Your customers don’t churn because the model is weak. They churn because they stop relying on it.

In AI-assisted decisions, responsibility is shared. When a decision goes wrong, someone has to establish whether the failure was in the model or in how the people around it behaved. Vendors who can show that their product supports appropriate reliance are better placed in that conversation than vendors who cannot.

If your product decides how much of a workflow passes from a person to automated steps, you are shaping reliance directly. The central question is where appropriate delegation ends and blind delegation begins. It is a behavioral question, it has measurable answers, and it is the question I study.

We use survey, interview and observation methods to find where users stop trusting or relying on the product, and which behavioral mechanisms explain it.

We distinguish failures that come from your design from failures that come from the customer’s environment, so each side fixes what it controls.

The output is specific changes to the experience, the workflow and the model-update process, ranked by their likely effect on adoption.

A fast first look at why customers aren’t using the product.

The BEAR Snapshot is a survey-only diagnostic for vendors whose customers are not using their tools as expected. It measures how users respond to the product, covering what they believe about it, how they use it, and where that response breaks down. Because it needs no extended fieldwork, it is the quickest way to find out whether a behavioral explanation fits the churn or low-usage pattern you are seeing.

You receive a clear read on where in the user experience the breakdown sits and which behavioral forces are behind it, so the next decision rests on evidence. Sometimes the Snapshot answers the question outright. Sometimes it shows that a fuller diagnosis is warranted, and it becomes the starting point for BEAR.

A 21-day diagnosis of a specific deployment.

BEAR examines how real users interpret, test and rely on your product inside a particular customer deployment. Usage metrics tell you what users did. BEAR explains why, by combining a structured survey, short engagements with users throughout the 21 days, and observation of how people actually behave in their workflows, including where they follow the product, override it or work around it.

The deliverables are a Behavioral Failure Mode Map that organizes the problems into underlying mechanisms, a Reliance Stability Score that shows where reliance is stable, fragile or at risk of drifting, and a Behavioral Stabilization Blueprint that ranks the changes most likely to stabilize appropriate, long-term use. For a vendor, this separates problems that sit in your design from problems that sit in the customer’s environment, so each side can fix what it controls.

Help customers get from a successful pilot to enterprise-wide use.

Pilots succeed in controlled conditions, and many stall when a customer scales them. Workflows become variable, users bring different norms, and the support that made the pilot work disappears. STAR (Scaling & Trust Accelerator Program) is a program that identifies the behavioral conditions a customer needs to meet for adoption to hold at scale, and it is relevant to vendors because the product’s success beyond the pilot depends on them.

The program runs in phases: a behavioral diagnostic, a definition of requirements, a transformation phase that redesigns workflows, interfaces and governance to support those requirements, and ongoing optimization in quarterly cycles. For vendors, it shows how the product behaves under operational pressure, which design and workflow adjustments reduce friction, and how to keep model updates aligned with how people actually work.

A finding on a single AI-assisted decision.

When one specific case is under scrutiny, such as an incident, a dispute or a customer challenge, BOLD (Behavioral Oversight & Legitimacy Diagnostic) is a rapid behavioral audit of that decision alone. It examines the evidence around the decision to determine whether the human behavior was reasonable, which helps separate a model failure from a process failure. This matters when responsibility is shared and each party needs to know where the failure sat.

The audit takes three to five business days and ends in a clear verdict that is defensible under review. It is also a low-commitment way to see the method applied to one real case before deciding on a larger engagement.