Trust in generative artificial intelligence (GenAI) is increasing globally, despite notable gaps in AI safety measures. According to the IDC Data and AI Impact Report commissioned by SAS, 48% of respondents expressed complete trust in GenAI, while only 18% felt the same about traditional AI. However, only 40% of organizations are investing in governance and ethical safeguards to ensure AI trustworthiness. Kathy Lange, Research Director at IDC, highlighted a contradiction where AI forms with human-like interaction garner higher trust, regardless of their actual reliability. As AI systems become more integrated into critical processes, the report emphasizes the importance of strong data foundations and governance to mitigate risks and enhance the return on investment.
According to Gartner, the use of generative AI is projected to lead to a significant decline in critical-thinking skills, prompting 50% of global organizations to require “AI-free” skills assessments by 2026. Daryl Plummer, a distinguished analyst at Gartner, warns that while embracing AI is essential, organizations must also emphasize the importance of human skills beyond technology. In addition, by 2027, 75% of hiring processes are expected to include certifications for workplace AI proficiency, highlighting the growing demand for AI skills in the IT workforce. Gartner predicts that the rise of generative AI will challenge mainstream productivity tools, potentially shaking up a $58 billion market. Furthermore, as countries like those in the European Union push for digital sovereignty, enterprises will face challenges in deploying uniform AI across different regions, with fragmented regulations anticipated to cover 50% of the world’s economies by 2027, driving substantial compliance investments.
Research firm Forrester warns that large organizations plan to defer 25 percent of their anticipated artificial intelligence spending from 2025 until 2027, indicating a potential market correction. Forrester’s analysis highlights a growing disconnect between the inflated promises made by AI vendors and the actual value delivered to enterprises, with fewer than one-third of decision-makers connecting AI investments to financial growth. In 2026, the hype surrounding AI is expected to diminish as companies face greater pressure to demonstrate measurable results from their AI initiatives. Sharyn Leaver, Forrester’s chief research officer, emphasized the need for tighter financial scrutiny and governance amid complex geopolitical and economic uncertainties. Meanwhile, the Bank of England has raised concerns about a market correction reminiscent of the dotcom bubble, citing similar financial metrics.
Recent analysis by the workplace platform Visier indicates that the trend of “layoff boomerangs” suggests that replacing workers with artificial intelligence may not be as effective as anticipated. Despite rising layoffs, rehiring rates are increasing, with approximately 5.3% of laid-off employees being brought back by their former employers, a figure that has seen a slight uptick since 2018. Andrea Derler, a principal at Visier, notes that while some executives view AI as a straightforward solution for workforce reduction, the reality is more complex. Companies may face hidden costs associated with layoffs, such as unemployment insurance and severance packages, which can exceed the savings from workforce cuts.
Why do we care?
So apparently, we trust generative AI now — almost half of people say they completely trust it. But only 40% of companies are actually putting governance or ethical safeguards in place. That’s not trust — that’s complacency.
IDC says we trust AI more when it sounds human. That’s scary. We’re confusing confidence for competence — just because the model sounds smart doesn’t mean it is.
Then there’s the Gartner piece: by 2026, half of companies will test employees for “AI-free” critical thinking skills. That’s right — we’ve gotten so dependent on AI that employers now have to check if people can still think for themselves.
And while all this hype builds, Forrester says a quarter of planned AI spending is being pushed back. Enterprises are pulling the reins — they want results, not experiments.
Add to that the “layoff boomerang” — companies firing workers for AI, then rehiring them because the robots didn’t pan out.
Don’t sell trust, build it. Governance, compliance, and measurable ROI — that’s the real opportunity. The AI gold rush isn’t about who builds the shiniest model. It’s about who keeps it from blowing up the business that bought it.