By Dr. Elissa Farrow
September 21, 2022
Views on Artificial Intelligence (AI), its future use and impact on organisations and society are often polarised (Farrow, 2019; van Belkom, 2020). It is a swinging narrative of either AI being human’s salvation and great hope, or being the enemy that brings vulnerability, enhanced discrimination to workers and pain (ibid). Given the widespread implications of AI on the deeper and fundamental challenge of concepts of the human’s contribution to the nature and concept of work and its futures (amongst other themes), this article will outline a number of implications for transformation teams and provide an opportunity to consider future transformation team scenarios. Transformation teams are defined here as either project, program, change teams working to introduce a new form of capability into the organisation.
Firstly, there needs to be close connectivity between the strategisers of the organisation’s future and designers/builders of the AI technology (Farrow, 2021). AI is already maximising the data analytic and interpretation power of transformation teams in several transformation office contexts. Any decision to introduce AI into a transformation office context needs to consider what the use cases the AI is intended to achieve, what it is not to achieve and what processes and data sets are required for a viable solution.
Secondly, larger global portfolios, are already benefiting from speed of issues identification and resolution via AI. In the past a process that would take a person or team twenty hours to do in a more manual way, can take a suitably designed AI algorithm, fed with appropriate quality data, and process an outcome in under one minute. When AI data interpretation is incorporated into decision making processes, there needs to be total trust and confidence in the interpretation calculation approach, the quality of the original data input and any risks of utilising the interpretation. Data cleansing and data governance becomes critical when AI mechanisms are being used in portfolio decision and monitoring processes.
Finally, transformation teams involved in AI are often explorers, forging new ground. Transformation teams need to facilitate deep discussions with not only decision makers, but the end users of AI applications on how the change in technology, process and Human to AI ratio (Farrow, 2022), will operate, and also what choice and control end users have if they disagree with an interpretation done by a machine. Many organisations will use more agile and flexible forms of delivery to not only deliver AI programs but use AI in transformation delivery. The good news is that organisations can choose their own adventure and ideally embed ethical prioritisation processes into codes of conduct and practice standards.
Farrow, E. (2019). To augment human capacity – artificial intelligence evolution through causal layered analysis. Futures, 108, 61-71. https://doi.org/10.1016/j.futures.2019.02.022)
Farrow, E. (2021) Extending the participant’s voice to guide artificial intelligence installation using futures methodology and layered user story analysis. World Futures Review.
Farrow, E. (2022) Determining the Human:AI Workforce Ratio – Exploring Future Organisational Scenarios and the Implications for Anticipatory Workforce Planning. Journal of Technology in Society.
van Belkom, R. (2020). The Impact of Artificial Intelligence on the Activities of a Futurist. World
Futures Review. 12(2):156-168. doi:10.1177/1946756719875720
Senior Consultant and Facilitator, International Institute of Learning