Beyond the Hype: AI in Use Today
We are in the hype cycle of Artificial Intelligence. Everyone is talking about AI. Venture capitalists and large technology companies are competing over how much money they can invest in it. Teenagers are testing their prompt engineering skills to get answers, create images, write code, and generate video clips. Employees are using it to do research, create sales pitches, and analyze data. Executives are struggling to set AI policies and define strategies.
Gartner Hype Cycle
The technology trigger was OpenAI’s introduction of ChatGPT, and we are now approaching what some think is the peak of inflated expectations. Extrapolating from the advancements in Large Language Model’s, some are predicting that Artificial General Intelligence is imminent and the end of human labor will soon follow. Others are predicting a less dire future—a utopia where AI software agents and AI robots free workers to focus on what Abraham Maslow described as self-actualization activities.
According to Gartner’s Hype Cycle chart, neither outcome is right around the corner. In fact, some of you may feel like you are now in the trough of disillusionment. As many experiments and implementations inevitably fall short of expectations, there will be a shake out of AI software providers. Every unicorn will not succeed. However, investments by industry in AI software will continue as the surviving providers improve their products to the satisfaction of early adopters. This will lead to the slope of enlightenment and eventually to a plateau of productivity.
How Should Private Equity Investors Assess the Hype?
For portfolio company executives and their fund investors weighing when to invest in AI technologies, should the Gartner Hype Cycle model be part of their decision calculus or merely an interesting technology adoption phenomenon to recognize? We argue the latter. While the early peaks and valleys represent sentiment that is either too optimistic or too pessimistic, if the technological innovation has sustainable benefit—represented at some level as the plateau of productivity—then you must invest early for competitive advantage and, indeed, survival.
And we emphasize that the plateau of productivity is often misrepresented by this graph—the productivity gains of technological innovations such as the PC, Internet, and mobility far exceeded even the most inflated early expectations of financial analysts and technology pundits. The hype cycle was observed in each of these cases; however, companies that chose the role of late adopters found themselves so far behind that they couldn’t catch up.
Current State of AI Adoption
While AI often makes headlines for its potential future capabilities to replace humans, the technology is already deeply embedded in many sectors of the economy. Recent data provides unprecedented insight into how AI is actually being used across industries, moving beyond speculation to hard evidence of its impact.
According to the 2025 Anthropic Economic Index, which analyzed millions of anonymized conversations with AI assistants, approximately 36% of occupations now use AI for at least a quarter of their associated tasks. This comprehensive study, based on direct analysis of AI usage rather than surveys or predictions, reveals that AI is primarily serving as a collaborative tool rather than an automation replacement.
The data shows a clear pattern in how AI is being integrated into work: 57% of AI usage involves "augmentation," where AI assists workers through activities like brainstorming, refining ideas, and accuracy checking. The remaining 43% represents direct automation, where AI completes tasks with minimal human involvement.
Distribution Across Industries and Roles
Software engineering leads AI adoption, accounting for 37.2% of analyzed AI interactions. These predominantly involve tasks such as debugging code, modifying software, and network troubleshooting. The second most significant category is creative and editorial work, including media, marketing, and content production, representing 10.3% of AI usage.
McKinsey's "State of AI" report complements these findings, showing that 55% of organizations report using AI in at least one function, with the highest adoption rates in product development and service operations.
Wage Distribution and AI Usage
One of the most revealing findings from the Anthropic Economic Index is the relationship between AI adoption and wage levels. Rather than concentrating at either end of the wage spectrum, AI usage peaks in the mid-to-high salary range, particularly among technical and analytical roles.
Financial Services
Banks and financial institutions continue to be significant adopters of AI technology. Visa's AI-powered fraud detection system, according to their 2023 security report, prevented an estimated $27 billion in fraud attempts in 2022, analyzing hundreds of millions of transactions in real-time using advanced machine learning algorithms.
Healthcare
In healthcare, AI has shown particular promise in specific applications. A 2023 study published in Nature Medicine demonstrated that AI algorithms achieved 91.5% accuracy in detecting breast cancer in mammograms, comparable to expert radiologists. The study, analyzing over 500,000 mammograms, represents one of the largest validations of AI in medical imaging.
Manufacturing and Physical Labor
The Anthropic Index reveals that AI usage is significantly lower in fields requiring physical labor, such as healthcare delivery, transportation, and agriculture. For instance, only 0.1% of analyzed conversations related to farming, fishing, and forestry tasks, highlighting the technology's current limitations in hands-on work requiring manual dexterity or complex physical interactions.
However, in specific manufacturing applications, successes have been documented. BMW Group's 2023 manufacturing report details their AI-powered image recognition systems inspecting over 100,000 components daily across their production facilities, with an accuracy rate exceeding 99% in detecting defects.
Impact on Workforce and Productivity
The U.S. Bureau of Labor Statistics' 2023 report on automation in the workplace, combined with the Anthropic Index findings, provides a clearer picture of AI's impact. Only about 4% of occupations show AI usage for at least 75% of their tasks, suggesting that while AI is transforming work processes, it is not leading to widespread job displacement yet.
MIT's Work of the Future task force's 2023 report found that companies successfully implementing AI saw the most significant gains when they focused on human-AI collaboration rather than replacement. This aligns with the Anthropic Index's finding that augmentation, rather than automation, is the dominant pattern of AI usage.
Challenges and Future Outlook
The World Economic Forum's 2023 Global Risk Report identifies several well-documented challenges in AI implementation. According to IDC's verified market research, global spending on AI systems reached $120 billion in 2023, with a projected compound annual growth rate of 26.5% through 2026.
The Anthropic Economic Index suggests that businesses should focus AI adoption efforts on knowledge-based professions where augmentation, rather than replacement, is the dominant pattern. This approach aligns with current usage patterns and appears to yield the most significant benefits.
Conclusion
The real-world applications of AI today demonstrate that while the technology has not reached its hypothetical potential (or early peak of inflated expectations), it is already delivering measurable benefits across industries. Success appears to come from thoughtful implementation that combines AI capabilities with human expertise, creating systems that enhance rather than replace human capabilities. As the Anthropic Index reveals, the future of AI in the workplace is not about wholesale automation but rather about strategic augmentation of human capabilities across a wide range of professional tasks.
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NextAccess Authors: Scott Kosch and Valerie VanDerzee
NextAccess is an advisory firm of experienced operators with deep experience running top-performing organizations and delivering exceptional results. We help executive teams and investors build stronger, more valuable companies through a powerful mix of operational expertise, strategic insight, and data-driven solutions.
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