Key success factors
Our experience includes three key factors that help organizations identify, develop and deploy AI to maximize profits and drive productivity.
1. Integration into workflows
It is important to consider existing workflows and processes even in the non-clinical field. AI solutions must be integrated with other systems and methods of work (including data collection and re-entry into other “main” systems). Otherwise, you'll create more work and take longer overall.
2. Identifying and tracking benefits
Given the importance of increasing efficiency and productivity, it is essential to have a baseline performance and a mechanism to monitor the benefits provided. It is wise to evaluate the pilot solution, and to determine whether or not to scale, depending on the results.
The roadmap should be self-funded whenever possible, and start with Quickwin's stage where you can improve your services and release cash. This could fund subsequent phases consisting of increasingly complex and ambitious opportunities. This iterative approach helps you earn shopping and maintain momentum through transformation.
3. Take an approach proportional to assessment and risk
Non-clinical AI Solutions Evaluation We are looking for a different approach to clinical AI solutions. For example, it is unlikely that a randomized controlled trial would be required. Pragmatic evaluation methodology is necessary to balance rigour and execution timelines and match the rapidly changing landscape of AI technology.
Mang risk remains a critical requirement for non-clinical AI solutions. The KPMG Trusted AI Approach is a methodology that designs, builds, deploys and uses AI strategies and solutions in a responsible and ethical way. It consists of 10 important elements[viii]:
