< Projects

Title

A Study of AI As a New Strategic Imperative; Challenging Existing Strategies, Business Models and Organizational Processes

About the project

The national focus on artificial intelligence (Ministry of Trade and Industry, N2018.14) underscores the immense potential of AI to drive economic growth and address environmental and social challenges. However, the implementation of AI in both private and public sectors presents a range of complex challenges. This project is dedicated to building a knowledge platform that will explore and address key issues related to the adoption of new AI solutions.

The project focuses on three main types of challenges in the implementation of AI:

  1. Business Development Challenges
    These involve translating AI-generated big data analyses into value-creating services. The project will investigate how companies can effectively leverage AI insights to enhance their services and products.
  2. Organizational and Business Model Challenges
    Implementing AI often requires new organizational structures and business models. The project will explore how businesses can adapt and evolve to integrate AI into their operations effectively.
  3. Strategic and Structural Challenges
    This includes addressing issues related to the distribution of responsibilities, control of AI-related activities, and the broader market development connected to AI. The project will also examine the implementation of new business models, such as “AI-as-a-Service.”

To tackle these challenges, the project will establish a new multi-industrial platform and “think tank” to generate knowledge across industry boundaries. This collaborative approach aims to develop both practical and theoretical insights into the strategic challenges of AI implementation.

The project is structured into three key components:

  1. AI Business Lab
    A dedicated space for exploring AI-driven business development, where companies can experiment with and refine their AI strategies.
  2. Empirical and Basic Research
    A research-focused component that will investigate the foundational aspects of AI implementation, drawing on empirical data and theoretical analysis.
  3. Knowledge Integration
    This component will synthesize insights from the research and business development activities, ensuring that knowledge is effectively integrated and applied across industries.

Initially, up to four companies from different sectors will join the knowledge platform, contributing to and benefiting from its focus on AI-driven business development and implementation. The knowledge integration component will play a critical role in ensuring that findings from both the research and business development efforts are effectively combined and utilized to advance AI implementation across industries.

Duration

Start: 01 January 2021
End: 31 December 2023

Project type

MMW

Keywords

Universities and institutes

Stockholm School of Economics

Project members

Per Andersson

Per Andersson

Professor

Stockholm School of Economics

Christopher Rosenqvist

Associate Professor

Stockholm School of Economics