The future of education is a site of struggle and contestation among a vast variety of actors, organisations and interests (Robertson 2022). Dominant visions of education futures are often framed by technocratic elites that can mobilise ideational and material resources and anticipatory expertise to delineate authoritative scenarios and visions (Facer & Sriprakash 2021). Educational futures are currently being inscribed in discursive visions of ‘digital transformation’ by political, industry and financial actors (Clark 2023), furthermore underpinned by quantitative valuation claims about the prospective economic returns from educational technology (edtech) investment (Williamson & Komljenovic 2022). The specific methods of market prediction used to calculate future edtech value, how these valuation methods inform visions of digital educational transformation, and the promissory politics that infuse such efforts are the original focus of this paper. Sociological work on expectations and futures examines the practices and political contests through which ‘promissory authorities’ construct and circulate visions (Tutton 2017). ‘Techniques of futuring’ refer to the practical ways selected futures are constructed, attract interest, and foster investments as ‘authoritative orientations for action’ (Oomen et al 2022). Futuring techniques span from creative and imaginative practices to calculative, rational and scientific methodologies like predictive forecasting and modelling, and are part of a ‘politics of expectation’ (Beckert 2016). Our contribution conceptualises ‘algorithmic futuring’ as the design and use of data-driven technologies and methods to predict educational futures and animate actions in the present towards their materialisation. Algorithmic futuring is part of a contemporary tendency to apply predictive techniques to societal problems, materialised in ‘technologies of speculation’ through which ‘social problems are made conceivable only as objects of calculative control’ (Hong 2022). We identify and examine promissory authorities where futures are constructed through algorithmic futuring methodologies in terms of edtech value, including management consultancies, think tanks and market intelligence agencies. Their algorithmic futuring methods include edtech market prediction with machine learning, natural language processing and clustering algorithms, aimed at directing venture capital investments towards high-value yields; and data-scientific predictions constructed by think tanks and consultancies to convince politicians and policymakers to invest in digital education as a route to long-term economic value. Algorithmic futuring constitutes a methodological practice that combines technologies of speculation with calculative and predictive practices of valuation. It functions to delimit the desirability of educational futures in terms of prospective future edtech value, exemplifying the speculative technologies, methods and promissory politics involved in performing predictive futures into existence.

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