[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"scribble-most-of-the-ai-projects-never-leave-pilot-mode-0ff283a8":3},{"id":4,"title":5,"user_id":6,"is_anonymous":7,"tags":8,"created_at":16,"updated_at":16,"storage_path":17,"is_public":18,"linked_scribbles":19,"previous_scribble":20,"next_scribble":20,"is_draft":7,"related_scribbles":21,"slug":22,"author_name":23,"author_username":24,"body":25,"linked_articles":26,"related_articles":27,"reverse_relation_map":68},"0ff283a8-c0f6-43c4-8390-50a86abcdd30","Most of the AI Projects Never Leave Pilot Mode","ff91778b-54c7-4d14-8f0c-9652e6b5021a",false,[9,10,11,12,13,14,15],"artificial intelligence","ai","ai scalability","ai production","enterprise ai","ai infrastructure","ai engineering","2025-12-31T07:45:32.674445+00:00","ff91778b-54c7-4d14-8f0c-9652e6b5021a/47a4a869-d60c-4b5e-b0c9-7a9f74db0300.md",true,[],null,[],"most-of-the-ai-projects-never-leave-pilot-mode-0ff283a8","Itih","itih","I keep reading that 67 percent of companies are stuck in AI pilot mode. They can't transition to production.\n\nThat's wild. Two-thirds of AI projects never leave the pilot phase.\n\nBut when I think about why, it makes sense.\n\nAI pilots are fun. You get some data. You train a model. It does interesting things. Everyone is excited.\n\nBut then you realize that scaling AI is different from piloting AI.\n\nA pilot might use a small dataset. Production needs to handle the data you actually generate.\n\nA pilot might use GPU that costs $1,000 a month. Production needs to be cost-effective for real usage.\n\nA pilot might be manually monitored by data scientists. Production needs automated monitoring. It needs alerting when the model drifts. It needs retraining pipelines.\n\nA pilot might be evaluated on accuracy. Production needs to account for fairness. Explainability. Regulatory compliance.\n\nA pilot can be built by a brilliant data scientist. Production needs to be built so a mid-level engineer can maintain it.\n\nThese are completely different problems.\n\nSo companies train a model in a pilot. It works. Then they realize that making it production-ready is 10x more work than the pilot.\n\nAnd at that point, the organization starts asking: \"Is this worth it?\"\n\nFor some projects, the answer is yes. For most, the answer is... we're not sure.\n\nSo they get stuck. In pilot hell.\n\nThey've spent money. They've proven the concept. But they can't justify the engineering effort to scale it.\n\nI think the next wave of AI companies that will win are the ones that make scaling easier. Not the ones that train better models.\n\nTools like MLOps platforms. Data validation tools. Model monitoring. Retraining pipelines.\n\nThese won't make headlines. But they'll be worth billions.\n\nBecause companies don't need better models. They need to get their existing models into production.",[],[28,32,36,40,44,48,52,56,60,64],{"id":29,"title":30,"slug":31},"3ef1be12-915f-417c-b4c9-c1aedd9048be","A Comprehensive Analysis of Big Tech Depreciation: Amazon.com, Inc","a-comprehensive-analysis-of-big-tech-depreciation-amazon-com-inc-3ef1be12",{"id":33,"title":34,"slug":35},"a0196843-b10b-4df9-8f47-fb72e0652901","A Comprehensive Analysis of Big Tech Depreciation: Alphabet Inc","a-comprehensive-analysis-of-big-tech-depreciation-alphabet-inc-a0196843",{"id":37,"title":38,"slug":39},"dc7937db-b59e-43bc-b8d4-9060d1b21360","A Comprehensive Analysis of Big Tech Depreciation: Meta Platforms, Inc","a-comprehensive-analysis-of-big-tech-depreciation-meta-platforms-inc-dc7937db",{"id":41,"title":42,"slug":43},"7e29ba1a-e289-4b1b-ab03-293b8932f167","A Comprehensive Analysis of Big Tech Depreciation: Microsoft Corporation","a-comprehensive-analysis-of-big-tech-depreciation-microsoft-corporation-7e29ba1a",{"id":45,"title":46,"slug":47},"dc4595c1-4f2f-4f00-8c74-8256efd1e935","The Empirical Evidence","the-empirical-evidence-dc4595c1",{"id":49,"title":50,"slug":51},"d04575d8-af9d-45d2-a284-3e96aeb52ad3","The Cannibalization of the Silicon Kings","the-cannibalization-of-the-silicon-kings-d04575d8",{"id":53,"title":54,"slug":55},"9571dc73-e002-4a06-8c8f-ae4f0c4a4acd","The 1.2 Gigawatt Gamble","the-1-2-gigawatt-gamble-9571dc73",{"id":57,"title":58,"slug":59},"7ed59681-19e9-47f4-8060-9e582da41b50","Companies Deployed AI Without Checking If It Works","companies-deployed-ai-without-checking-if-it-works-7ed59681",{"id":61,"title":62,"slug":63},"360b06c6-998e-4d43-9d6b-8d349428268b","Companies Can't Keep Up with AI Model Upgrades","companies-can-t-keep-up-with-ai-model-upgrades-360b06c6",{"id":65,"title":66,"slug":67},"362c71c9-30f7-4712-a038-96a688a401fc","Developers Prefer Claude for Coding","developers-prefer-claude-for-coding-362c71c9",{}]