AI news ·
Reports show generative AI adoption remains slow and uneven amid consumer skepticism and algorithmic bias.
Only 18.4% of US businesses will actively use AI in 2026 due to high costs. Meanwhile, workers with AI skills earn up to 25% more and get promoted 3.5 times faster.
Eighteen months into the generative AI boom, the gap between what the technology is promised to do and what it is actually doing is widening, not closing. A series of reports released this week covering business adoption, consumer trust, career mobility, and algorithmic bias reveal that AI adoption is slow, concentrated, and met with deep skepticism, while bias remains baked into the systems themselves.
Business adoption slow, concentrated among large firms
Massachusetts-based Daniel Research Group estimates that only 18.4% of US businesses will be actively using AI to produce goods or services in 2026. That figure rises from 11.2% in 2025 and just 3.9% in 2023. The firm's analysis, built on Census Bureau data, found that activity remains concentrated among large companies and technology-heavy sectors. Small and mid-size businesses, which make up the bulk of US firms, are still on the sidelines.
Cost, a shortage of qualified staff, and unresolved questions about return on investment remain the biggest brakes on faster uptake. The firm also described a deeper, recurring unease about handing decisions to machines. For IT and development teams in smaller organizations, this means the practical challenges of AI for IT & Development implementation-finding talent, proving ROI, and managing risk-are far from solved.
Consumers are not buying the pitch
If businesses are cautious, consumers are openly skeptical. A new Future of the Web survey from WordPress VIP, conducted among 2,000 respondents including 800 enterprise marketing decision-makers, found that 74% of people think the internet feels less human than it did a decade ago. The average person hits "bot fatigue" within about 40 minutes. Six in 10 said AI showing up in a brand's messaging is actually a turnoff, and most could not name a single company they believe is using AI well in its marketing.
Search results or AI-generated answers without clear attribution are now the thing US consumers say they trust least online, ranking below medical bills, airline fees, and confusing fine print. Yet 86% still click through to an original source after getting an AI summary. Enterprises are investing in the opposite direction: 60% of their audience reach now comes from third-party platforms they do not own, while only 17% plan to prioritize their own websites for growth next year.
AI pays off for individual workers
Where the technology is paying off most clearly is for individual workers, according to talent firm Randstad. Its analysis of more than 35 million job postings since 2021 found that professionals who pick up advanced AI credentials are securing promotions up to 3.5 times faster than traditional peers. AI-integrated roles command salary premiums of up to 25% over traditional equivalents. Demand for distinctly human skills-creativity, emotional intelligence, ethical judgment-has also surged alongside it.
"While today's headlines often focus on how automation is leading to job displacement, our data reveals a powerful human judgment premium emerging across the US workforce," said Greg Dyer, CCO of Randstad North America. "The most successful professionals today are using AI to not only work faster, but also free up the headspace required for the critical thinking only a human can provide."
Bias built into the systems themselves
A peer-reviewed study led by Special Olympics in partnership with Oregon State University, published in the Disability and Health Journal, asked five widely used large language models-including GPT-4-Turbo-to generate 25,000 short stories about everyday situations. Stories describing a person with an intellectual disability were consistently portrayed as more dependent, more childlike, and more in need of supervision. Some stories were more than 100 times as likely to carry a paternalistic tone. The findings underscore how Generative AI and LLM systems can embed harmful stereotypes at scale.
"Artificial intelligence is quickly becoming foundational to how our world operates, from healthcare to education to economic opportunity. That makes this a pivotal moment," said Nathan Cook, Special Olympics Chief Information and Technology Officer. "If we do not intentionally design for inclusion from the outset, we risk embedding bias into systems that will scale globally and persist for generations. We want to disrupt automated ableism from the start."
Why this matters for IT and development professionals
The reports highlight a split: AI is advancing, but its benefits are unevenly distributed. For developers and IT leaders, the concentration of adoption in large firms and tech-heavy sectors signals that most businesses still lack the internal capability to deploy AI effectively. The talent shortage cited by Daniel Research Group means professionals who can bridge the gap-combining technical skill with an understanding of ROI and risk-will command a premium. At the same time, consumer distrust and documented bias in language models mean that shipping AI features without clear attribution, fairness testing, and human oversight will backfire. The opportunity lies in building systems that are transparent, inclusive, and demonstrably useful, not just technically impressive.