To gain trust from medical and regulatory teams, AI companies must move beyond being 'tech demos.' The key is to build solutions as medical products with transparent validation, reproducible results, and deep integration into existing clinical workflows. Trust is earned through reliability over time, not just peak performance on a single dataset.

Being patient-centered is necessary but insufficient for adoption. Technology in healthcare must be seamlessly embedded into a physician's existing, time-constrained workflow. Great tech that adds friction will be ignored, regardless of its potential patient benefit.

Product stickiness in health systems is achieved through deep workflow integration. By embedding a solution into the daily processes of every stakeholder—from medical assistants to billing coordinators—it becomes entrenched and difficult to replace, mirroring the zero-churn model of EMR giant Epic.

To overcome mistrust in AI due to issues like "hallucinations," health systems should avoid large-scale rollouts. Instead, they must build trust by starting small within a single department, proving the concept with a multidisciplinary team, and demonstrating clear wins before scaling across the entire organization.

Founders often define "integration" as connecting software via APIs. However, true integration means embedding a product seamlessly into the clinician's and patient's existing daily workflow. Any deviation, no matter how small, creates friction that kills adoption rates among busy healthcare professionals.

To build trust in specialized medicine like theranostics, companies must understand and cater to the unique needs of all stakeholders, including nuclear medicine technicians and billing departments, not just the referring physicians and patients.

Kindbody's rapid, venture-backed expansion mirrored a tech startup's trajectory. However, this 'Silicon Valley style' disruption in a sensitive medical field like fertility care ultimately led to significant patient disillusionment, revealing a fundamental clash between a speed-focused business model and the requirements of trust-based medicine.

Many telehealth startups fail by viewing their service as a video call, ignoring the complex workflows of therapists and health systems. TheraNow succeeded by deeply integrating into these existing processes, making its technology an enhancement, not an extra burden, which drove adoption.

When patient engagement is owned by a single department, it's often treated as optional. To make it a core business driver, responsibility must be shared across R&D, medical, regulatory, and commercial teams. This requires a structural and cultural shift to become truly transformational for the organization.