{"id":93983,"topic":"ai","source":"Yahoo Finance","title":"AI Can Write Code, But It Will Not Replace The Enterprise Tech Stack - Yahoo Finance","url":"https://finance.yahoo.com/technology/ai/articles/ai-write-code-not-replace-054500782.html","url_hash":"1b695c2422d694e5d85f8c0856d0bd20e39db3da","author":"","summary":"AI Can Write Code, But It Will Not Replace The Enterprise Tech Stack Yahoo Finance","content":"The rise of generative AI and agentic AI, with AI coding tools capabilities, has created a powerful bear case against traditional software, SaaS, and technology services companies. The argument is seemingly straightforward: if AI can generate software quickly and cheaply, enterprises should be able to replace much of their existing technology stack, thereby reducing what they spend on software vendors, systems integrators, outsourcing providers, and managed services firms. \nI believe that this thesis is substantially overstated. AI will change the economics of technology, but wholesale replacement of the enterprise tech stack is likely to take much longer than many investors expect. There are several reasons why I have come to this conclusion. \nReason 1: AI Can Rewrite Code, But It is Not the Same as Replacing a Tech Stack\nThere is no question that AI can generate code quickly and effectively, and increasingly so. We already see examples where AI tools are being used to refactor applications or port code from unsupported environments into newer technology environments. Those cases can work well. The cost of generating the new code can also be quite reasonable. However, that does not mean enterprises will suddenly start rewriting their entire technology estates.\nThe reason for this is that the difficult part is not generating the code. The difficult part is understanding everything the existing application does, every system it touches, every dependency it contains, and every business process that relies on it. Even if code generation became effectively free, testing and integration would not be free.\nFor a large enterprise, the business risk of missing one critical dependency can be substantial. The cost of proving that a rewritten system behaves correctly across thousands of processes and interfaces can also be substantial, which changes the economics of replacement considerably.\nReason 2: Working Software has More Value than its License Cost\nMany companies understandably complain about what they pay their major software and SaaS vendors. In some cases, executives feel they are paying a king's ransom. However, that cost needs to be compared with something else: the risk of replacing a system that already works.\nMost large companies have technology environments that may be expensive, complicated, and inelegant, but they reliably run important parts of the business. Replacing those systems merely to reduce software expense is often not a compelling use of capital.\nEnterprises generally allocate investment dollars toward initiatives with the highest expected return, and that's unlikely to change any time soon. Today, that often means investing in new agentic capabilities that can create new productivity, improve customer experiences, automate workflows, or enable entirely new ways of operating. That being said, in many cases, those agentic systems will sit alongside the existing technology stack rather than immediately replace it.","image_url":"https://s.yimg.com/lo/mysterio/api/96497fb3f4033e52805bcd149a924c86d321738e3dbc69f0b6815e9d2967f008/lightyear_networkapi/resizefill_w1200%3Bquality_80%3Bformat_webp/https%3A%2F%2Fmedia.zenfs.com%2Fen%2Fforbes_contributor_845%2F1c246365da0607fd43fc73c6032cf0e6.jpg","lang":"en","published_at":"2026-10-01T05:45:00+00:00","fetched_at":"2026-10-01T06:15:05+00:00","status":"read","starred":0,"extract_state":"ok","summary_auto":"The rise of generative AI and agentic AI, with AI coding tools capabilities, has created a powerful bear case against traditional software, SaaS, and technology services companies. 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The argument is seemingly straightforward: if AI can generate software quickly and cheaply, enterprises should be able to replace much of their existing technology stack, thereby reducing what they spend on software vendors, systems integrators, outsourcing providers, and managed services firms. \nI believe that this thesis is substantially overstated. AI will change the economics of technology, but wholesale replacement of the enterprise tech stack is likely to take much longer than many investors expect. There are several reasons why I have come to this conclusion. \nReason 1: AI Can Rewrite Code, But It is Not the Same as Replacing a Tech Stack\nThere is no question that AI can generate code quickly and effectively, and increasingly so. We already see examples where AI tools are being used to refactor applications or port code from unsupported environments into newer technology environments. Those cases can work well. The cost of generating the new code can also be quite reasonable. However, that does not mean enterprises will suddenly start rewriting their entire technology estates.\nThe reason for this is that the difficult part is not generating the code. The difficult part is understanding everything the existing application does, every system it touches, every dependency it contains, and every business process that relies on it. Even if code generation became effectively free, testing and integration would not be free.\nFor a large enterprise, the business risk of missing one critical dependency can be substantial. The cost of proving that a rewritten system behaves correctly across thousands of processes and interfaces can also be substantial, which changes the economics of replacement considerably.\nReason 2: Working Software has More Value than its License Cost\nMany companies understandably complain about what they pay their major software and SaaS vendors. In some cases, executives feel they are paying a king's ransom. However, that cost needs to be compared with something else: the risk of replacing a system that already works.\nMost large companies have technology environments that may be expensive, complicated, and inelegant, but they reliably run important parts of the business. Replacing those systems merely to reduce software expense is often not a compelling use of capital.\nEnterprises generally allocate investment dollars toward initiatives with the highest expected return, and that's unlikely to change any time soon. Today, that often means investing in new agentic capabilities that can create new productivity, improve customer experiences, automate workflows, or enable entirely new ways of operating. That being said, in many cases, those agentic systems will sit alongside the existing technology stack rather than immediately replace it.","excerpt":"The rise of generative AI and agentic AI, with AI coding tools capabilities, has created a powerful bear case against traditional software, SaaS, and technology services companies. The argument is seemingly straightforward: if AI can generate software quickly and cheaply, enterprises should be able to replace much of their existing technology stack, thereby reducing what they spend on software vendors, systems integrators, outsourcing providers, and managed services firms.","extraction":{"state":"ok","confidence":0.9,"error":null,"explanation":"High confidence: full text extraction produced 2983 characters.","diagnostics_url":"/api/diagnose?url=https%3A//finance.yahoo.com/technology/ai/articles/ai-write-code-not-replace-054500782.html","quality_profile":{"profile_version":"extraction_quality.v2","bucket":"high","confidence":0.9,"failure_kind":"none","retryable":false,"retry_after_attempts":0,"reason":"High confidence: full text extraction produced 2983 characters.","operator_guidance":{"severity":"ok","recommended_action":"trust_full_text","next_step":"Use the extracted full text as the primary article source.","operator_label":"Ready","can_retry":false,"can_use_summary":false,"diagnostics_required":false},"content_depth":{"contract_version":"content_depth.v1","category":"full_text","label":"Full text","has_full_text":true,"has_summary":true,"content_length":2983,"summary_length":477,"usable_text_length":2983,"source_field":"content"},"legacy_collapsed":false,"signals":{"extract_state":"ok","extract_error":null,"extract_retries":0,"content_length":2983,"summary_length":477}}},"display_formats":["compact","card","full","digest_section","json"]},"daily_stack_record":{"title":"AI Can Write Code, But It Will Not Replace The Enterprise Tech Stack - Yahoo Finance","url":"https://finance.yahoo.com/technology/ai/articles/ai-write-code-not-replace-054500782.html","summary":"The rise of generative AI and agentic AI, with AI coding tools capabilities, has created a powerful bear case against traditional software, SaaS, and technology services companies. 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AI will change the economics of technology, but wholesale replacement of the enterprise tech stack is likely to take much longer than many investors expect. There are several reasons why I have come to this conclusion. \nReason 1: AI Can Rewrite Code, But It is Not the Same as Replacing a Tech Stack\nThere is no question that AI can generate code quickly and effectively, and increasingly so. We already see examples where AI tools are being used to refactor applications or port code from unsupported environments into newer technology environments. Those cases can work well. The cost of generating the new code can also be quite reasonable. However, that does not mean enterprises will suddenly start rewriting their entire technology estates.\nThe reason for this is that the difficult part is not generating the code. 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AI will change the economics of technology, but wholesale replacement of the enterprise tech stack is likely to take much longer than many investors expect. There are several reasons why I have come to this conclusion. \nReason 1: AI Can Rewrite Code, But It is Not the Same as Replacing a Tech Stack\nThere is no question that AI can generate code quickly and effectively, and increasingly so. We already see examples where AI tools are being used to refactor applications or port code from unsupported environments into newer technology environments. Those cases can work well. The cost of generating the new code can also be quite reasonable. However, that does not mean enterprises will suddenly start rewriting their entire technology estates.\nThe reason for this is that the difficult part is not generating the code. The difficult part is understanding everything the existing application does, every system it touches, every dependency it contains, and every business process that relies on it. Even if code generation became effectively free, testing and integration would not be free.\nFor a large enterprise, the business risk of missing one critical dependency can be substantial. The cost of proving that a rewritten system behaves correctly across thousands of processes and interfaces can also be substantial, which changes the economics of replacement considerably.\nReason 2: Working Software has More Value than its License Cost\nMany companies understandably complain about what they pay their major software and SaaS vendors. In some cases, executives feel they are paying a king's ransom. However, that cost needs to be compared with something else: the risk of replacing a system that already works.\nMost large companies have technology environments that may be expensive, complicated, and inelegant, but they reliably run important parts of the business. Replacing those systems merely to reduce software expense is often not a compelling use of capital.\nEnterprises generally allocate investment dollars toward initiatives with the highest expected return, and that's unlikely to change any time soon. Today, that often means investing in new agentic capabilities that can create new productivity, improve customer experiences, automate workflows, or enable entirely new ways of operating. 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