The role of firm AI capabilities in generative AI-pair coding DOI
Jacques Bughin

Journal of Decision System, Год журнала: 2024, Номер unknown, С. 1 - 22

Опубликована: Ноя. 27, 2024

Generative Artificial Intelligence (genAI) is the latest evidence of transformative value AI in organisations. One promising avenue software engineering, where genAI can contribute to coding by pairing with developers. Based on a sample global companies, two key findings emerge from an analysis productivity impact pair coding. Coding quality negatively correlated throughput gains, while quality-adjusted gains depend extent which firms have deployed capabilities form data, skills upgrading and governance. As observed other digital technologies, success using closely linked complementary technical organisational resources.

Язык: Английский

Beware of botshit: How to manage the epistemic risks of generative chatbots DOI
Timothy R. Hannigan, Ian P. McCarthy,

André Spicer

и другие.

Business Horizons, Год журнала: 2024, Номер 67(5), С. 471 - 486

Опубликована: Март 20, 2024

Язык: Английский

Процитировано

33

Creational and conversational AI affordances: How the new breed of chatbots is revolutionizing knowledge industries DOI Creative Commons

Laavanya Ramaul,

Paavo Ritala,

Mika Ruokonen

и другие.

Business Horizons, Год журнала: 2024, Номер 67(5), С. 615 - 627

Опубликована: Май 24, 2024

The new generative AI paradigm offers unprecedented opportunities for users to tap into. capabilities are increasingly helpful in creative and knowledge-intensive domains that have long been considered a territory of human expertise. breed chatbots is based on large language models, they overcome many constraints plague the everyday use previous technologies. This article employs theory affordances understand how ChatGPT facilitates (i.e., affords) disaffords) usefulness chatbots. We further divide two distinct yet interrelated dimensions affordances: creational conversational. Using 29 interviews with professionals using various sectors, we identify three (content creation enhancement, knowledge acquisition creativity augmentation, task automation) conversational (contextual sensitivity, interactive accessibility, human–AI workflow synergy) affordances. Creational refer system's ability produce novel outputs as well automate routine work, whereas encompass variety interaction possibilities an system. Interestingly, both also involve disaffordances limit types systems. Furthermore, introduce integrated framework shows reinforce each other via meta-affordances accumulation, adaptability. illustrate our findings practical examples offer guidelines these emerging company settings.

Язык: Английский

Процитировано

20

Managing a ChatGPT-empowered workforce: Understanding its affordances and side effects DOI Creative Commons
Jana Retkowsky, Ella Hafermalz, Marleen Huysman

и другие.

Business Horizons, Год журнала: 2024, Номер 67(5), С. 511 - 523

Опубликована: Апрель 6, 2024

Generative AI, particularly ChatGPT, creates new managerial concerns. This article addresses a crucial challenge: While employees are including the tool as their private knowledge assistant in many aspects of daily work, it is difficult for managers to see and understand impact within organization. There more literature on what ChatGPT means business, but we cannot say much long uninformed about its actual use. So, getting an insider's perspective needed think consequences organizations. The grounded qualitative study employees' experiences interacting with among 50 early adopters. First, show how employee-ChatGPT relations develop from private, experimental use into integral part work. Second, identify six affordances: searching information, brainstorming ideas, structuring content, writing first draft, embellishing text, proofing Further, highlight three looming side effects that threaten ties, quality organizations, work roles configured. Accordingly, this offers guidance managing ChatGPT-empowered workforce way aims mitigate these while harnessing opportunities.

Язык: Английский

Процитировано

17

Written by ChatGPT: AI, large language models, conversational chatbots, and their place in society and business DOI
Jan Kietzmann, Andrew Park

Business Horizons, Год журнала: 2024, Номер 67(5), С. 453 - 459

Опубликована: Июнь 1, 2024

Язык: Английский

Процитировано

17

Generative artificial intelligence: a proactive and creative tool to achieve hyper-segmentation and hyper-personalization in the tourism industry DOI
Lázaro Florido-Benítez

International Journal of Tourism Cities, Год журнала: 2024, Номер unknown

Опубликована: Окт. 29, 2024

Purpose The purpose of this paper is to explore how GenAI can help companies achieve a higher level hyper-segmentation and hyper-personalization in the tourism industry, as well show importance disruptive tool for marketing. Design/methodology/approach This used Web Science Google Scholar databases provide updated studies expert authors industry. Analysing modalities through their new challenges tourists, cities companies. Findings reveal that technology exponentially improves consumers’ segmentation personalization products services, allowing organizations create tailored content real-time. That why concept substantially focused on customer (understood segment one) his or her preferences, needs, personal motivations purchase antecedents, it encourages design services with high individual scalability performance called hyper-personalization, never before seen Indeed, contextualizing experience an important way enhance personalization. Originality/value also contributes enhancing bootstrapping literature industry because field study, its functional operability incubation stage. Moreover, viewpoint facilitate researchers successfully integrate into different travel activities without expecting utopian results. Recently, there have been no tackle methodologies

Язык: Английский

Процитировано

15

A framework of diversity, equity, and inclusion safeguards for chatbots DOI Creative Commons

Esraa Abdelhalim,

Kemi S. Anazodo,

Nazha Gali

и другие.

Business Horizons, Год журнала: 2024, Номер 67(5), С. 487 - 498

Опубликована: Март 21, 2024

Язык: Английский

Процитировано

13

Navigating the challenges of generative technologies: Proposing the integration of artificial intelligence and blockchain DOI

Jordan Brewer,

Dhru Patel,

Dennie Kim

и другие.

Business Horizons, Год журнала: 2024, Номер 67(5), С. 525 - 535

Опубликована: Апрель 12, 2024

Язык: Английский

Процитировано

8

Managerial framework for evaluating AI chatbot integration: Bridging organizational readiness and technological challenges DOI Creative Commons
Roberto Urbani, Caitlin Ferreira, Joey Lam

и другие.

Business Horizons, Год журнала: 2024, Номер 67(5), С. 595 - 606

Опубликована: Май 21, 2024

The ubiquity of chatbots continues to expand offering a multitude benefits for firms. While acknowledging the capabilities AI handle customer interactions and improve response times, we critically examine several challenges they present - including interoperability challenges, data protection concerns, biased output. This research presents novel framework managers assess firm's readiness adopt chatbot technology through lens Technology Acceptance Model (TAM) which has been adapted account critical associated with emerging technology. Incorporating four factors namely subjective norms, compatibility, facilitating conditions trust allows more holistic assessment framework, together tool, provides comprehensive mechanism managerial decision-making, focusing on adoption enhancing strategic implementation these technologies in service, sales, marketing business functions. By exploring extended factors, our article offers an in-depth perspective implications integrating into processes, ensuring informed approach adoption.

Язык: Английский

Процитировано

8

Mechanical Structure Design and Motion Simulation Analysis of a Lower Limb Exoskeleton Rehabilitation Robot Based on Human–Machine Integration DOI Creative Commons
Chenglong Zhao, Zhen Liu, Yvonne Ou

и другие.

Sensors, Год журнала: 2025, Номер 25(5), С. 1611 - 1611

Опубликована: Март 6, 2025

Population aging is an inevitable trend in contemporary society, and the application of technologies such as human-machine interaction, assistive healthcare, robotics daily service sectors continues to increase. The lower limb exoskeleton rehabilitation robot has great potential areas enhancing human physical functions, training, assisting elderly disabled. This paper integrates structural characteristics limb, motion mechanics, gait features design a biomimetic structure proposes integrated robot. Human data are collected using Optitrack optical 3D capture system. SolidWorks modeling software Version 2021 used create virtual prototype exoskeleton, kinematic analysis performed standard Denavit-Hartenberg (D-H) parameter method. Kinematic simulations carried out Matlab Robotic Toolbox R2018a with derived D-H parameters. A was fabricated tested verify validity controller based on BP fuzzy neural network PID control designed ensure stability walking. By comparing two sets simulation results, it shown that outperforms other methods terms overshoot settling time. specific conclusions follows: after multiple walking tests, robot's process proved be relatively safe stable; when control, there no significant oscillation, 5.5% time 0.49 s, but speed slow, approximately 0.18 m/s, stride length about 32 cm, cycle duration 1.8 s. model proposed this can effectively assist patients recovering their ability walk. However, still faces challenges, slow speed, large size, heavy weight, which need optimized improved future research.

Язык: Английский

Процитировано

0

Generative artificial intelligence chatbots in investment decision-making: a phantom menace or a new hope? DOI

Kumbirai Mabwe,

Nasir Aminu, Stanislav Ivanov

и другие.

foresight, Год журнала: 2025, Номер unknown

Опубликована: Март 6, 2025

Purpose This study aims to investigate the relevance, accuracy, specificity and justification of investment recommendations generative artificial intelligence (GenAI) chatbots for different capitals countries (UK Bulgaria). Design/methodology/approach A two-stage mixed methods approach was used. Prompts were queried into OpenAI’s ChatGPT, Microsoft Bing Google Bard (now Gemini). Finance practitioners finance lecturers assessed chatbots’ through an online questionnaire using a five-point Likert scale. The Chi-squared test, Wilcoxon-signed ranks Mann–Whitney U test Friedman used data analysis compare GenAIs’ UK Bulgaria across amounts capital assess consistency chatbots. Findings GenAI responses found perform medium-to-high in terms justification. For sample, amount had marginal effect but prompt timing interesting impact. Unlike British application, did not significantly influence Bulgarian respondents’ evaluations. While mean sample slightly higher, these differences statistically significant, indicating that performed similarly both Bulgaria. Originality/value assesses two periods, countries.

Язык: Английский

Процитировано

0