In 2026, three hurdles AI must overcome before being widely implemented
# 2026: Three hurdles to overcome for AI implementation ## Key event: The AI industry enters a “capability—organization” gap phase In 2026, the AI industry faces the most real challenge: the speed of model iteration far exceeds the evolution rate of corporate organizations. Models like DeepSeek V4 Pro and Alibaba Qwen3.8-Max improve their capabilities on a weekly basis, while enterprises still lag behind in organizational adaptation, data governance, and process reengineering. This “capability—organization” gap becomes the core contradiction for AI implementation in 2026. ## Three progressive hurdles ### First hurdle: Capability issues – Can organizations handle AI? Enterprises do not lack computing power or model APIs; what they lack is the structure to “feed” AI into their businesses. John List points out that there are three common gaps in enterprises: - **Business operations are not online**: Operations are recorded in meetings, reports, and front-line experiences, with systems only recording results rather than processes; - **There are no standards for judgment**: Decision-making logic is locked in the minds of senior employees, and it loses its effectiveness when people change; -…