Thimaya Subaiya’s Post

MIT says 95% of generative AI pilots are failing. That’s a wake-up call, not to slow down, but to focus on real-world impact. At Cisco, we’re weaving AI into our core platforms so it drives business value, scales securely, and addresses real problems. What excites me is seeing how we’re moving from experiments to solutions that work in the real world. Turning generative AI into something reliable means breaking out of silos and focusing on value at scale. What do you think needs to change for AI success?

Generative AI is gaining traction, but adoption in enterprises is proving challenging. MIT’s recent report sheds light on what’s working—and what isn’t. KEY INSIGHTS ● Most AI pilots are struggling: 95% of generative AI projects fail to deliver significant revenue impact, with only a small number achieving rapid results. ● Focused approach and partnerships matter: Startups and some larger firms succeed by addressing one clear problem and collaborating strategically, rather than deploying AI broadly without a plan. ● AI can drive real value: When implemented thoughtfully, AI improves back-office efficiency, reduces costs, and streamlines operations. ● Integration is critical: Success often comes from using specialized AI tools, empowering line managers, and ensuring systems adapt to real workflows. 💬 How is your organization approaching AI adoption? What lessons have you learned about turning AI pilots into meaningful business outcomes? #AI #GenerativeAI #ArtificialIntelligence https://lnkd.in/dCYp7s_v

A striking insight from MIT’s latest research: while generative AI is making headlines, 95% of pilots aimed at accelerating revenue fail to deliver. This is even higher than the 2024 estimate of a 90% failure rate for AI pilots reaching operational deployment. But there’s a silver lining. The study suggests back-office efficiency applications are showing more promise. These use cases are not only more viable but are also significantly reducing demand for traditional BPO services—a shift that could reshape entire industries. To succeed where others fail enterprises must focus on readiness of their business operations to embrace AI augmentation and on how to best customize these powerful tools for their specific purposes not just pilot generic consumer AI products. #AI #GenAI #DigitalTransformation #MITResearch #OperationalEfficiency #BPO #Leadership #InnovationStrategy https://lnkd.in/eGmWAvGs

A new report published by MIT’s NANDA initiative, reveals that while generative AI holds promise for enterprises, most initiatives to drive rapid revenue growth are falling flat. Despite the rush to integrate powerful new models, about 5% of AI pilot programs achieve rapid revenue acceleration; the vast majority stall, delivering little to no measurable impact on P&L. How companies adopt AI is crucial. Purchasing AI tools from specialized vendors and building partnerships succeed about 67% of the time, while internal builds succeed only one-third as often. Looking ahead, the most advanced organizations are already experimenting with agentic AI systems that can learn, remember, and act independently within set boundaries—offering a glimpse at how the next phase of enterprise AI might unfold. #ai #business #digital https://lnkd.in/ezwuA2xQ

Over the past months, I’ve dived deep into cutting-edge AI at MIT. One study stood out: 95% of GenAI pilots at companies fail. But here’s the truth I’ve seen play out time and time again over 20+ years in tech: the failure isn’t about the technology - it’s about the “why.” If you don’t know why you’re implementing AI (or building any product), you’re headed straight for that 95% failure zone. Instead, start with a pain point: 👉 In your company 👉 With your customers 👉 In society Don’t implement AI just because it’s hype. Don’t build #AI products just for the sake of telling investors you did. AI is a powerful tool but it’s not always the best answer to a real problem, nor the wisest use of resources. As product leaders, our job is to stay disciplined: problems first, tech second. That mindset is timeless, even in the #GenAI era. https://lnkd.in/eBTKqgVG #ArtificialIntelligence #GenerativeAI #TechTrends #DigitalTransformation #ProductManagement #ProductLeadership #TechStrategy #ChiefProductOfficer #Innovation #BusinessStrategy #AIProductManagement

The MIT report says that 95% of AI pilots fail because companies focus on generic tools that don't adapt to workflows. So, the problem is not the AI itself but how it is being used. Corporations are replacing people to cut costs quickly. Meanwhile, this approach does not consider the deeper social impact or the need for AI to serve a purpose beyond just profit. They are not addressing the learning gap or integrating AI in a way that adds real value. Instead of using AI to enhance human capabilities and solve specific problems tech companies are using it as a blunt instrument for cost cutting for profit. This misalignment with the social purpose leads to failure because the AI is not effectively integrated into the organization's workflow or aligned with broader societal goals.

A new MIT study, titled "The GenAI Divide: State of AI in Business 2025," has found that 95% of corporate generative AI pilot programs are failing to deliver significant financial impact. Despite massive investments in AI, the report, which was first covered by Fortune, indicates that most projects stall in the pilot phase and do not achieve measurable results. The main reasons cited for this high failure rate are not the quality of the AI models themselves, but rather a "learning gap" for both the tools and the organizations implementing them, as well as poor enterprise integration. The study also found that most AI budgets are being misallocated to sales and marketing departments, while the highest return on investment (ROI) is actually found in back-office automation tasks like streamlining operations and cutting costs. Companies rushed to adopt AI with the belief that it would immediately revolutionize their business, but the actual performance has not met these high expectations. The study notes that even the most advanced AI products can only reliably complete about 30% of assigned office tasks. https://lnkd.in/e45WtBW6

The MIT report highlights that generative AI is not a silver bullet—it is rather a strategic asset that requires focus, structure, and alignment. Organizations must move beyond experimentation and ensure AI initiatives are tied to measurable outcomes, operational readiness, and long-term value creation. The technology is powerful, but without purpose, it is just noise. #Gen-AI #InnovationWithPurpose

95% FAILING! How companies adopt #AI is crucial. Purchasing AI tools from specialized vendors and building partnerships succeed about 67% of the time, while internal builds succeed only one-third as often. The GenAI Divide: State of AI in Business 2025, a new report published by MIT’s NANDA initiative, reveals that while generative AI holds promise for enterprises, most initiatives to drive rapid revenue growth are falling flat. Aokah Massachusetts Institute of Technology https://lnkd.in/e6GiiW6f

MIT report says 95% of companies piloting Gen AI are not pulling in more cooperate profits I don't think this study is definitive, but the report seems to suggest that: 1. Gen AI needs to be cheaper; or 2. Companies need to fire more workers For AI to increase profits. (Or it is this still too early to tell?) What do you think? #business #GenAI #AI #Wallstreet #Greed #jobs #Tech #endoftheworld https://lnkd.in/eik_b8iX