Bank of Japan Deputy Governor Shinichi Uchida said on 5 October 2026 that large-volume bond issuances by AI-related companies are pushing up long-term interest rates, even as AI-driven stock gains ease financial conditions.
Speaking at the opening of the ECONDAT 2026 Fall Meeting, Uchida described competing effects that make AI’s influence on monetary policy difficult to assess. His remarks, titled AI, Big Data, and Monetary Policy
, were opening comments at a conference, not a policy decision.
Bond issuance offsets easier financial conditions
Uchida said AI has boosted stock prices, making financial conditions easier, while large-volume bond issuances by AI-related companies have been putting upward pressure on long-term interest rates, thereby making financial conditions tighter.
The remarks, published in English on the Bank of Japan’s website, named no companies and gave no figures for bond issuance or the size of the effects.
Despite the upward pressure on long-term rates, Uchida’s tentative assessment was that AI had made financial conditions easier overall.
Tentatively, it appears that the demand side has come first and that it has been making financial conditions more accommodative on balance, while there is a risk of correction, if profits do not follow.
Uchida also described a risk of correction, if profits do not follow.
He did not say profits would fail to follow, or provide a probability or date for a correction.
Four channels for monetary policy
Uchida set out four ways AI affects monetary policymaking: demand, supply, financial conditions and labour markets. These have implications for core policy parameters, including the output gap, financial conditions and star variables.
He called AI a big positive demand shock
and, in his four-factor account, a big positive demand shock, which has put upward pressure on the economy and prices.
On the supply side, he said AI could have an effect perhaps positively by raising productivity and enhancing capital stock accumulations
, which might in turn affect r-star.
His wording distinguished the demand effects already seen from possible supply-side gains. He said AI has put upward pressure
on the economy and prices, while describing its supply-side influence with could
, perhaps
and might.
Alongside its opposing effects on financial conditions, Uchida said AI may change the labor markets structurally.
Each factor affects monetary policy in different directions and in different time horizons
, he said.
The effects on r-star and u-star remain hard to gauge
at this juncture. Uchida said AI has become a key topic of discussion
at the Bank’s Monetary Policy Meetings.
Better data, but unanswered questions
The conference would examine both the use of AI and big data in central-bank analysis and research, and the economic consequences of AI adoption for productivity and labour markets.
Uchida said AI and big data appear to be removing constraints on computational power and data availability. He cited high-frequency human mobility data used during the pandemic and, more recently, vessel-tracking data used to monitor the Middle East conflict’s impact on crude oil imports and supply chains.
He also said conventional statistics might struggle to keep pace with AI adoption, while alternative data could help.
Uchida said his aim was to make balanced decisions, neither underestimating nor overestimating the impacts of AI.
His tentative view was that the demand side has come first and that it has been making financial conditions more accommodative on balance, while there is a risk of correction, if profits do not follow.
But the scale and timing of AI’s effects remain unsettled.
But, to what extent and degree? In what time horizons? We don’t have a clear answer yet.
On those questions, Uchida said: We don’t have a clear answer yet.