Build vs. Buy AI: Why SMBs Must Account for the Full Cost of Ownership

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Adopting AI tools for business operations carries hidden long-term costs that go far beyond licensing fees, including ongoing maintenance, model deprecation, and connector upkeep. Research from McKinsey, BCG, and Gartner highlights that while AI use is widespread, fewer than 6% of enterprises generate measurable value at scale, and over 40% of agentic AI projects may be canceled by 2027. AI systems differ from traditional software in that they drift over time — accuracy can silently degrade and outputs carry legal weight, as demonstrated when Air Canada was held liable in a 2024 tribunal ruling for a chatbot's incorrect policy advice. A support agent handling 50,000 chats monthly can require over $500,000 per year just to maintain accuracy, while typical enterprise AI rollouts see only a fraction of licensed seats used regularly. For small and mid-sized businesses, the core question is not which tool has the best features, but whether the organization can sustain the full operational burden of ownership over a 24-month horizon.

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ProgrammingDEV Community ·

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