December 23, 2025
Healthcare Is Done Experimenting With AI
Healthcare organisations are no longer asking whether AI belongs in their operations. That question has been answered. The real question now is whether AI can deliver results quickly, safely, and without disrupting already strained systems.
A new executive outlook report from IntelePeer suggests that 2026 will be the year healthcare finally moves beyond experimentation. Instead of pilots and proof-of-concept projects, leaders are prioritising AI systems that integrate into existing workflows and show measurable impact almost immediately.
Pilots Have Worn Thin
AI projects in healthcare have previously stalled in testing phases. Many never made it past small-scale trials, while others introduced complexity without clear returns. According to IntelePeer’s report, patience for this approach is running out.
Healthcare providers face persistent staffing shortages, rising costs, and growing demand for digital access. In that environment, AI that takes months to configure or requires major system changes is no longer viable. Executives want solutions that can be deployed fast and start reducing pressure on staff within weeks, not years.
The report points to high-volume, rules-based processes as the first targets. Scheduling, patient inquiries, billing questions, and contact centre interactions are areas where AI can make an immediate difference without touching clinical decision-making.
Trust Is the Baseline
In healthcare, trust determines whether technology is adopted at all. According to the report, AI systems must be built with compliance and safety as core requirements.
That includes HIPAA and PHI readiness, governed models, strict guardrails, and clear escalation paths when human intervention is required. Without these controls, AI remains a liability rather than an asset. As a result, healthcare leaders are increasingly sceptical of tools that promise intelligence but lack transparency or accountability.
“For the C-suite, clear outcomes, compliance and trust should be non-negotiable requirements for implementing AI,” said Frank Fawzi, CEO of IntelePeer.
Integration over Disruption
Another sign that experimentation is ending is how healthcare organisations approach deployment. Instead of replacing core platforms, they expect AI to fit into existing environments. Integration with electronic health records, practice management systems, and contact centre platforms is essential. This approach reduces risk, shortens deployment timelines, and allows staff to work within familiar systems. AI that requires a “rip-and-replace” strategy is increasingly seen as impractical.
When it comes to speed, AI initiatives should demonstrate return on investment within 90 days. Anything slower risks being deprioritised or cancelled altogether.
This focus on day-one value reflects financial pressure across the sector. Healthcare leaders are no longer funding AI because it is innovative. They are funding it because it can improve access, reduce administrative burden, and stabilise operations under strain.
Analytics Turn AI into Something Manageable
The report identifies analytics as the layer that makes AI usable at scale. By analysing transcripts, sentiment, outcomes, and workflow performance, organisations can monitor how AI behaves and adjust it over time.
This visibility is also critical for compliance and governance. When leaders can explain how AI decisions are made and show performance data, confidence increases across clinical and administrative teams.
Healthcare organisations delaying the adoption of integrated, compliant agentic AI may struggle to catch up. As interoperable, standards-based systems become more common, early adopters are gaining operational advantages that are difficult to reverse.
