Companies are increasingly investing in AI technology, yet many are struggling to achieve significant returns. The “GenAI Divide: State of AI in Business 2025” report by MIT’s NANDA initiative reveals that only 5% of AI pilot programs lead to rapid revenue growth, while most fail to impact profit and loss. The key challenge isn’t the quality of AI models but the “learning gap” within organizations and their integration processes. Though startups are excelling by targeting specific problems and leveraging partnerships, larger enterprises face higher failure rates when building proprietary systems. Successful implementations stem from purchasing AI tools and empowering managers to drive adoption, rather than solely relying on central AI labs. Additionally, employing AI in back-office operations offers greater ROI than marketing uses. As companies navigate workforce disruptions and cybersecurity risks, the future of AI deployment suggests a shift toward more adaptable systems that can learn and evolve within specific parameters.
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