https://sloanreview.mit.edu/article/philosophy-eats-ai/ MIT Sloan Management Review Logo Menu Search [ ] Topics < Back to Menu * Data, AI, & Machine Learning * Innovation * Leadership * Managing Technology * Marketing * Operations * Social Responsibility * Strategy * Workplace, Teams, & Culture * All Topics * Trending * AI & Machine Learning * Organizational Culture * Hybrid Work Our Research < Back to Menu * Big ideas Research Projects * Artificial Intelligence and Business Strategy * Responsible AI * Future of the Workforce * Future of Leadership * All Research Projects Spotlight < Back to Menu * Most Popular * AI in Action * Hybrid Work * Coaching for the Future-Forward Leader * Culture Champions * Measuring Culture Magazine < Back to Menu Winter 2025 IssueWinter 2025 Issue Winter 2025 Issue Our winter 2025 issue focuses on improving work design, implementing AI, increasing employee engagement, and more. * Past Issues Webinars & Podcasts < Back to Menu * Upcoming Events * Video Archive * Podcasts * Me, Myself, and AI Subscribe Now Save 22% on Unlimited Access. [svg][Winter2025] Subscribe Topics * Data, AI, & Machine Learning * Innovation * Leadership * Managing Technology * Marketing * Operations * Social Responsibility * Strategy * Workplace, Teams, & Culture * All Topics * Trending * AI & Machine Learning * Organizational Culture * Hybrid Work Our Research * Big ideas Research Projects * Artificial Intelligence and Business Strategy * Responsible AI * Future of the Workforce * Future of Leadership * All Research Projects Spotlight * Most Popular * AI in Action * Hybrid Work * Coaching for the Future-Forward Leader * Culture Champions * Measuring Culture Magazine Winter 2025 IssueWinter 2025 Issue Winter 2025 Issue Our winter 2025 issue focuses on improving work design, implementing AI, increasing employee engagement, and more. * Past Issues Webinars & Podcasts * Upcoming Events * Video Archive * Podcasts * Me, Myself, and AI Search Store Sign In Subscribe -- 22% off MIT Sloan Management Review LogoMIT Sloan Management Review Logo Philosophy Eats AI Generating sustainable business value with AI demands critical thinking about the disparate philosophies determining AI development, training, deployment, and use. Michael Schrage and David Kiron January 16, 2025 Reading Time: 32 min Topics * Data, AI, & Machine Learning * Disruption * AI & Machine Learning * Technology Implementation Subscribe Permissions and PDF Share Twitter Facebook Linkedin [svg][Kiron-1290] Carolyn Geason-Beissel/MIT SMR | Getty Images In 2011, coder-turned-venture-investor Marc Andreessen famously declared, "Software is eating the world" in the analog pages of The Wall Street Journal. His manifesto described a technology voraciously transforming every global industry it consumed. He wasn't wrong; software remains globally ravenous. Not six years later, Nvidia cofounder and CEO Jensen Huang boldly updated Andreesen, asserting, "Software is eating the world ... but AI is eating software." The accelerating algorithmic shift from human coding to machine learning led Huang to also remark, "Deep learning is a strategic imperative for every major tech company. It increasingly permeates every aspect of work, from infrastructure to tools, to how products are made." Nvidia's multitrillion-dollar market capitalization affirms Huang's prescient 2017 prediction. But even as software eats the world and AI gobbles up software, what disrupter appears ready to make a meal of AI? The answer is hiding in plain sight. It challenges business and technology leaders alike to rethink their investment in and relationship with artificial intelligence. There is no escaping this disrupter; it infiltrates the training sets and neural nets of every large language model (LLM) worldwide. Get Updates on Leading With AI and Data Get monthly insights on how artificial intelligence impacts your organization and what it means for your company and customers. [ ] sign up Please enter a valid email address Thank you for signing up Privacy Policy Philosophy is eating AI: As a discipline, data set, and sensibility, philosophy increasingly determines how digital technologies reason, predict, create, generate, and innovate. The critical enterprise challenge is whether leaders will possess the self-awareness and rigor to use philosophy as a resource for creating value with AI or default to tacit, unarticulated philosophical principles for their AI deployments. Either way -- for better and worse -- philosophy eats AI. For strategy-conscious executives, that metaphor needs to be top of mind. While ethics and responsible AI currently dominate philosophy's perceived role in developing and deploying AI solutions, those themes represent a small part of the philosophical perspectives informing and guiding AI's production, utility, and use. Privileging ethical guidelines and guardrails undervalues philosophy's true impact and influence. Philosophical perspectives on what AI models should achieve (teleology), what counts as knowledge (epistemology), and how AI represents reality (ontology) also shape value creation. Without thoughtful and rigorous cultivation of philosophical insight, organizations will fail to reap superior returns and competitive advantage from their generative and predictive AI investments. This argument increasingly enjoys both empirical and technical support. Topics * Data, AI, & Machine Learning * Disruption * AI & Machine Learning * Technology Implementation About the Authors Michael Schrage is a research fellow with the MIT Sloan School of Management's Initiative on the Digital Economy. His research, writing, and advisory work focuses on the behavioral economics of digital media, models, and metrics as strategic resources for managing innovation opportunity and risk. David Kiron is the editorial director, research, of MIT Sloan Management Review and program lead for its Big Ideas research initiatives. References 1. L. Burgis, "The Philosophy of Peter Thiel's 'Zero to One,'" Medium, May 9, 2022, https://luke.medium.com; P. Westberg, "Alex Karp: The Unconventional Tech Visionary," Quartr, May 8, 2024, https: //quartr.com; F.-F. Li, "The Worlds I See: Curiosity, Exploration, and Discovery at the Dawn of AI." (New York: Flatiron Books, 2023); and S. Wolfram, "How to Think Computationally About AI, the Universe, and Everything," Stephen Wolfram Writings, October 27, 2023, https:// writings.stephenwolfram.com. 2. M. Awwad, "Influences of Frege's Predicate Logic on Some Computational Models," Future Human Image Journal 9 (April 14, 2018): 5-19. 3. C. McGinn, "Intelligibility," Colin McGinn, Dec. 14, 2019, www.colinmcginn.net. 4. J. Del Ray, "The Making of Amazon Prime, the Internet's Most Successful and Devastating Membership Program," Vox, May 3, 2019, www.vox.com. 5. T. Schaul, "Boundless Socratic Learning With Language Games," arXiv, Nov. 25, 2024. https://arxiv.org; and The Physics arXiv Blog, "AI Systems Reflect the Ideology of Their Creators, Say Scientists," Discover Magazine, Oct. 31, 2024, www.discovermagazine.com. Tags: Cognitive Technologies Machine Learning Technology Innovation Value Creation Reprint #: 66311 More Like This Add a comment Cancel reply You must sign in to post a comment. First time here? Sign up for a free account: Comment on articles and get access to many more articles. No comments MIT Sloan Management Review LogoMIT Sloan Management Review Logo Copyright (c) Massachusetts Institute of Technology, 1977-2025. All rights reserved. * Home * Organization Subscriptions * About Us * Newsletters * Store * Advertise With Us * Contact Us * Republishing * Help * Author Guidelines Get free, timely updates from MIT SMR with new ideas, research, frameworks, and more. [ ] sign up Please enter a valid email address Thank you for signing up Privacy Policy Follow Us * Facebook * X * Linkedin * Youtube * Instagram Login Create an Account Business Access