Project on AI Impact on Productivity

I have an active project in Artificial Intelligence impact on productivity that will run throughout 2018 and on to 2019/20. This builds on 4-5 years experience from previous work on AI Impact in 2016/17 and earlier digital business work in 2014/15.

This is a joint Industry, academic initiative that draws on the previous research and practice development in several fields to identify mechanisms and best practices for business use of AI in their strategy, products and services and value chain.

A primary goal is to understand and develop best practice in how AI changes productivity in human and machine tasks and job employment, the company operating models, products, and services creation and value and wider policy and ecosystem concerns.

The studies are practice-based evidence and involve the development of methodologies, metrics and business case to accelerate AI adoption and value creation in innovation and invention of automation and intelligent systems technologies applied to the machine and human work, business models, markets, and wider ecosystems.

The work introduces new techniques and methods in the fields of business strategy, data science, integration, devices/sensors and human-computing interactions. It also examines cross-cutting concerns in network and systems integration, cyber security, ethics, legal, governmental policy and commercial governance; metrics and issues from social, economic, environmentally and human well-being perspectives.

The project program involves companies in the public and private sector.

The work builds on my previous book publications in digital business strategy, building digital ecosystem integration platform architectures and recent work on Artificial Intelligence impact on business, social and societal systems.

The Publication: "The 4th Industrial Revolution: Responding to the impact of Artificial Intelligence on Business" provides background on several of the major business themes included in this project. More information is available on the microsite here.

For more information please contact Prof. Mark Skilton via email

mark.skilton@wbs.ac.uk

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