A recent Pew Research Center study highlights that Americans are more concerned than excited about artificial intelligence and its growing presence in daily life. Conducted with 5,023 adults, the survey revealed that 50% of participants expressed greater concern than excitement regarding AI, a significant increase from 37% in 2021. Additionally, 57% of respondents rated the societal risks of AI as high, while only 25% viewed its benefits similarly. Americans expressed skepticism about AI’s impact on human creativity and relationships, with 53% believing it would worsen creative thinking and 50% saying it would negatively affect interpersonal connections. This research underscores the ongoing debate about AI’s role in society and the need for better understanding and control over its application.
New research from LearnUpon reveals that artificial intelligence is significantly reshaping workplace learning and development, as organizations in the United States, United Kingdom, Australia, and New Zealand increase their budgets for these initiatives. According to the inaugural “State of Learning and Development Report,” 43% of learning and development leaders believe that AI could fully replace their roles, while 40% anticipate partial changes due to AI disruption.. The report highlights that 91% of leaders feel confident in measuring the effectiveness of their programs, with a notable shift toward tracking broader business-aligned outcomes beyond traditional metrics.
Recent studies reveal that artificial intelligence chatbots are relying on flawed research from retracted scientific papers to answer questions, raising concerns about the reliability of these AI tools in evaluating scientific information. Researchers found that when OpenAI’s ChatGPT was asked about medical imaging based on 21 retracted papers, it referenced these papers in five instances, advising caution in only three cases. As the use of AI chatbots for medical advice and scientific research continues to grow, it is imperative to ensure these tools accurately reflect the current state of research, including the status of published papers. The National Science Foundation has recently invested $75 million to advance the development of AI models for scientific research, highlighting the urgent need for robust quality checks in AI-generated information.
Why do we care?
Americans aren’t buying the hype—Pew says half of us are more worried than excited about AI, up big since 2021. In the workplace, learning leaders are already wondering if AI is coming for their jobs. And on top of that, chatbots are spitting out answers based on retracted science papers. That’s not trust—that’s risk.
Customers are not just curious about AI; they’re anxious. Inside organizations, AI is already seen as disruptive to professional roles, with nearly half of learning leaders believing their jobs could be replaced. That tension underscores a paradox: businesses are spending more on L&D, but staff may be skeptical about whether AI will ultimately help or displace them.
Bad data leads to bad outputs. This goes beyond medical use cases—MSPs and IT providers deploying AI need to think about data provenance, validation layers, and customer safeguards. It’s not enough to roll out a chatbot or AI agent; providers must establish quality checks and communicate clearly about limitations.
For IT service providers, here’s the play: it’s not about who’s first with AI tools, it’s who helps customers use them responsibly. Put in governance, validate the data, and frame AI as augmentation, not replacement. That’s where the real value is going to be.