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Hello and welcome to Notes in the Week Ahead, a JP Morgan asset management podcast that provides insights on the markets and the economy to help you stay informed in the week ahead. Hello, this is David Kelly. I'm chief strategist here at JPMorgan Asset Management. Today's April 20, 2026 On Tuesday, the Senate Banking Committee will hold hearings to consider the nomination of Kevin Warsh to be the next Fed Chair. His confirmation is likely going to be delayed until the Justice Department's investigation into Jerome Powell is fully resolved. But despite this, Mr. Warsh's answers to the committee's questions could shed important light on the future direction of monetary policy. One particularly important question will be how Mr. Warsh views short term interest rates in the balance sheet. In an interview on Fox Business last summer, he argued that the Fed should reduce the size of its balance sheet and since doing so would imply monetary tightening, this would give the Fed the leeway to cut short term rates. As we outlined in a recent article, however, shrinking the balance sheet is complicated on both sides of the ledger and would likely raise long term interest rates in general and mortgage rates in particular, hardly a result that the Administration would want given its aggressive efforts to strong arm the Fed into lowering rates. However, assuming that the Fed doesn't engage in dramatic quantitative tightening to justify lowering short term rates, Mr. Walsh has suggested another possible rationale. In a Wall Street Journal op ed last November, he argued that AI will be a significant disinflationary force, will really be disinflationary, and if it is, would that justify more aggressive Fed easing in the short run? The tsunami of spending dedicated to AI development is likely inflationary rather than deflationary, as the extra demand is hitting the economy in advance of the productivity payoff. One aspect of this demand is spending on electricity. After more than a decade of no growth, US electricity production rose by 2.5% in 2024, 2.4% in 2025, and was up by 3% year over year in March of this year. Much of this increase is due to data center consumption, and an increasing share of this consumption is devoted to building and employing AI models or, in the jargon of the industry, training and inference. This likely Contributed to a 4.6% year over year rise in consumer electricity prices in March. However, since electricity has just a 2.5% weight in the CPI basket, rising electricity costs accounted for just 1/10 of 1% of March's 3.3% year over year increase in headline CPI. There are, of course, other potential areas where demand from AI Development could feed through to higher prices. Memory chip prices have soared due to the demands of the AI buildout and this is adding to costs for manufacturers of other consumer goods such as laptops, smartphones and even autos. However, only some of this extra cost is likely being passed on to consumers and still isn't a major source of economy wide inflation. The build out of AI data centers is also boosting the demand for construction workers who saw their wages rise by 4.3% year over year in March compared to 3.5% for all private sector workers. However, this increase is more likely due to labour supply issues. Over the past year, the total number of US construction workers has risen by just 0.7%, reflecting in part a huge reversal of immigration trends in a profession that has traditionally employed many immigrants. More broadly, the US has seen a pickup in inflation over the past year from 2.4% year over year in March of 2025 to 3.3% in March of this year, and we project 3.6% in April. However, with the unemployment rate actually up slightly from a year ago, this seems to be the result of supply side issues such as the impact of the Iran war, higher tariffs and fewer immigrant workers, rather than any AI driven surge in demand. Finally, it's unlikely that most corporations have realized significant cost savings from the deployment of the newest AI models yet, and even less likely that they would have passed these cost savings on to consumers. There is a small but growing number of layoff announcements explicitly attributed to AI, and there are some signs of diminished hiring of entry level workers in the most AI exposed industries. A fear that AI will take your job could also be contributing to an even more passivity among workers, with economy wide year over year wage growth falling to an almost a five year low in March. Despite this labor market scare effect, however, it does appear that AI is on balance adding slightly to inflation in the short run, although it will be far from the most important inflation driver if this continues to be the case over say the next two years, then this alone would negate the idea that a disinflationary impulse from AI supports the need for higher short term interest rates. That being said, in the long run, AI is likely to be a significantly disinflationary force. This argument starts with the potential for AI to boost productivity. However, an equally important issue is how the AI revolution could impact the way these productivity gains are divvied up among businesses, workers and consumers. Figuring out the size of the potential productivity gains is extremely difficult. However, a few points are perhaps obvious. Many of which we discuss in our AI Hub at www.jpmorganaihub. first, the productivity gains will vary dramatically by sector and should reflect worker displacement. The Census Bureau's Business Trends and Outlook survey shows that in March of this year, AI applications were being used in over 30% of businesses in the technology, information, financial, and education sectors, but in fewer than 15% of the firms in construction, retail, leisure, and hospitality and transportation sectors. Second, as in any technological revolution, adoption will lag behind potential and efficient usage will lag behind adoption. This is partially because of organizational inertia and partly due to cost. One example of the inertia effect was a sudden ubiquitous adoption of video calls and video conferencing at the start of the pandemic. The capability had been there for years it just required some event to force mass adoption. In the case of AI, expense will also become an issue. While retail consumers are able to access AI tools very cheaply today, they are effectively being subsidized by the providers. At the enterprise level. There are presumably many tasks that AI could perform, but not as yet in a cost effective manner. Third, both the capabilities and usage of AI are increasing at an extraordinary pace. While measuring AI capabilities requires a degree of qualitative judgment, anecdotal evidence and the very rapid upgrading of models suggest a frenetic pace of quality improvement. Meanwhile, more concretely, adoption is rising very swiftly. According to Gallup, in the first quarter of 2026, 50% of employees reported using AI at least some of the time in the role, up from 21% in the second quarter 2023. Over the same very short period, the number of employees saying that they used AI daily or multiple times a week or rose from 11% to 28%. Fourth, it needs to be recognized that measuring the impact of AI will be a continuing problem. For example, in medicine, more accurate diagnostic tools and AI assistance in the development of better therapies may never be officially counted as an improvement in the quality of the output of the medical sector and implicitly a decline in the cost of average care for consumers. Better answers to questions than could be provided by traditional Internet browsers may amount to quality improvement that is also unrecognized in inflation, productivity or output. Conversely, national income and product accounts will also be silent on the negative impacts of AI, such as the increased isolation of individuals or political manipulation. In addition, AI has an extraordinary potential to advance the pace of technological progress in areas such as robotics, biotech, and energy, with these cross pollination impacts also largely being invisible in the economic statistics all we can say with confidence at this point is that AI will have a meaningful and accelerating impact on productivity that will likely always be understated in economic statistics. Returning to the question of inflation, however, there is something else to say. The productivity gains from AI will likely be distributed in a way that is disinflationary rather than inflationary. To see this, it's important to consider the forces that have generally reduced US Inflation in recent decades. One of these forces has been a decline in union power. According to the Bureau of Labor statistics, between 1974 and 2025, union membership as a percentage of all American workers fell from 26% to 10%, while the number of major strikes that is involving a thousand or more workers fell from 424 to 30. If anything, competition from AI will likely reduce labour power, further extending this trend and dampening wage growth. A second trend depressing inflation has been rising inequality. The percentage of pre tax income received by the highest earning 20% of households rose from 43.5% in 1974 to 52.2% in 2024. Richer households save and invest a larger share of their income. So this long trend of rising inequality has diverted demand from goods and services to stocks and bonds, reducing consumer inflation and boosting asset prices. If the AI revolution increases inequality, it will also feed this trend. Finally, there's the general impact of the information revolution, providing buyers across the economy with better ways to compare prices across sellers, thereby increasing competition and holding down prices again. AI will augment this trend. In short, not only is AI likely to boost productivity growth, it is likely to do so in a way that reduces inflation. But even if Mr. Warsh is right in asserting the potential for AI to reduce inflation in the long run, does that justify near term Fed easing? There's a strong case to be made that it does not. First, AI will likely only become a net disinflationary force after some years, while Fed easing this year would impact financial conditions immediately. Second, we currently estimate that by May, year over year, PCE inflation could hit 3.9%, almost double the Federal Reserve's 2% target. If a solution emerges to the Iran conflict, allowing oil prices to fall, if the Administration and Congress resist the urge to inject more fiscal stimulus into the economy before the midterm elections, and if the Administration abandons its plan to replace the structured antiipa tariffs with other tariffs of the same magnitude, then inflation could fall back to 2% or below in early 2027. However, there are far too many ifs in that statement. To use it as a justification for immediate monetary easing. Finally, as Kevin Warsh might well argue himself, the Fed often attempts to achieve goals beyond its remit with very mixed results. Cutting rates today would most obviously help lower mortgage rates and some would argue, help with the affordability issue for young people trying to buy a home. However, the very reason that homes are unaffordable today is not that mortgage rates are too high. It is that the Federal Reserve allowed mortgage rates to stay too low for much too long between the financial crisis and the pandemic and enabling prices to soar. Indeed, super low interest rates for long stretches of time have fueled a boom in asset prices in general. And since assets are even more unequally distributed across society than income, this has actually worsened inequality over time. In short, the Federal Reserve is in no position to remedy the problems of inequality through lower interest rates, nor can it offset the supply side impacts of policies from the other side of Washington. For investors, the best message from Mr. Warsh's testimony would have been explicit recognition of this while still professing confidence in the potential long term economic benefits of the AI revolution. Well, that's it for this week. Please tune in again next week and if you have any questions in the meantime, please reach out to your J.P. morgan representative.
Episode: AI, Inflation and Interest Rates
Host: Dr. David Kelly (Chief Global Strategist, J.P. Morgan Asset Management)
Date: April 20, 2026
Dr. David Kelly discusses the intersection of artificial intelligence (AI), inflation, and interest rates, focusing on the forthcoming Senate hearings for Fed Chair nominee Kevin Warsh. He analyzes Warsh's monetary policy outlooks—particularly regarding AI's impact on inflation—and details the nuanced economic mechanisms at play. The episode critically examines whether AI-driven productivity gains justify near-term changes in the Federal Reserve’s policy, while highlighting trends in inflation, labor, and the broader implications for investors and policymakers.
Quote:
"Shrinking the balance sheet is complicated on both sides of the ledger and would likely raise long-term interest rates in general and mortgage rates in particular, hardly a result that the Administration would want..." (01:24)
Quote:
"Despite this labor market scare effect, however, it does appear that AI is on balance adding slightly to inflation in the short run, although it will be far from the most important inflation driver..." (06:25)
Productivity Promise (07:05):
Adoption Trends (08:21):
Quote:
"All we can say with confidence at this point is that AI will have a meaningful and accelerating impact on productivity that will likely always be understated in economic statistics." (10:10)
Quote:
"If the AI revolution increases inequality, it will also feed this trend." (12:36)
No Immediate Justification for Fed Easing (13:20):
Structural Issues with Rate Cuts (15:04):
Quote:
"Super low interest rates for long stretches of time have fueled a boom in asset prices in general. And since assets are even more unequally distributed across society than income, this has actually worsened inequality over time." (16:07)
On AI’s short-term effects:
"It does appear that AI is on balance adding slightly to inflation in the short run, although it will be far from the most important inflation driver if this continues to be the case over say the next two years, then this alone would negate the idea that a disinflationary impulse from AI supports the need for higher short term interest rates." – Dr. David Kelly (06:25)
On AI’s likely long-term impact:
"AI will have a meaningful and accelerating impact on productivity that will likely always be understated in economic statistics." – Dr. David Kelly (10:10)
On the limits of monetary policy:
"The Federal Reserve is in no position to remedy the problems of inequality through lower interest rates, nor can it offset the supply side impacts of policies from the other side of Washington." – Dr. David Kelly (16:34)
| Timestamp | Topic | |-----------|-----------------------------------------------------------| | 00:10 | Senate hearings for Fed Chair; Warsh's views | | 01:00 | Warsh on balance sheet reduction & policy implications | | 01:54 | AI as a disinflationary force? | | 02:10 | AI-driven electricity demand and inflation | | 03:07 | AI impact on memory chips and construction wages | | 04:13 | Recent and projected inflation (CPI) | | 06:25 | AI’s current role in inflation vs. other inflation drivers| | 07:05 | Long-run AI productivity: mechanism and measurement | | 08:21 | AI adoption trends across sectors | | 09:35 | Challenges in measuring AI’s true impact | | 11:12 | Structural suppressors of inflation (unions, inequality) | | 13:20 | Monetary policy: Why not cut rates now? | | 15:04 | Asset prices, housing, and the side effects of low rates | | 16:34 | Fed’s limited role in addressing inequality |
For more insights, visit J.P. Morgan’s AI Hub or reach out to your representative.