ITEA is the Eureka Cluster on software innovation
ITEA is the Eureka Cluster on software innovation

ResilientEnterprise

Improving Resilience of Enterprise Workforce and AI to Operational Challenges

Project description

Resilience is an ability to recover from or adjust easily to adversity or change . As operational environment of enterprises becomes increasingly more dynamic and complex, it becomes necessary to improve enterprise resilience to various kinds of changes. Human workforce is the key to enterprise success; hence, from user point of view, the main goal of this project is to advance abilities of enterprises to create perceptive and sustainable workplaces. Since nowadays role of AI in enterprise operations is increasing, it implies necessity to advance AI, especially, to advance AI adaptation abilities in realistic ways, i.e., by employing human oversight, but not requiring notable oversight efforts. Currently, there is no “one-fits-all-problems” AI solution, and methods for AI-based solutions to evolve with time, e.g., to adapt to gradual (e.g., employee ageing) and abrupt (e.g., moving to a new building) changes are very limited. This project will develop “resilience by design” framework and implement it in selected use cases: 1. Perceptive sustainable workplace: solutions to support engaging and effective work (in office, construction, factory) by making operations smooth, upskilling employees, and reducing risks for them, while also improving sustainability of enterprise assets, e.g., abilities of buildings and property maintenance to adapt to climate change. 2. Hospital robots: advancing robots ability to operate independently in dynamic hospital environments and to relief hospital staff from mundane tasks. 3. Driver readiness: boosting readiness of elderly drivers in semi-autonomous vehicles, i.e., to help elderly drivers to adapt quicker to road changes, such as the need to take control over advanced driving monitoring system. These use cases will develop (1) innovative solutions to improve resilience and sustainability of workplaces and hereby to assess and to assist in mitigating employee risks (such as stress, work overload, urgent unscheduled work tasks, lack of skills/ readiness to drive/ extreme weather etc.) and (2) methods to adapt these solutions to specifics of each enterprise, user group or individual and (3) methods to gain user trust, such as explainability. These solutions and methods will be developed in use case – specific ways and generalised to facilitate development of resilience in other domains. The selected use cases have high business potential and will impact smart buildings, manufacturing, construction, robotic and automotive markets. Developed methods to use AI in long term in dynamic realistic settings will have high business potential in the above-listed and other domains because according to Forbes, implementing AI in a way that will still prove useful “a year from now” is among the biggest challenges for AI adoption by business.

Project leader

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Finland

Korea, Republic of

Portugal

Romania

Switzerland

United Kingdom

Swift Robotics

United Kingdom

The Open University

United Kingdom

Project publications