The current mass-adoption phase for AI tools means buying decisions that would normally take 5-7 years are being compressed into 1-2 years. Startups that don't secure customers now risk being shut out, as enterprises will lock in with their chosen vendors for the subsequent half-decade.

Unlike the slow denial of SaaS by client-server companies, today's SaaS leaders (e.g., HubSpot, Notion) are rapidly integrating AI. They have an advantage due to vast proprietary data and existing distribution channels, making it harder for new AI-native startups to displace them. The old playbook of a slow incumbent may no longer apply.

Unlike previous top-down technology waves (e.g., mainframes), AI is being adopted bottom-up. Individuals and small businesses are the first adopters, while large companies and governments lag due to bureaucracy. This gives a massive speed advantage to smaller, more agile players.

Previous technology shifts like mobile or client-server were often pushed by technologists onto a hesitant market. In contrast, the current AI trend is being pulled by customers who are actively demanding AI features in their products, creating unprecedented pressure on companies to integrate them quickly.

Hospitals are adopting a phased approach to AI. They start with commercially ready, low-risk, non-clinical applications like RCM. This allows them to build an internal 'AI muscle'—developing frameworks and expertise—before expanding into more sensitive, higher-stakes areas like patient engagement and clinical decision support.

A major market opportunity exists when one side of an industry (e.g., insurance companies) adopts new technology like AI faster than its counterpart (e.g., hospitals). Startups can succeed by building tools that close this technology gap, effectively 'arming the rebels' and leveling the playing field.

Unlike the top-down, regulated rollout of EHRs, the rapid uptake of AI in healthcare is an organic, bottom-up movement. It's driven by frontline workers like pharmacists who face critical staffing shortages and need tools to manage overwhelming workloads, pulling technology in out of necessity.

In the current, rapidly evolving AI market, the long-term winners are not yet clear. CIOs should de-risk their budgets by experimenting with more vendors, using shorter-term contracts, and prioritizing products that can be tested and prove value quickly.

Unlike typical tech disruption, healthcare often requires collaboration. Startups effectively "rent" distribution and patient access from incumbents. In return, incumbents "rent" cutting-edge innovation from startups, creating a necessary symbiotic relationship.