At the 2026 Inclusion·Bund Conference held in Shanghai on September 9, discussions centered on new paradigms for AI-driven economic growth and social value reconstruction. Miao Yanliang, Chief Economist at CICC, highlighted that the demand shortfall triggered by AI's impact is fundamentally a structural and distributional challenge.

He advocated for tax system adjustments to correct the current "differential treatment" between labor and capital. Specifically, he suggested considering the moderate implementation of an "automation tax," "robot tax," or "AI tax" to address these imbalances.

On the topic of workforce displacement, Miao emphasized the need for targeted education and retraining programs to mitigate structural unemployment. He also stressed the importance of carefully calibrating the timing and exit mechanisms for both training initiatives and relief measures, cautioning against creating long-term welfare dependency that could lead to permanent or semi-permanent joblessness.

Furthermore, because AI-era job creation is relatively slow, many job seekers are being pushed into lower-skilled positions. To counter this trend, Miao proposed using fiscal interest subsidies in coordination with structural monetary policy tools, such as targeted relending, to steer private capital toward emerging service sectors that are difficult for AI to replace or that require human-machine collaboration.