January 29, 2026 | Economic Update

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We continue to expect the above-trend GDP growth the US economy showed in the second half of 2025 to persist in the coming months, as a recovery in business sentiment from depressed levels and tax incentives embedded in President Trump’s One Big Beautiful Bill Act (OBBBA) enacted last July will lead to a rebound in job gains and in non-tech business capital spending. Supporting this lift will be consumers, whose resilient spending continued apace through last year’s near stall in job growth. Retail sales reports indicate sustained, solid increases while personal spending, which accounts for about 70% of GDP, remains strong, rising 0.5% in November, according to the Bureau of Economic Analysis (BEA). With these gains underpinning GDP growth, and strong fourth quarter profits, business sentiment is on the rise.

Following a recovery from recession-like levels last quarter, US regional manufacturing surveys point to a further gain in business capital spending intentions. Recent flash purchasing managers’ reports (PMIs), which reversed declines in the previous two months, were important markers for gauging the likelihood of a rebound in non-tech manufacturing employment in the New Year. A recent Commerce Department report also showed durable goods orders grew 5.3% in November, the largest increase in six months, while core capital goods shipments, a widely followed indicator of underlying business investment, rose 0.4%.

Last year’s sentiment collapse appears to have been triggered by disruptive US policy decisions, so it’s reasonable to question whether the latest flurry of surprising US policy developments could short-circuit the sentiment lift. We believe the linkage between US domestic policy developments and sentiment is likely to prove different this year for a couple of reasons. First, is the changing motivation for policy actions at this point in the election cycle. The objective in 2025 was to disrupt the economy with shocking immigration and DOGE initiatives geared toward medium-term objectives despite short-term growth concerns. By contrast the upcoming mid-term elections have focused attention on policies to boost near-term growth. The latest initiatives to pressure interest rates lower and support housing are a reaction to rising affordability concerns. The second difference from last year’s policy steps is the constraints the administration is facing in the implementation of its initiatives. An example of this is the cap on credit card interest rates which would require congressional approval is already seeing pushbacks. Lacking votes to ease fiscal policy and facing a Fed that is signaling a pause, the recent proposals look more performative than substantive.

On balance, we believe US macroeconomic policies, including further Fed accommodation, stimulative spending and tax initiatives, and deregulation, combined with an improvement in consumer sentiment already underway, are likely to deliver a notable boost to growth this year. However, beyond these, the latest flurry of policy announcements, if enacted, are unlikely to alter the trajectory of the economy materially. While the proposal to cap credit card rates at 10% could save borrowers as much as $100 billion annually, this benefit could be outweighed by a pullback in credit availability. And regarding Trump’s housing proposals, we fail to see the President’s directive for the GSEs to purchase $200 billion of mortgage-backed securities as having a meaningful impact on housing, and the ban on institutional investors from buying single-family homes could serve to raise rental costs even if it reduces the costs for first-time homebuyers. Most important, Trump’s housing proposals-to-date fail to meaningfully address the severe shortfall in the supply of affordable housing.

Real GDP grew at a rapid 4.4% annual rate in the third quarter, the fastest quarterly pace in two years. Core GDP, which includes consumer spending, business fixed investment, and home building, while excluding the more volatile categories like government purchases, inventories and trade, grew at a respectable 2.9% rate in Q3. More impressively, it looks like economic growth in the fourth quarter could come in even faster. Currently, the Atlanta Fed’s GDP Now model suggests the economy grew at a 5.4% annual rate in Q4. Yes, much of that growth is related to a very favorable international trade report for October which might reverse in November. But even if we exclude that trade reading, by looking instead at Core GDP for Q4, the economy appears to have grown at about a 2.75% annual rate, well above trend which the Fed pegs at 1.8%.

Clearly there are risks to the forecast that the combination of resilient consumer spending and the willingness of businesses to invest for the future will produce a hiring rebound. While exogenous shocks are to be expected, the principal risk to the recoupling of hiring and non-tech business spending is the possibility that the weak job growth we have seen is structural, as the implementation of AI technologies has shifted production functions. In this case, employment will be insensitive to normalizing business sentiment.

Employment

While not as strong as the overall economy, reports on the job market show no signs of stress. The employment rate finished 2025 at 4.4%, versus 4,1% a year ago and down from 4.6% the prior month, but private sector payroll growth continues strong, despite a large drop in net immigration into the US. True, growth in private sector payrolls has been narrow and mostly confined to health care and social assistance. More importantly, the latest household survey, which contacts people directly rather than surveying employers, shows an increase of 2.4 million jobs in the past twelve months. And initial jobless claims have held steady near 200,000 per month with continuing claims little changed below 2.0 million for months.

Inflation and the Fed

The latest reading of the Federal Reserve’s preferred inflation gauge, the Personal Consumption Expenditures price index (PCE) came in largely as expected in November, offering no impetus for officials to alter monetary policy any time soon. The core PCE, which excludes food and energy, rose 0.2% in November, from the previous month and 2.8% from a year earlier. The figures suggest inflation remains sticky, well above the Fed’s 2% target, but stable, holding near recent levels. However, beneath the surface we see signs of slowly cooling inflation. Wage growth has slowed sharply, with the Atlanta Fed’s wage tracker showing annual gains near pre-pandemic levels. Slower wage growth makes it more difficult for services inflation to remain stubbornly high, particularly as housing costs are expected to cool further this year.

FOMC members are confronted with conflicting inflation signals. Inflation does not appear to be worsening despite some economists’ fears that tariffs will lead to a spike in prices. On the other hand, prices have not softened enough to clearly justify a rate cut any time soon. January and February inflation data will likely test how much price stickiness remains in the system and will inform policy decisions to be taken this Spring.

Risks of AI Coming into Focus

Over roughly the past two years, enthusiasm around artificial intelligence has been an important driver of corporate investment plans and stock market performance. The case for AI’s benefits (e.g. productivity, innovation, and new business and consumer capabilities) has been widely broadcast. More recently, however, a broader discussion has emerged around technology’s potential downsides and the ways in which today’s financial and real-economy could amplify those risks. In assessing these risks, it is useful, we believe, to separate them into three categories: (1) labor-market and distribution effects; (2) investment-cycle and financial-stability considerations; and (3) infrastructure and real-resource constraints. Each of these categories has different timelines, and each would be expected to operate through different channels.

Labor Market Displacement

The labor market is typically where technology-driven change becomes most visible to households. It is also where the transition costs can be most acute. Public estimates of “exposure” to AI vary, but they are consistently large. The IMF has estimated that around 40% of global employment is exposed to AI, with a higher exposure of 60% in advanced economies, given their occupational mix. That exposure, importantly, is not synonymous with outright job loss but it reflects that individual tasks within many jobs may be augmented or automated.

Still, the near-term risk that has caught our attention is not simply displacement of workers in the aggregate; it is the hollowing out of entry-level work, the early-career roles through which workers accumulate firm-specific knowledge and generate so-called human capital. A recent Dallas Fed research summary, drawing on work by Stanford researchers, reports that workers aged 22-25 in the most AI exposed roles have experienced a 13% relative decline in employment since 2022, while employment for less-exposed or more-experienced workers has been steadier.

This pattern, if it persists, carries two compounding risks: First, longer-run wage scarring. Economic research has long found that weak early-career attachment can have persistent effects on earnings trajectories. If entry level slots contract in AI exposed fields, the burden is borne disproportionately by young workers and career switchers. Second, a skills pipeline problem. Firms may achieve short-run efficiency by automating junior tasks, but they may also reduce the on-the-job training that produces the next cohort of supervisors, specialists, and managers.

Regarding job loss magnitudes, forecasts differ greatly, but some are sizable. A widely cited Goldman Sachs analysis estimated that generative AI could expose the equivalent of 300 million full-time jobs globally to some degree of automation, while also emphasizing offsetting forces through productivity and job creation. Other projections are more directly framed around net job losses. For example, we have seen estimates 10.4 million US jobs could be eliminated between 2025 and 2030 (roughly 6% of all jobs) with substantially more roles reshaped.

While these projections are subject to revision, they do help illustrate the scale of adjustment that could occur if the adoption of AI accelerates and if firms pursue substitution rather than augmentation of roles.

Concentration of Risk

A second set of risks arises from the way AI production is organized today; a relatively small set of companies supply critical inputs (e.g. advanced chips, cloud capacity, and frontier models), and a relatively small set of buyers account for a meaningful share of demand. The resulting concentration may promote efficiencies, but it can also create fragility. For example, in a recent quarter NVIDIA reported that one customer represented 23% of its total revenues, and a second customer accounted for an additional 16%, together 39% of that firm’s revenues. Even if these customers are only intermediaries and the ultimate end-demand is diversified, the figures are a reminder that the AI capex cycle is unusually dependent on a small number of very large purchasers. In such an environment, a relatively modest shift in the investment plans of just a handful of hyper-scalers, due to profitability issues, energy constraints, regulation or simply a reassessment of the pace of monetization, could have outsized effects along the supply chain.

Enthusiastic markets often price risk imperfectly during expansions, particularly when recent growth rates are extrapolated.

Circular Financing Risks

Circular financing refers to a structure where a supplier of key inputs (e.g. chips, cloud capacity) also helps finance a buyer such as a model developer or AI startup and the buyer then uses that financing, directly or indirectly, to purchase the supplier’s inputs. So circular financing involves arrangements where companies supplying a product or service are also significant investors, creating a loop where invested capital flows back through outright purchases or long-term contracts. Analysts have debated whether these structures are benign, simply a modern form of partnership, or whether they obscure underlying demand.

One view argues that the rise in circular financing, an increasingly visible feature of AI deal-making, signals a bubble in the making. Others note that circular deals can raise concerns because they can facilitate channel stuffing, blurring arm’s length discipline. The risk here is not that such arrangements are inherently improper. Rather, the macro-financial concern that price signals become less informative.

Historically, periods of rapid technological investment (e.g. railroads, electrification, telecom, the dot-com era) have often delivered transformative long-run gains while still producing intermediate-term booms and busts tied to overbuilding, leverage, optimistic projections, and novel forms of financing which eventually led to unintended adverse consequences.

Scale of Investment

Public data suggest that AI has become a central driver of venture capital (VC) and corporate investment. One source, PitchBook, noted that in 2024, AI and machine learning accounted for about 35.7% of global venture capital deal value, with global investment in AI rising to $131.5 billion. Separately, a report from EY indicated that global VC funding in AI reached $49.2 billion in the first half of 2025, surpassing 2024 totals. Large capital flows are not, by themselves, evidence of excess. But they do raise the probability of misallocation, especially when funding is abundant, when competitive pressure encourages parallel buildouts, and when near-term profitability is uncertain.

If expected returns on AI investments lag the cost of capital, the adjustment may come through equity repricing, pullbacks in capex, and the knock-on effects to employment, affected sectors and the broader economy.

Real-resource Constraints

Unlike purely digital innovations, frontier AI is constrained by physical infrastructure (e.g. data centers, grid connections, and energy supply). The International Energy Agency (IEA) projects that global electricity consumption from data centers could more than double by 2030, with AI a major driver of the increase. In the US, IEA’s short-term outlook points to rising energy demand and explicitly cites expanding data-center use tied to AI. Formidable energy constraints, along with permitting backups and materials shortages, matter as they can create bottlenecks that are difficult to clear quickly. Where power is scarce, the incidence shows up in higher prices, delayed projects and geographic concentration, all of which can feed back into corporate earnings and local economic conditions which can quickly become political footballs.

Taken together, these risks do not argue against AI’s enormous, long-run potential. They do, however, suggest that the transition to AI’s broad implementation may be uneven, risky, and that the current investment cycle has characteristics that warrant close monitoring including: Pressures on entry level employment pathways, high concentration in buyers and sellers, financing structures that can blur demand signals, and binding real-resource constraints.

Equity Investment Policy

There has been no change in equity investment policy. Portfolios under our firm’s supervision are fully invested within agreed to account guidelines. High quality, large cap equity investments are well diversified, balanced between growth and value shares. Our investment platform also allows for small cap equities and international developed and emerging market investments. Recall that by blending growth and value investments in a single portfolio, a style of management unique to Front Barnett management, we seek to smooth portfolio returns over a market cycle.

The US economy remains fundamentally sound, well financed, gradually emerging from the rolling recession of the past couple of years, providing a favorable backdrop for equity investment. There are no signs of a broad economic contraction ahead. Our firm’s proprietary Economic Model, updated with data received through October, remains above-trend signaling expansion. While pockets of weakness, particularly in interest rate sensitive and goods producing sectors of the economy, cloud the outlook for the next couple of quarters and employment growth has slowed markedly, the broadening economic expansion we expect to take hold will provide a lift to lagging industries. The overall economy will be driven by a combination of tailwinds including a recovery in employment growth, resilient consumer outlays, deregulation, Fed accommodation and fiscal stimulus.

The S&P500, a cap-weighted stock market index dominated by mega cap tech and telecommunications services stocks, which now account for about 35% of the value of the index, remains fully valued at 22.5X forward earnings. Further S&P500 gains will come over time as reported earnings eclipse consensus estimates. Growth stocks, particularly those highly valued stocks with a direct connection to the AI story, are most vulnerable to sharp pullbacks in the event of a sentiment driven 10%+ general market correction. On the other hand, the forward P/E of the S&P500 equal weight index, with a concentration of only about 17% in tech and telecommunications services, is more reasonably priced at less than 18X forward earnings, only moderately above its average valuation. A broadening economic expansion is, in our view, likely to drive a narrowing in the P/E differential noted above, leaving room for further gains in the cohorts of the S&P500 equal weight index.

Fixed Income Investment Policy

While both short-term and long-term interest rates have drifted a bit lower since late December, the net changes have been small with rates at both ends remaining range-bound. The Fed has signaled a pause in the pace of its accommodation. We see short-term rates are expected to show little change near-term. Meanwhile, the benchmark 10-Year US Treasury bond yield, importantly driven by inflation expectations, which have plateaued in recent months, has ranged between 4.0% and 4.5% since mid-2025. We see these rates remaining stable near the current level of 4.20% over the next few months.

The target duration for the high quality corporate bond portfolios we manage remains a conservative 2.75 years. The proceeds of maturing bonds are currently being reinvested to fill out client’s ladders.

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Indexes are unmanaged, do not include fees or expenses and are not available for direct investment. Definitions: Personal Consumption Expenditures Index (PCE): A measure of the prices that people living in the United States, or those buying on their behalf, pay for goods and services. The PCE price index is known for capturing inflation (or deflation) across a wide range of consumer expenses and reflecting changes in consumer behavior. Conference Board’s Confidence Index: The Consumer Confidence Survey® reflects prevailing business conditions and likely developments for the months ahead. ISM Manufacturing Index: The ISM manufacturing index or purchasing managers' index is considered a key indicator of the state of the US economy. It indicates the level of demand for products by measuring the amount of ordering activity at the nation's factories. ISM Non-Manufacturing Index: The Institute of Supply Management (ISM) Non-Manufacturing Index is an economic index based on surveys of more than 400 non-manufacturing (or services) firms' purchasing and supply executives. S&P 500 Index: The S&P 500 Index, or Standard & Poor's 500 Index, is a market-capitalization-weighted index of 500 leading publicly traded companies in the US. S&P 500 Growth Index: The S&P 500 Growth Index is a stock index administered by Standard & Poor's-Dow Jones Indices. As its name suggests, the purpose of the index is to serve as a proxy for growth companies included in the S&P 500. S&P 500 Value Index: The S&P 500 Pure Value Index refers to a score-weighted index developed by Standard and Poor's (S&P). The index uses what it calls a "style-attractiveness-weighting scheme" and only consists of stocks within the S&P 500 Index that exhibit strong value characteristics.