{"slug": "why-we-need-technology-economists", "title": "Why we need technology economists", "summary": "Organizations need technology economists, not just IT finance professionals, to evaluate AI investments because AI breaks the stable relationship between technology spending and business outcomes, according to a Substack article by Howard A. Rubin. The article argues that a $10 million AI investment could generate $100 million in value or nothing at all, and that technology economists study entire economic systems and value chains, focusing on capital allocation efficiency, opportunity cost, and portfolio optimization, which traditional IT finance overlooks.", "body_md": "The advent of AI is precisely why organizations need technology economists, not just IT finance professionals.\n\nIT finance is primarily concerned with budgeting, accounting, cost allocation, depreciation, chargebacks and financial reporting. These disciplines remain important, but they assume a relatively stable relationship between technology spending and business outcomes. [AI breaks that assumption](https://howardarubin.substack.com/p/why-ai-roi-is-so-darn-hard-to-measurehttps:/howardarubin.substack.com/p/why-ai-roi-is-so-darn-hard-to-measurehttps:/howardarubin.substack.com/p/why-ai-roi-is-so-darn-hard-to-measure).\n\nTechnology economics asks a fundamentally different question: How do technology investments create, destroy, shift or delay economic value?\n\nAI introduces a set of economic dynamics that traditional IT finance was never designed to evaluate.\n\nIn traditional IT, spending $10 million typically produced a somewhat predictable capacity increase or operational improvement.\n\nWith AI, a $10 million investment might generate $100 million in value. It might generate no value at all. It could increase costs while appearing successful. It could also create strategic advantages that do not show up in financial statements for years.\n\nA technology economist studies the relationship between technology inputs, organizational capability, productivity outcomes and economic value creation.\n\nIT finance largely records the spending.\n\nAI is not merely another technology platform. It acts as a form of digital labor.\n\nOrganizations now face questions such as:\n\nThese are economic questions, not accounting questions.\n\nA [fascinating paradox](https://www.northerntrust.com/united-states/insights-research/2026/investment-perspective/is-ai-inflationary-or-deflationary) is emerging: AI can reduce costs in some areas while dramatically increasing costs elsewhere.\n\nFor example, fewer coding hours. More GPU costs. Lower service desk costs. Higher cybersecurity costs. Reduced consulting expenses. Increased data management expenses.\n\nTechnology economists study entire economic systems and value chains.\n\nIT finance often sees only line items.\n\nHistorically, organizations measured projects delivered, systems implemented, budgets achieved and uptime percentages.\n\nThe AI era requires measuring:\n\nTechnology economists focus on these outcome measures.\n\nThis is one reason why [AI performance measurement frameworks](https://www.nytimes.com/2026/08/03/business/economy/ai-spending-tokenomics.html), including AI-focused balanced scorecard approaches, are becoming increasingly important.\n\nOne of the largest AI risks is not technological failure.\n\nIt is investing in the wrong AI initiatives.\n\nA bank might spend $50 million building an AI solution that saves $5 million annually while ignoring another opportunity that could have generated $500 million in new revenue.\n\nTechnology economics focuses on capital allocation efficiency, opportunity cost, marginal returns and portfolio optimization.\n\nThese concepts sit outside traditional IT finance.\n\nHistorically, technology supported the business.\n\nIncreasingly, technology *is* the business.\n\nIn many industries, AI determines customer experience, operating efficiency, innovation speed and competitive advantage.\n\nTechnology is becoming a primary production factor alongside labor, capital and natural resources.\n\nOrganizations therefore need experts who understand the economics of technology as a production asset.\n\nMany organizations are deploying AI rapidly without understanding:\n\nA technology economist examines the total lifecycle economics.\n\nThe cheapest AI solution today may become the most expensive solution over the next decade.\n\nThe central challenge of the AI era is no longer *“Can we build it?”*\n\nThe challenge is, “Should we build it, where should we deploy it, what value will it create, what risks will it introduce and what is the optimal economic allocation of technology capital?”\n\nThose are technology economics questions.\n\nIT finance professionals are essential for controlling and reporting technology spending.\n\nTechnology economists are essential for determining whether that spending creates sustainable economic value.\n\nAs AI becomes embedded into every business process, the organizations that outperform will not necessarily be those with the biggest AI budgets. They will be those that best understand the economics of technology itself — how AI, data, infrastructure, labor, risk and innovation combine to [create measurable business value](https://www.cio.com/article/4137420/5-metrics-to-drive-successful-ai-outcomes.html). That is the domain of technology economics.", "url": "https://wpnews.pro/news/why-we-need-technology-economists", "canonical_source": "https://www.cio.com/article/4215355/why-we-need-technology-economists.html", "published_at": "2026-08-31 12:00:00+00:00", "updated_at": "2026-08-31 12:24:35.560321+00:00", "lang": "en", "topics": ["artificial-intelligence", "ai-policy"], "entities": ["Howard A. Rubin"], "alternates": {"html": "https://wpnews.pro/news/why-we-need-technology-economists", "markdown": "https://wpnews.pro/news/why-we-need-technology-economists.md", "text": "https://wpnews.pro/news/why-we-need-technology-economists.txt", "jsonld": "https://wpnews.pro/news/why-we-need-technology-economists.jsonld"}}