Public perception suggests investors and the tech industry are the primary factors driving demand for AI adoption, but recent data suggests workers, not corporations, are the ones driving these trends.
Recon Analytics, a leading customer insights service provider, has surveyed well over 100,000 workers in an effort to gather real-time data that can give enterprises the recent and relevant information they need to not only answer AI usage questions, but also make predictions based on that data to get ahead of trends. Among 70,000 of these workers, 61% reported that they use AI tools, not because they were told to do so, but because they sought to get more work done faster.
These findings suggest that AI is becoming human-driven rather than model-driven, with workers selecting AI tools based on speed, ease, and trust instead of the results optimization that many businesses have prioritized.
The Value of Current, Quality Data
Given the disconnect between consumers and AI platforms, the AI market is currently quite volatile and prone to rapid swings, such as those between the market shares of ChatGPT and Gemini. AI workplace transformation analysis shows how these shifts are reshaping business strategy across industries.
Recon provides enterprises a degree of certainty amongst this volatility because their AI insights are based on real-time data pulled from the largest dataset of its kind. Additionally, Recon maintains the ability to answer questions within a week’s time, making it easier for them to uphold their mission of anticipating outcomes rather than merely reacting to them. With these insights, enterprises can make high-impact decisions based on real, reliable, and current user intelligence.
Concrete Insights from Recon’s Roger Entner and Joe Salesky
Recon founder Roger Entner and Joe Salesky, CEO of Recon’s AI division, have both conducted in-depth analyses and interpretations of the aforementioned dataset, yielding a number of valuable, concrete insights.
“Workers prioritize speed over every other value driver,” Entner explains, noting that this fundamentally changes how AI platforms should approach product development. Thus far, the two have determined that among the 61% of workers who use AI tools, those who use paid, premium versions report a 13% increase in productivity. For nearly 80% of workers who use AI tools, however, this boost is not enough to warrant paying for them, which explains why so many users are hesitant to utilize paid services.
Interestingly, Entner and Salesky explain that 29% of surveyed users who do pay for AI tools eventually churn out of those services. This churn substantially contributes to the AI market’s current instability. As to why this churn occurs, Entner and Salesky determined that workers prioritize speed over other value drivers such as ease of access and privacy. AI platforms have not been tailoring their tools to meet these demands; instead, they have focused on outcomes rather than processes.
How Workers Outpace Traditional Research Methods
“Market shifts happen too quickly for traditional research methods,” Salesky notes. “Our real-time model is built precisely for this moment.” Recon’s proprietary real-time model makes their services invaluable at a time when these quick market shifts demand immediate intelligence. AI adoption has taken place suddenly and quickly, as users feel out what they do and do not need from their AI tools. As it stands, AI platforms need to accommodate these demands, not the other way around.
AI is reaching a cultural tipping point, making Recon Analytics’ real-time data all the more important for explaining how workers, not companies, are driving where AI goes next.
