The mortgage industry is currently witnessing a paradigm shift in how its most prominent leaders communicate with their audiences. For decades, the sector’s top executives relied on a sophisticated network of ghostwriters, coaches, and professional marketing services to distill their complex strategies into digestible, authoritative content. This human-centric model of brand building, which prioritized "extracting" the unique perspectives of leaders, is rapidly being replaced by generative artificial intelligence (AI). However, as more executives turn to platforms like ChatGPT to automate their thought leadership, industry experts are warning of a phenomenon known as "the great averaging"—a systemic homogenization of content that threatens to render once-distinct brands invisible in an increasingly crowded digital marketplace.
The transition to AI-driven content creation was highlighted recently when a high-profile mortgage executive reportedly paid a significant sum to a social media consultant for an eight-week intensive course on automating his entire LinkedIn presence through AI. While the executive viewed this as a breakthrough in efficiency, marketing analysts suggest this approach may inadvertently dismantle the very brand equity he spent years building. By delegating the "thinking" process to large language models (LLMs), leaders risk producing content that is technically proficient but fundamentally indistinguishable from their competitors.
The Mechanics of the Great Averaging
The core issue with the widespread adoption of AI in executive branding lies in the nature of the technology itself. Tela Mathias, who leads the PhoenixTeam and manages the Mortgage Bankers Association’s AI Mortgage Change Champion program, notes that because major foundation models—such as OpenAI’s GPT, Google’s Gemini, and Anthropic’s Claude—are trained on largely overlapping datasets, their outputs tend to converge toward a statistical mean.
"All of the foundation model providers are trained on essentially the same body of knowledge," Mathias observed. "They will produce, all things being equal, basically the same result." This creates a scenario where a lender could utilize six different AI models to build a website or a social media strategy, and the end result would appear nearly identical. In the context of executive branding, this means that every leader who hands their voice over to AI is being "averaged" against every other leader doing the same. The result is a sea of "fine" content: grammatically correct, logically sound, but entirely forgettable.
A Historical Context of Risk Aversion
The mortgage industry’s current susceptibility to AI-driven homogenization is rooted in a decade of conditioned caution. Following the 2008 financial crisis, many leaders in the sector adopted a strategy of extreme risk aversion in their public communications. The prevailing wisdom became to "round oneself down" and adhere to safe, uncontroversial narratives to avoid regulatory or public scrutiny.
This culture of "not upsetting anyone" has created a vacuum that AI is perfectly designed to fill. Because AI models are programmed to be helpful, harmless, and honest, they naturally gravitate toward the "safe" middle ground. While this prevents PR disasters, it also eliminates the possibility of genuine thought leadership. In a professional environment where marketing departments often prioritize "assets" (the number of posts) over "outcomes" (the impact of those posts), AI provides an efficient way to check a box without actually saying anything of substance.
The Three Pillars of Authentic Branding: Taste, Guts, and Receipts
To counter the diluting effects of AI, industry veterans suggest a framework built on three specific human elements that LLMs cannot replicate: taste, guts, and receipts.
The Role of Taste in Curation
Taste is defined as the disciplined ability to discern what aligns with a specific brand voice and the willingness to discard anything that does not. While AI can generate fifty clean drafts in a minute, it cannot determine which one possesses the unique "spark" of a specific individual. Experts note that AI-written content often suffers from a flattening of rhythm and predictable word choices. In a digital feed where users scroll past hundreds of posts, "fine" is the equivalent of invisible. The test for taste is simple: if a leader cannot quote a single line from their own post the following morning without looking at it, the content has failed to make an impact.
The Necessity of Guts
"Guts" refers to the courage to take a definitive stance that invites disagreement. Much of current mortgage marketing relies on platitudes such as "it’s about relationships, not rates" or "people do business with people." Because no one disagrees with these statements, they carry no weight. A true position of leadership requires a statement that a specific person in the room would push back against. AI, by design, lacks the personal stakes required to take such risks. It has nothing to lose; an executive, however, has their reputation and market share on the line.
The Importance of Receipts
In an era of synthetic content, "receipts"—specific, verifiable evidence of actions and costs—are the ultimate proof of humanity. This includes specific dates, dollar amounts, and descriptions of deals that failed. A receipt is characterized by a decision that carried a real cost. For example, a leader who refuses to publish a generic, AI-generated post, even if it saves time, is holding a line that carries a cost in efficiency. This specificity is what prevents a leader from being "laundered" out of their own professional record.
The Shift in Due Diligence: When AI Vets the Executive
The consequences of the "great averaging" extend beyond social media engagement; they impact recruitment and business partnerships. In the current market, a potential recruit or a Realtor partner is likely to perform due diligence by asking an AI model about a specific executive or company.
If an executive’s entire digital footprint consists of averaged, AI-generated content, the model will have no unique data to draw upon. When a user asks an LLM, "What makes this leader different?" and the model provides a generic summary of "industry experience and a focus on customer service," the executive has effectively become invisible at the most critical moment of the professional relationship. A brand was once what people said about you when you left the room; today, it is also what the model says about you when someone asks.
Chronology of the Content Evolution in Mortgage
The shift from human-led thought leadership to AI automation has followed a distinct timeline:
- The Pre-2008 Era: High-profile leaders often spoke candidly, though the industry was less focused on digital personal branding.
- The Post-Crisis Retrenchment (2009–2018): A period of extreme caution where ghostwriters were hired to ensure "safe" messaging.
- The Digital Authority Boom (2019–2022): Executives recognized the need for "personal brands" to compete for talent and leads, leading to a surge in professional content coaching.
- The Generative AI Pivot (2023–Present): The release of ChatGPT and subsequent models led to a mass migration toward automated content, resulting in the current "great averaging."
Strategic Analysis: Using AI as a Banned List
Rather than abandoning AI entirely, forward-thinking marketing strategists suggest a "reverse-engineering" approach. Instead of asking AI to write a post, leaders should ask the model to generate the most common, generic response to a piece of industry news. Whatever the AI produces should then be treated as a "banned list"—a collection of phrases and ideas to be strictly avoided.
By identifying the "average" response, an executive can intentionally write around it, finding the specific angle, the controversial take, or the personal anecdote that the model is incapable of producing. This method ensures that AI is used as a tool for differentiation rather than a replacement for original thought.
Broader Implications for the Mortgage Industry
The trend toward automated content comes at a time when the mortgage industry is navigating significant volatility, including fluctuating interest rates and shifting regulatory landscapes. In such an environment, the value of a trusted, distinct voice is at an all-time high. Consumers and partners are not looking for more information; they are looking for clarity and conviction.
If the industry continues down the path of the "great averaging," it risks a total commoditization of leadership. When every executive sounds like a version of the same bot, the only remaining point of differentiation is price. For an industry that prides itself on being a "relationship business," the surrender of the individual voice to the algorithm represents a significant strategic risk.
The executive who paid thousands of dollars to automate his content may find that he has purchased efficiency at the expense of influence. As the digital landscape becomes increasingly saturated with synthetic voices, the market’s premium will inevitably shift toward those few leaders who remain stubbornly, specific, and authentically human. In the final analysis, the most successful leaders will not be those who use AI to write their thoughts, but those who use AI to identify what is common, so they can offer something rare.
