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How to succeed with an AI-first strategy?

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WorkDifferentWithAI.com Academic Paper Alert!

Written by Mika Ruokonen, Paavo Ritala

Category: AI Strategy & Governance

Article Section: AI Strategy and Governance; Best Practices for AI Adoption

Publication Date: 2023-01-01

SEO Description: “Strategies for AI-first adoption, competitive advantages, and AI’s strategic business role across industries explored.”

Keywords

artificial intelligence, algorithms, strategy, competitive advantage, generative AI

AI-Generated Paper Summary

Generated by Ethical AI Researcher GPT

The academic paper titled “How to succeed with an AI-first strategy?” by Mika Ruokonen and Paavo Ritala, focuses on the strategic implementation of AI in businesses. The paper is comprehensive and addresses several key areas:

Novelty

  1. AI-First Approach: The paper delves into the concept of an AI-first strategy, a relatively new and evolving area in strategic management. It brings fresh perspectives on how companies can integrate AI into their core strategies.
  2. Three AI-First Strategy Archetypes: The authors introduce distinct strategic archetypes for AI implementation: Digital Tycoon, Niche Carver, and Asset Augmenter. This framework offers a novel approach to categorizing AI strategies based on a company’s nature and operational focus.

Merit

  1. Real-World Examples: The paper is enriched with practical examples from various industries, demonstrating how AI is being strategically adopted. Examples like GE, JPMorgan Chase, PayPal, Netflix, and Spotify illustrate the tangible benefits and challenges of AI in business.
  2. Comprehensive Analysis: The authors provide a well-rounded discussion, including potential bottlenecks and strategic challenges associated with each AI-first archetype. This makes the paper valuable for both academics and practitioners.
  3. Generative AI Focus: Attention to the rise of generative AI tools and their impact on business strategies is particularly timely and relevant, considering the rapid advancements in this area.

Commercial Applications

  1. Guidance for Business Strategy: Businesses can utilize the insights to shape their AI strategies. For instance, companies in traditional industries can learn from the Asset Augmenter archetype to integrate AI in enhancing their physical assets.
  2. Framework for AI Strategy Development: The archetypes and examples provide a framework that companies can use to assess their current position and potential AI strategy.
  3. Risk and Bottleneck Identification: Understanding potential risks and bottlenecks in AI implementation can aid businesses in planning and mitigating these challenges.

Overall Assessment

  • The paper is a significant contribution to the understanding of how AI can be strategically implemented in various business contexts.
  • Its focus on different strategic archetypes makes it applicable to a broad range of industries.
  • It balances academic rigor with practical relevance, making it a valuable resource for both researchers and business leaders.

The insights from this paper can be instrumental in guiding businesses on the path to becoming AI-first, helping them navigate the complexities and maximize the benefits of AI integration

Author’s Abstract

Purpose The purpose of this paper is to identify the potential and the challenges for different firms in adopting an AI-first strategy. The study attempts to discern if any company can prioritize AI at the forefront of their strategic plans.Design/methodology/approach Drawing from illustrative examples from well-known AI-leaders like Netflix and Spotify, as well as from upcoming AI startups and industry incumbents, the paper explores the strategic role of AI in core business processes and customer value creation. It also discusses the advent and implications of generative AI tools since late 2022 to firms’ business strategies.Findings The authors identify three types of AI-first strategies, depending on firms’ starting points: digital tycoon, niche carver and asset augmenter. The authors discuss how each strategy can aim to achieve data, algorithmic and execution advantages, and what the strategic bottlenecks and risks are within each strategy.Originality/value To the best of the authors’ knowledge, this paper is the first to systematically describe how companies can form “AI-first” strategies from different starting points. This study includes actionable examples from known industry players to more emerging startups and industrial incumbents.

Read the full paper here

Last updated on November 26th, 2023.