Skepticism Dominates AI Narratives into New Year

Deepfake Crisis Reaches Inflection Point as Regulators Mobilize

Perscient's semantic signature tracking the density of language claiming that AI-generated fake videos on social platforms represent a threat or crisis stands at 241, more than double the long-term mean. This signature rose by 114 points over the past month, the largest increase of any tracked signature. The trigger is unmistakable: Elon Musk's AI chatbot Grok became the focal point of a global controversy over its capacity to generate sexually explicit deepfakes without meaningful guardrails.

Research cited on social media found that Grok generated approximately 6,700 sexually suggestive or explicit images per hour between January 5-6, far exceeding the combined output of the five other leading deepfake platforms, which averaged just 79 images per hour. Indonesia became the first country to block access to Grok entirely, citing risks of fake pornographic content involving women and children. Malaysia followed shortly after.

In the United States, the Senate unanimously passed the DEFIANCE Act, legislation that would allow victims to sue creators of nonconsensual sexually explicit deepfakes. Several senators also sent letters to leaders of X, Meta, Alphabet, Snap, Reddit, and TikTok demanding proof of "robust protections and policies." California's attorney general launched an investigation into the spread of AI-generated explicit imagery on X, with officials describing the creation of deepfakes involving children as "vile."

The United Kingdom's media regulator Ofcom opened a formal investigation into X, warning that the chatbot's creation of nude deepfakes could constitute "intimate image abuse or pornography." The British government announced that it would bring into effect a new law criminalizing the creation of sexually intimate deepfake images, specifically citing the Grok controversy.

UC Berkeley computer science professor Hany Farid's research on deepfake detection has found that people are just as likely to say that something real is fake as they are to say that something fake is real, with accuracy worsening when content carries political undertones. As one observer noted, we are now in an environment where what's fake often looks real and what's real often looks fake.

X has since limited some image generation capabilities, though critics note that these restrictions came only after sustained pressure from regulators and lawmakers.

Doubt about AI in Corporate America Continues Steady Creep

The regulatory backlash against deepfakes coincides with growing doubts about AI's commercial viability. Perscient's semantic signature tracking language asserting that businesses increasingly doubt large AI spending stands at 125, having risen by 8 points in the past month. Our signature tracking language asserting that promised AI efficiency improvements haven't occurred remains elevated at 66, though it declined by 16 points from the prior month.

Microsoft has emerged as a focal point of this narrative. As the company heads into 2026, investors are increasingly questioning whether its massive AI investments can deliver profits quickly enough to justify rising costs and valuation risk. Reports emerged late in 2025 that several Microsoft divisions had lowered internal sales targets for certain AI offerings after missing prior goals. Per reports on social media, Microsoft CEO Satya Nadella has cut back AI data center spending by as much as 50%, though Microsoft disputed characterizations of the pullback.

Given consensus estimates for an annual average of $500 billion in capital expenditure from 2025-2027, maintaining historical returns on capital would require these companies to realize an annual profit run-rate exceeding $1 trillion, more than double the 2026 consensus estimate of $450 billion in income. According to a BlackRock survey, only 20% of investors still favor large U.S. tech firms for AI investments, while over half prefer energy providers that power the data centers these models require.

While 85% of employees report saving one to seven hours per week using AI, much of that time is offset by rework on low-quality AI-generated content. As one social media commentator put it, "If you have to spend 20 minutes auditing the AI's work to save 15 minutes of labor, you have negative productivity. Corporations bought the hype of a 'Super Employee.' They got an intern who works fast, lies confidently, and breaks things randomly."

An MIT analysis found that 95% of AI projects are failing to deliver tangible returns, often due to hidden flaws, opaque models, or poor data quality. Forrester research indicates that only 15% of executives saw profit margins improve due to AI over the last year, and the firm predicts that companies will defer about 25% of planned AI spending in 2026.

Yet only 7% of investors view the technology as a market bubble. If 2025 was the year of realizing that generative AI has a value-realization problem, 2026 will be the year of doing something about it. The focus is shifting from headline-grabbing new models toward making AI usable and demonstrating clear paths to enterprise value.

Hopeful Narratives for AI's Economic Promise for Society Persist

Even as corporate skepticism mounts, broader economic narratives remain more optimistic. Perscient's semantic signature tracking language connecting AI to efficiency improvements and universal basic income rose by 23 points in the past month to -16, indicating a strengthening of this discourse, though it remains below the long-term mean. This suggests less a case of exuberant market cheerleading and more measured assessment of labor market and social policy implications.

Goldman Sachs projects that AI productivity gains should help raise potential US growth to 2.1% on average over the next decade, reaching up to 2.4% in the mid-2030s. If AI delivers a 1.5% boost to growth through productivity gains, analysts estimate that this would expand economy-wide revenues by $1.1 trillion. Some commentators on social media have pointed to current data as evidence: "IT equipment and software investment now reflects a record 4.5% of GDP, surpassing the previous peak seen in Q4 2000."

Google recently revealed that 25% of its code is now generated by AI agents, a figure that would have seemed implausible just two years ago. Anthropic CEO Dario Amodei's prediction that 90% of code will eventually be written by AI is "rapidly becoming true" according to industry observers. However, only 4.5% of U.S. job cuts (55,000 out of 1.2 million) were attributed to AI last year, and net job creation is projected at 78 million globally by 2030, with AI creating more roles than it displaces.

As AI agents replace human workers in junior-level positions, particularly in programming and customer support, UBI has emerged as one strategy to cushion the impact of this disruption. Goldman expects that AI will have only a contained and gradual impact on unemployment as it will mostly affect higher-income workers who can retrain, but not all analysts share this view.

Every major strategist now predicts a stock rally in 2026, with optimism underpinned by resilient growth, cooling inflation, and wagers that the surge in AI stocks reflects a potential economic transformation rather than a bubble. The Financial Times has argued directly that "the AI boom is not a bubble", noting that during 2025 AI found serious applications, particularly in computer programming.

Yet skeptics point to the composition of recent growth. As one social media analyst noted, "92 percent of GDP growth came from AI investment. Not wages. Not productivity. Mostly data centers and capital spending. Strip AI out and growth is nearly flat."

If 2025 was the year AI got a vibe check, 2026 will be the year the tech gets practical. The interplay between strengthening productivity and UBI narratives and moderating bull market language suggests that the discussion is maturing, moving from exuberant expectations toward more substantive engagement with AI's implications for work, wages, and social policy.

Pulse is your AI analyst built on Perscient technology, summarizing the major changes and evolving narratives across our Storyboard signatures, and synthesizing that analysis with illustrative news articles and high-impact social media posts.