An AI decision-making framework for business value maximization

被引:2
|
作者
Gudigantala, Naveen [1 ,4 ]
Madhavaram, Sreedhar [2 ]
Bicen, Pelin [3 ]
机构
[1] Univ Portland, Robert B Pamplin Sch Business Adm, Portland, OR USA
[2] Texas Tech Univ, Jerry S Rawls Coll Business Adm, Lubbock, TX USA
[3] Suffolk Univ, Sawyer Business Sch, Dept Mkt, Boston, MA USA
[4] Univ Portland, Robert B Pamplin Sch Business Adm, Portland, OR 97203 USA
关键词
ARTIFICIAL-INTELLIGENCE; BIG DATA;
D O I
10.1002/aaai.12076
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This article addresses a key question of why businesses are failing to maximize business value from their artificial intelligence (AI) investments and proposes a strategic decision-making framework for AI decision-making to address this problem. We suggest that a firm's business strategy must drive AI-driven business outcomes and measurements, which in turn should drive the AI implementation decisions. Very often, we find that businesses fail to successfully cast business problems into AI problems. To bridge this gap, we propose that firms use a performance management system such as objectives and key results (OKRs) to ensure that the business and AI goals & objectives are well defined, tightly aligned, and made transparent across the company, and the AI efforts are approached in an integrated manner by the different parts of a firm. We use McDonald's use of AI initiatives as a business use case to demonstrate support for our AI decision-making framework. We argue that using the business strategy as a primary driver will enable firms to solve the right problems using AI, turning it to be a source of technology innovation and competitive advantage.
引用
收藏
页码:67 / 84
页数:18
相关论文
共 50 条
  • [1] Generative AI-Augmented Decision-Making for Business Information Systems
    Kromidha, Endrit
    Davison, Robert M.
    HUMAN CHOICE AND COMPUTERS, HCC 2024, 2024, 719 : 46 - 55
  • [2] AI-Assisted Decision-making in HealthcareThe Application of an Ethics Framework for Big Data in Health and Research
    Tamra Lysaght
    Hannah Yeefen Lim
    Vicki Xafis
    Kee Yuan Ngiam
    Asian Bioethics Review, 2019, 11 : 299 - 314
  • [3] AI-Assisted Decision-making in Healthcare: The Application of an Ethics Framework for Big Data in Health and Research
    Lysaght, Tamra
    Lim, Hannah Yeefen
    Xafis, Vicki
    Ngiam, Kee Yuan
    ASIAN BIOETHICS REVIEW, 2019, 11 (03) : 299 - 314
  • [4] Managerial Perception of AI in Strategic Decision-Making
    Chaturvedi, Anurag
    Dasgupta, Meeta
    JOURNAL OF COMPUTER INFORMATION SYSTEMS, 2024,
  • [5] The roles of AI and educational leaders in AI-assisted administrative decision-making: a proposed framework for symbiotic collaboration
    Dai, Ruixun
    Thomas, Matthew Krehl Edward
    Rawolle, Shaun
    AUSTRALIAN EDUCATIONAL RESEARCHER, 2025, 52 (02) : 1471 - 1487
  • [6] Improving environmental decision-making in environmental business-management using big data and AI
    Vagin, Sergei G.
    Klimenko, Viktor A.
    Telegina, Zhanna A.
    Aleksashina, Tatiana, V
    FRONTIERS IN ENVIRONMENTAL SCIENCE, 2022, 10
  • [7] Big data and decision-making in international business
    Ulman, Milos
    Musteen, Martina
    Kanska, Eva
    THUNDERBIRD INTERNATIONAL BUSINESS REVIEW, 2021, 63 (05) : 597 - 606
  • [8] Human Control and Discretion in AI-driven Decision-making in Government
    Mitrou, Lilian
    Janssen, Marijn
    Loukis, Euripidis
    14TH INTERNATIONAL CONFERENCE ON THEORY AND PRACTICE OF ELECTRONIC GOVERNANCE (ICEGOV 2021), 2021, : 10 - 16
  • [9] Artificial intelligence (AI) in strategic marketing decision-making: a research agenda
    Stone, Merlin
    Aravopoulou, Eleni
    Ekinci, Yuksel
    Evans, Geraint
    Hobbs, Matt
    Labib, Ashraf
    Laughlin, Paul
    Machtynger, Jon
    Machtynger, Liz
    BOTTOM LINE, 2020, 33 (02) : 183 - 200
  • [10] A Framework for AI-enabled Proactive mHealth with Automated Decision-making for a User's Context
    Sulaiman, Muhammad
    Hakansson, Anne
    Karlsen, Randi
    HEALTHINF: PROCEEDINGS OF THE 15TH INTERNATIONAL JOINT CONFERENCE ON BIOMEDICAL ENGINEERING SYSTEMS AND TECHNOLOGIES - VOL 5: HEALTHINF, 2021, : 111 - 124