensures brand consistency, and finalizes all visual materials.
Every cited source is manually verified. Every data point is checked against primary sources. Human accountability for accuracy.
What These Roles Mean
Human-Created
Work originated and executed entirely by human expertise. AI played no role in conception or execution.
AI-Assisted
AI provided initial output or suggestions. Human reviewed, revised, and made final decisions on what to use.
Collaborative
AI and human worked iteratively. AI processed information or generated options, human directed and validated output.
Human-Verified
Human personally checked, validated, and took accountability for accuracy regardless of how information was initially gathered.
Our AI Principles
AI Is a Tool, Not a Shortcut
We use AI to work faster and more efficiently—not to replace the expertise, judgment, and original thinking that makes research valuable. AI helps us process more information and produce clearer outputs. It doesn’t tell us what to think.
Human Accountability for Every Claim
Every report carries David Marrinan-Hayes’s name because he’s personally accountable for every analysis, conclusion, and recommendation. If something’s wrong, that’s on him—not on the tools used to produce it.
Transparency About Methodology
We believe readers deserve to know how research is produced. This transparency extends beyond AI to include our research process, source evaluation criteria, and analytical frameworks. Good methodology should withstand scrutiny.
Continuous Evolution
As AI capabilities change, our usage will evolve. We’ll update this page to reflect new tools, new workflows, and new ways AI contributes to research. What won’t change: human expertise drives the analysis, and we’re transparent about what we’re doing.