Barriers to the Implementation of AI in Organizations: Findings from a Delphi Study

Bérubé, Mathieu; Giannelia, Tanya; Vial, Grégory

doi:10.24251/hicss.2021.805

Cited by 23 publications

(7 citation statements)

References 31 publications

(53 reference statements)

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“…Extant research on the challenges of adopting AI for public service delivery has pointed to barriers related to AI-specific capabilities, including capabilities for managing algorithmic performance and data governance, more general technical and managerial capabilities, and regulatory hurdles (Sun and Medaglia, 2019;Wirtz et al, 2019;Mikalef et al, 2022). These barriers rhyme with the ones identified for AI adoption by organizations beyond the public sector (Bérubé et al, 2021). Schmager (2022) found that existing approaches cannot be directly translated to the public sector context and need to be adapted and individually scrutinized.…”

Section: Ai In Public Service Deliverymentioning

confidence: 99%

Exploring citizens’ stances on AI in public services: A social contract perspective

Schmager,

Grøder,

Parmiggiani

et al. 2024

Data & Policy

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This paper explores citizens’ stances toward the use of artificial intelligence (AI) in public services in Norway. Utilizing a social contract perspective, the study analyzes the government–citizen relationship at macro, meso, and micro levels. A prototype of an AI-enabled public welfare service was designed and presented to 20 participants who were interviewed to investigate their stances on the described AI use. We found a generally positive attitude and identified three factors contributing to this: (a) the high level of trust in government (macro level); (b) the balanced value proposition between individual and collective needs (meso level); and (c) the reassurance provided by having humans in the loop and providing transparency into processes, data, and model’s logic (microlevel). The findings provide valuable insights into citizens’ stances for socially responsible AI in public services. These insights can inform policy and guide the design and implementation of AI systems in the public sector by foregrounding the government–citizen relationship.

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Section: Ai In Public Service Deliverymentioning

confidence: 99%

Exploring citizens’ stances on AI in public services: A social contract perspective

Schmager,

Grøder,

Parmiggiani

et al. 2024

Data & Policy

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“…Although AI systems can bring many benefits to the workplace, it is important to recognise that their use does not always and automatically lead to a systematic improvement in employees' skills. According to the literature (Alsheibani et al, 2019;Bérubé et al, 2021;Nylin et al, 2022), if not properly managed, the use of AI in the workplace and the related organisational changes may improve or increase employees' skills while limiting the pace of work and reduce employees' autonomy. Indeed, increased complexity and more need for interaction and adaptability are introduced when AI is introduced.…”

Section: 2020)mentioning

confidence: 99%

The Impact of Artificial Intelligence on Workers’ Skills: Upskilling and Reskilling in Organisations

et al. 2023

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Aim/Purpose: This paper aims to investigate the recent developments in research and practice on the transformation of professional skills by artificial intelligence (AI) and to identify solutions to the challenges that arise. Background: The implementation of AI in various organisational sectors has the potential to automate tasks that are currently performed by humans or to reduce cognitive workload. While this can lead to increased productivity and efficiency, these rapid changes have significant implications for organisations and workers, as AI can also be perceived as leading to job losses. Successfully adapting to this transformation will lead companies and institutions to new working and organisational models, which requires implementing measures and strategies to upskill or reskill workers. Organisations, therefore, face considerable challenges such as guiding employees towards the change process, dealing with the cost of training, and ensuring fairness and inclusion posed by age, gender, and cultural diversity. Methodology: A narrative review has been conducted to analyse research and practice on the impact of AI on human skills in organisations. Contribution: This work contributes to the body of knowledge by examining recent trends in research and practice on how AI will transform professional skills and workplaces, highlighting the crucial role played by transversal skills and identifying strategies that can support organisations and guide workers toward the upskilling and reskilling challenges. Findings: This work found that introducing AI in organisations combines many organisational strategies simultaneously. First, it is critical to map the transversal skills needed by workers to mitigate the current skills gap within the workplace. Secondly, organisations can help workers identify the skills required for AI adoption, improve current skills, and develop new skills. In addition, the findings show that companies need to implement processes to support workers by providing ad hoc training and development opportunities to ensure that workers’ attitudes and mental models towards AI are open and ready for the changing labour market and its related challenges. Recommendation for Researchers: AI is a complex and multifaceted field that encompasses a wide range of disciplines, including computer science, mathematics, engineering, and behavioural and social sciences. Researchers should take a transdisciplinary approach to enable the integration of knowledge and perspectives from different fields that are essential to understanding the full range of implications and applications of AI. Future Research: Further research is needed to understand the impact of AI on human skills and the role of soft skills in the adoption of AI in organisations. Future studies should also consider the challenges presented by Industry 5.0, which is likely to involve the integration of new technologies and automation on an even greater scale.

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“…Although opportunities for AI in the public sector are exciting, it is not used as much by the government as by the private sector (Bailey and Barley, 2020), and research on the AI-backed public service delivery is few and far between (Kankanhalli et al , 2019). This is because AI is a complicated field with a steep learning curve, and the government has a unique purpose and environment that makes it hard to use (Bérubé et al , 2021; Mahmoud et al , 2020). The notion that AI will increasingly match or exceed human performance in terms of the work roles implies that there shall be a radical transformation of the operational edifices of the public sector, thereby disrupting the conventional public administration practices (Agrawal Gans and Goldfarb, 2017; Füller et al , 2022).…”

Section: Basic Conceptsmentioning

confidence: 99%

Integration of artificial intelligence of things (AIoT) in the public sector: drivers, barriers and future research agenda

Ishengoma

Shao²,

Alexopoulos³

et al. 2022

DPRG

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Purpose With the development of information technology (IT), governments around the globe are using state-of-the-art IT interfaces to implement the so-called 3E’s in public service delivery, that is, economy, efficiency and effectiveness. Two of these IT interfaces relate to Artificial Intelligence (AI) and Internet of Things (IoT). While AI focuses on providing a “human” garb for computing devices, thereby making them “intelligent” devices, IoT relies on interfaces between sensors and the environment to make “intelligent” decisions. Recently, the convergence of AI and IoT – also referred to as Artificial Intelligence of Things (AIoT) – is seen as a real opportunity to refurbish the public service delivery formats. However, there is limited understanding as to how AIoT could contribute to the improvisation of public service delivery. This study aims to create a modular framework for AIoT in addition to highlighting the drivers and barriers for its integration in the public sector. Design/methodology/approach This descriptive-explanatory study takes a qualitative approach. It entails a thorough examination of the drivers and barriers of integrating AI and IoT in the public sector. A review of literature has led to the development of a conceptual framework outlining the various factors that contribute to creating public value. Findings Value creation occurs when AI and IoT coalesce in the public service delivery mechanisms. Originality/value AIoT is a cutting-edge technology revolutionizing health care, agriculture, infrastructure and all other industrial domains. This study adds to the growing body of knowledge on the public sector's use of AI and IoT. Understanding these disruptive technologies is critical to formulating policies and regulations that can maximize the potential benefits for the public-sector organizations.

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Barriers to the Implementation of AI in Organizations: Findings from a Delphi Study

Cited by 23 publications

References 31 publications

Exploring citizens’ stances on AI in public services: A social contract perspective

Exploring citizens’ stances on AI in public services: A social contract perspective

The Impact of Artificial Intelligence on Workers’ Skills: Upskilling and Reskilling in Organisations

Integration of artificial intelligence of things (AIoT) in the public sector: drivers, barriers and future research agenda

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