D. Brian Blank, Mississippi State University and Brandy Hadley, Appalachian State University

The U.S. economy heads into 2026 in an unusual place: Inflation is down from its peak in mid-2022, growth has held up better than many expected, and yet American households say that things still feel shaky. Uncertainty is the watchword, especially with a major Supreme Court ruling on tariffs on the horizon.

To find out what’s coming next, The Conversation U.S. checked in with finance professors Brian Blank and Brandy Hadley, who study how businesses make decisions amid uncertainty. Their forecasts for 2025 and 2024 held up notably well. Here’s what they’re expecting from 2026 – and what that could mean for households, workers, investors and the Federal Reserve:

What’s next for the Federal Reserve?

The Fed closed out 2025 by slashing its benchmark interest rate by a quarter of a percentage point – the third cut in a year. The move reopened a familiar debate: Is the Fed’s easing cycle coming to an end, or does the cooling labor market signal a long-anticipated recession on the horizon?

While unemployment remains relatively low by historical standards, it has crept up modestly since 2023, and entry-level workers are starting to feel more pressure. What’s more, history reminds us that when unemployment rises, it can do so quickly. So economists are continuing to watch closely for signs of trouble.

So far, the broader labor market offers little evidence of widespread worsening, and the most recent employment report may even be more favorable than the top-line numbers made it appear. Layoffs remain low relative to the size of the workforce – though this isn’t uncommon – and more importantly, wage growth continues to hold up. That’s in spite of the economy adding fewer jobs than most periods outside of recessions.

Gross domestic product has been surprisingly resilient; it’s expected to continue growing faster than the pre-pandemic norm and on par with recent years. That said, the recent shutdown has prevented the government from collecting important economic data that Federal Reserve policymakers use to make their decisions. Does that raise the risk of a policy miscue and potential downturn? Probably. Still, we aren’t concerned yet.

And we aren’t alone, with many economists noting that low unemployment is more important than slow job growth. Other economists continue to signal caution without alarm.

Consumers, the largest driver of economic growth, continue spending – perhaps unsustainably – with strength becoming increasingly uneven. Delinquency rates – the share of borrowers who are behind on required loan payments in housing, autos and elsewhere – have risen from historic lows, while savings balances have declined from unusually high post-pandemic levels. A more pronounced K-shaped pattern in household financial health has emerged, with older higher-income households benefiting from labor markets and already seeming past the worst financial hardship.

Still, other households are stretched, even as gas prices fall. This contributes to a continuing “vibecession,” a term popularized by Kyla Scanlon to describe the disconnect between strong aggregate economic data and weaker lived experiences amid economic growth. As lower-income households feel the pinch of tariffs, wealthier households continue to drive consumer spending.

For the Fed, that’s the puzzle: solid top-line numbers, growing pockets of stress and noisier data – all at once. With this unevenness and weakness in some sectors, the next big question is what could tip the balance toward a slowdown or another year of growth. And increasingly, all eyes are on AI.

Is artificial intelligence a bubble?

The dreaded “B-word” is popping up in AI market coverage more often, and comparisons to everything from the railroad boom to the dot-com era are increasingly common.

Stock prices in some technology firms undoubtedly look expensive as they rise faster than earnings. This may be because markets expect more rate cuts coming from the Fed soon, and it is also why companies are talking more about going public. In some ways, this looks similar to bubbles of the past. At the risk of repeating the four most dangerous words in investing: Is this time different?

Comparisons are always imperfect, so we won’t linger on the differences between this time and two decades ago when the dot-com bubble burst. Let’s instead focus on what we know about bubbles.

Economists often categorize bubbles into two types. Inflection bubbles are driven by genuine technological breakthroughs and ultimately transform the economy, even if they involve excess along the way. Think the internet or transcontinental railroad. Mean-reversion bubbles, by contrast, are fads that inflate and collapse without transforming the underlying industry. Some examples include the subprime mortgage crisis of 2008 and The South Sea Company collapse of 1720.

If AI represents a true technological inflection – and early productivity gains and rapid cost declines suggest it may – then the more important questions center on how this investment is being financed.

Debt is best suited for predictable, cash-generating investments, while equity is more appropriate for highly uncertain innovations. Private credit is riskier still and often signals that traditional financing is unavailable. So we’re watching bond markets and the capital structure of AI investment closely. This is particularly important given the growing reliance on debt financing in some large-scale infrastructure projects, especially at firms like Oracle and CoreWeave, which already seem overextended.

For now, caution, not panic, is warranted. Concentrated bets on single firms with limited revenues remain risky. At the same time, it may be premature to lose sleep over “technology companies” broadly defined or even investments in data centers. Innovation is diffusing across the economy, and these tech firms are all quite different. And, as always, if it helps you sleep better, changing your investments to safer bonds and cash is rarely a risky decision.

A quiet but meaningful shift is also underway beneath the surface. Market gains are beginning to broaden beyond mega-cap technology firms, the largest and most heavily weighted companies in major stock indexes. Financials, consumer discretionary companies and some industrials are benefiting from improving sentiment, cost efficiencies and the prospect of greater policy clarity ahead. Still, policy challenges remain ahead for AI and housing with midterms looming.

Will things ever feel affordable again?

Policymakers, economists and investors have increasingly shifted their focus from “inflation” to “affordability,” with housing remaining one of the largest pressure points for many Americans, particularly first-time buyers.

In some cases, housing costs have doubled as a share of income over the past decade, forcing households to delay purchases, take more risk or even give up on hopes of homeownership entirely. That pressure matters not only for housing itself, but for sentiment and consumption more broadly.

Still, there are early signs of relief: Rents have begun to decline in many markets, especially where new supply is coming online, like in Las Vegas, Atlanta and Austin, Texas. Local conditions such as zoning rules, housing supply, population growth and job markets continue to dominate, but even modest improvements in affordability can meaningfully affect household balance sheets and confidence.

Looking beyond the housing market, inflation has fallen considerably since 2021, but certain types of services, such as insurance, remain sticky. Immigration policy also plays an important role here, and changes to labor supply could influence wage pressures and inflation dynamics going forward.

There are real challenges ahead: high housing costs, uneven consumer health, fiscal pressures amid aging demographics and persistent geopolitical risks.

But there are also meaningful offsets: tentative rent declines, broadening equity market participation, falling AI costs and productivity gains that may help cool inflation without breaking the labor market.

Encouragingly, greater clarity on taxes, tariffs, regulation and monetary policy may arrive in the coming year. When it does, it could help unlock delayed business investment across multiple sectors, an outcome the Federal Reserve itself appears to be anticipating.

If there is one lesson worth emphasizing, it’s this: Uncertainty is always greater than anyone expects. As the oft-quoted baseball sage Yogi Berra memorably put it, “It’s tough to make predictions, especially about the future.”

Still, these forces may converge in a way that keeps the expansion intact long enough for sentiment to catch up with the data. Perhaps 2026 will be even better than 2025, as attention shifts from markets and macroeconomics toward things that money can’t buy.

D. Brian Blank, Associate Professor of Finance, Mississippi State University and Brandy Hadley, Associate Professor of Finance and Distinguished Scholar of Applied Investments, Appalachian State University

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Siwei Lyu, University at Buffalo

Over the course of 2025, deepfakes improved dramatically. AI-generated faces, voices and full-body performances that mimic real people increased in quality far beyond what even many experts expected would be the case just a few years ago. They were also increasingly used to deceive people.

For many everyday scenarios — especially low-resolution video calls and media shared on social media platforms — their realism is now high enough to reliably fool nonexpert viewers. In practical terms, synthetic media have become indistinguishable from authentic recordings for ordinary people and, in some cases, even for institutions.

And this surge is not limited to quality. The volume of deepfakes has grown explosively: Cybersecurity firm DeepStrike estimates an increase from roughly 500,000 online deepfakes in 2023 to about 8 million in 2025, with annual growth nearing 900%.

I’m a computer scientist who researches deepfakes and other synthetic media. From my vantage point, I see that the situation is likely to get worse in 2026 as deepfakes become synthetic performers capable of reacting to people in real time.

Dramatic improvements

Several technical shifts underlie this dramatic escalation. First, video realism made a significant leap thanks to video generation models designed specifically to maintain temporal consistency. These models produce videos that have coherent motion, consistent identities of the people portrayed, and content that makes sense from one frame to the next. The models disentangle the information related to representing a person’s identity from the information about motion so that the same motion can be mapped to different identities, or the same identity can have multiple types of motions.

These models produce stable, coherent faces without the flicker, warping, or structural distortions around the eyes and jawline that once served as reliable forensic evidence of deepfakes.

Second, voice cloning has crossed what I would call the “indistinguishable threshold.” A few seconds of audio now suffice to generate a convincing clone – complete with natural intonation, rhythm, emphasis, emotion, pauses, and breathing noise. This capability is already fueling large-scale fraud. Some major retailers report receiving over 1,000 AI-generated scam calls per day. The perceptual tells that once gave away synthetic voices have largely disappeared.

Third, consumer tools have pushed the technical barrier almost to zero. Upgrades from OpenAI’s Sora 2 and Google’s Veo 3, and a wave of startups mean that anyone can describe an idea, let a large language model such as OpenAI’s ChatGPT or Google’s Gemini draft a script, and generate polished audio-visual media in minutes. AI agents can automate the entire process. The capacity to generate coherent, storyline-driven deepfakes at a large scale has effectively been democratized.

This combination of surging quantity and personas that are nearly indistinguishable from real humans creates serious challenges for detecting deepfakes, especially in a media environment where people’s attention is fragmented and content moves faster than it can be verified. There has already been real-world harm – from misinformation to targeted harassment and financial scams – enabled by deepfakes that spread before people have a chance to realize what’s happening.

The future is real-time

Looking forward, the trajectory for next year is clear: Deepfakes are moving toward real-time synthesis that can produce videos that closely resemble the nuances of a human’s appearance, making it easier for them to evade detection systems. The frontier is shifting from static visual realism to temporal and behavioral coherence: models that generate live or near-live content rather than pre-rendered clips.

Identity modeling is converging into unified systems that capture not just how a person looks, but how they move, sound, and speak across contexts. The result goes beyond “this resembles person X,” to “this behaves like person X over time.” I expect entire video-call participants to be synthesized in real time; interactive AI-driven actors whose faces, voices and mannerisms adapt instantly to a prompt; and scammers deploying responsive avatars rather than fixed videos.

As these capabilities mature, the perceptual gap between synthetic and authentic human media will continue to narrow. The meaningful line of defense will shift away from human judgment. Instead, it will depend on infrastructure-level protections. These include secure provenance, such as media signed cryptographically, and AI content tools that use the Coalition for Content Provenance and Authenticity specifications. It will also depend on multimodal forensic tools such as my lab’s Deepfake-o-Meter.

Simply looking harder at pixels will no longer be adequate.

Siwei Lyu, Professor of Computer Science and Engineering; Director, UB Media Forensic Lab, University at Buffalo

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Richard Whitman, University of Kent; Royal United Services Institute and Stefan Wolff, University of Birmingham

By agreeing to provide a loan of €90 billion (£79 billion) for the years 2026-2027, EU leaders have set the direction for the future of support for Ukraine.

At stake at the meeting of the European Council on December 18 was not just Kyiv’s ability to continue to defend itself against Russia’s ongoing aggression, but also the credibility of the EU as a player in the future of European security.

The key decision for the EU’s leaders was whether, and how, they would provide financial support for Ukraine over the next two years. Europeans have provided a vital drip-feed of ongoing financial assistance to Kyiv throughout almost four years of war.

But they have also struggled to fill, in its entirety, the hole created by the withdrawal of US support since the return of Donald Trump to the White House in January 2025.

The estimated €136 billion of budget support needed by Ukraine in 2026 and 2027 is a relatively fixed figure regardless of whether any peace initiative comes to fruition. A large part of it – €52 billion in 2026 and €33 billion in 2027 – is for military support.

The EU-agreed loan of €90 billion, “based on EU borrowing on the capital markets backed by the EU budget headroom”, thus covers at least the essential military needs of Ukraine. The loan will either contribute to the ongoing war effort or help create a sufficiently large and credible defence force to deter any future aggression by Russia.

Brussels is now the most important financial partner for Ukraine by any measure.

To fund the support the EU wants to provide to Ukraine, the commission developed two proposals. The most widely supported – and ultimately rejected – proposal was to use the Russian assets held by the Belgium-based Euroclear exchange as collateral to for a loan to fund Ukraine’s defence and reconstruction over the next few years.

In view of Belgian opposition because of insufficient protections against likely Russian retaliation, the European Commission had also proposed joint EU borrowing to fund support for Kyiv. Despite resistance from a group of EU member states, it was the only agreeable solution at the end.

The agreement on a loan to Ukraine funded from EU borrowing achieves the primary goal of securing at least a modicum of budgetary stability for Kyiv. But it came at the price of EU unity.

An “opt-out clause” had to be provided for Hungary, Slovakia and Czechia. All three countries are governed by deeply Euro-sceptical and Russia-leaning parties.

The deep irony is that by opposing EU support for Ukraine, they expose Ukrainians to a fate similar to that they suffered when the Soviet Union suppressed pro-democracy uprisings in Hungary in 1956 and then Czechoslovakia in 1968.

The EU until now managed to maintain a relatively united front on sanctions against Russia, on political, economic and military support for Ukraine, and on strengthening its own defence posture and defence-industrial base.

Over the past year, these efforts have accelerated in response to Trump’s return to the White House. This has shifted the US position to one which is in equal measure more America first and more pro-Russia than under any previous US administration.

And the pressure on Kyiv and Brussels has increased significantly over the past few weeks.

First there was the 28-point peace plan, which may have been a US-led proposal, but read as if it was Kremlin-approved. Then the new US national security strategy, which gave significantly more space to criticisms of Europe than to condemnation of Russia for the war in Ukraine.

No longer casting Russia as a threat to international security shows how detached the US has become from reality and the transatlantic alliance.

Russia’s president, Vladimir Putin, keeps insisting that he will achieve his war aims of fully annexing another four Ukrainian regions – in addition to Crimea – by force or diplomacy. Giving his usually optimistic outlook on Russia’s military and economic strength, Putin reiterated these points at his annual press conference on December 19.

EU divisions widen

In light of how squeezed Brussels and Kyiv now are between Washington and Moscow, the agreement on EU financing for Ukraine, despite its flaws and the acrimony it has caused within the EU, is a significant milestone in terms of the EU gaining more control over its future security. But it is not a magic wand resolving Europe’s broader problems of finding its place and defining its role in a new international order.

The agreement reached at the summit between the EU’s leaders on how to financially support Ukraine was overshadowed by their failure to overcome disagreement on signing a trade agreement with the South American trade group, Mercosur.

A decision on this trade deal with Argentina, Bolivia, Brazil, Paraguay, Uruguay and (currently suspended) Venezuela had been 25 years in the making. The deal was due to be signed on December 20, but this has now been postponed until January.

This is meant to provide time for additional negotiations to assuage opponents of the deal in its current form, especially France, Italy and Poland, who fear that cheaper imports from Mercosur countries will hurt European farmers. Those farmers staged a fiery protest at the European parliament ahead of the European Council meeting.

The delay does not derail the trade deal, which aims to create one of the world’s largest free trade areas. But it severely dents the EU’s claim to leadership of an international multilateral trading system based on rules that prioritise mutual benefit, as an alternative to the Trump administration’s unpredictable and punitive America-first trade practices.

Both disagreements continue to hamper the EU’s capacity for a decisive international role more generally. Where Trump’s US offers unpredictability, Brussels for now only offers extended procrastination on key decisions.

This places limits on the confidence that the EU’s would-be partners in a new international order can have in its ability to lead the shrinking number of liberal democracies. Without skilled and determined leadership, they will struggle to survive – let alone thrive – in a world carved up between Washington, Moscow and Beijing.

Richard Whitman, Member of the Conflict Analysis Research Centre, University of Kent; Royal United Services Institute and Stefan Wolff, Professor of International Security, University of Birmingham

This article is republished from The Conversation under a Creative Commons license. Read the original article.