AI and Intelligent Automation
Identifying, designing and integrating AI and automation where it does real work and human oversight stays clear.
Typical business challenges
- Uncertainty about where AI fits
- Poor data readiness
- Governance and accountability concerns
Expected outcomes
- A prioritised set of use cases
- Working pilots with clear measures
- Defined human oversight
What the data says
of organisations regularly use AI in at least one business function, while most have not yet scaled it
Source: McKinsey State of AI, 2025of US non-federal acute care hospitals used predictive AI integrated with the EHR in 2024, up from 66% in 2023
Source: ASTP/ONC data brief, 2025of independent hospitals used predictive AI in 2024, against 86% of hospitals in multi-hospital systems
Source: ASTP/ONC data brief, 2025How we deliver it
Try it: Clinical Intelligence and Analytics
Decision support that predicts which patients need attention and shows why, with demand forecasts, executive dashboards and plain-language summaries. Use it for yourself, or
Estimate it for your organisation
Time spent on routine document and data entry work. Set your own numbers and your estimate updates instantly.
Based on 230 working days and 1,720 hours a year. An estimate from your inputs, not a guaranteed result.
Review this with our teamHow you can engage with REVONWELL
Often starts with a focused use-case workshop.