Dresner Advisory's 2025 AI and Machine Learning Study Highlights Strategic Impact
In a recent study from Dresner Advisory Services, findings indicate a significant shift in the operational role of artificial intelligence (AI), data science (DS), and machine learning (ML) within organizations. The 2025 AI, Data Science, and Machine Learning Market Study is a part of the esteemed Wisdom of Crowds® research series. A considerable portion of survey participants acknowledged that AI is no longer just a novel technology but plays an essential role in formulating strategic initiatives. The transition of AI to act as a direct driver or a supportive element in business operations marks a pivotal change in how organizations perceive and utilize these advanced technologies.
The survey results reveal that AI, DS, and ML encompass a wide array of techniques, including statistics, modeling, neural networks, and data mining, aimed at analyzing and predicting outcomes based on factual data. This 12th edition of the study showcases the increasing relevance of these technologies as companies strive to enhance their operational efficiency, improve forecasting accuracy, and drive innovation in a competitive landscape.
Despite the current modest level of deployment, predictions suggest a robust future uptake of AI technologies. The study identifies key use cases where AI can significantly impact business performance, including demand forecasting, customer segmentation, and predictive maintenance. These elements are critical for organizations that wish to maintain an edge in today's data-driven environment.
Howard Dresner, founder and chief research officer at Dresner Advisory, commented on the findings by highlighting that most organizations recognize the direct or supportive role of AI in their operations. The need to address inefficiencies, conduct experiments, and prepare for market disruptions drives this investment momentum in AI technologies. While there is a general sense of caution among organizations, optimism prevails as many are advancing toward a more mature and extensive implementation of AI, DS, and ML aimed at maximizing business value.
In addition to studying the impacts of AI, Dresner Advisory also released a companion report focusing on ModelOps. This encompasses the practices and processes used to manage and operationalize machine learning models throughout their entire lifecycle. It includes various model types such as those utilized in machine learning and artificial intelligence, including large language models (LLM).
The 4th annual ModelOps Market Study addresses the management and governance of these AI and machine learning models. It emphasizes operational priorities that are necessary for maximizing the value derived from technological implementations. With the growing prevalence of these technologies, ModelOps is integral for ensuring operational efficiency and effectiveness within AI initiatives. It provides a comprehensive framework for managing model lifecycles, scalability, and performance metrics.
Dresner further elaborated on the ongoing evolution, stating that although the volume and variety of models in production are increasing, organizations face continuous challenges related to visibility, oversight, and accountability in this area. The rise of agentic AI highlights the urgency in establishing solid ModelOps practices, thereby extending their essential role beyond merely AI and machine learning to encompass all analytical models. As adoption rates deepen, effective ModelOps will be crucial for organizations to maintain adaptability, accountability, and overall value from their production models.
The Wisdom of Crowds® research methodology relies on data collected from various industry users to accurately represent the dynamics of usage, deployment trends, and product perceptions within the market. The comprehensive nature of the feedback provides a well-rounded perspective of contemporary realities and future aspirations when it comes to AI and machine learning utilization. To learn more about the insights shared in this study and the latest advancements in AI, visit Dresner Advisory's website.
Dresner Advisory Services, founded by Howard Dresner, is focused on delivering strategic insights in the fields of AI, data analytics, business intelligence (BI), performance management, and enterprise resource planning (ERP). The firm aims to enhance understanding and application of technology in business settings, contributing significantly to the discourse around these pivotal areas in today's organizational environments.
The survey results reveal that AI, DS, and ML encompass a wide array of techniques, including statistics, modeling, neural networks, and data mining, aimed at analyzing and predicting outcomes based on factual data. This 12th edition of the study showcases the increasing relevance of these technologies as companies strive to enhance their operational efficiency, improve forecasting accuracy, and drive innovation in a competitive landscape.
Despite the current modest level of deployment, predictions suggest a robust future uptake of AI technologies. The study identifies key use cases where AI can significantly impact business performance, including demand forecasting, customer segmentation, and predictive maintenance. These elements are critical for organizations that wish to maintain an edge in today's data-driven environment.
Howard Dresner, founder and chief research officer at Dresner Advisory, commented on the findings by highlighting that most organizations recognize the direct or supportive role of AI in their operations. The need to address inefficiencies, conduct experiments, and prepare for market disruptions drives this investment momentum in AI technologies. While there is a general sense of caution among organizations, optimism prevails as many are advancing toward a more mature and extensive implementation of AI, DS, and ML aimed at maximizing business value.
In addition to studying the impacts of AI, Dresner Advisory also released a companion report focusing on ModelOps. This encompasses the practices and processes used to manage and operationalize machine learning models throughout their entire lifecycle. It includes various model types such as those utilized in machine learning and artificial intelligence, including large language models (LLM).
The 4th annual ModelOps Market Study addresses the management and governance of these AI and machine learning models. It emphasizes operational priorities that are necessary for maximizing the value derived from technological implementations. With the growing prevalence of these technologies, ModelOps is integral for ensuring operational efficiency and effectiveness within AI initiatives. It provides a comprehensive framework for managing model lifecycles, scalability, and performance metrics.
Dresner further elaborated on the ongoing evolution, stating that although the volume and variety of models in production are increasing, organizations face continuous challenges related to visibility, oversight, and accountability in this area. The rise of agentic AI highlights the urgency in establishing solid ModelOps practices, thereby extending their essential role beyond merely AI and machine learning to encompass all analytical models. As adoption rates deepen, effective ModelOps will be crucial for organizations to maintain adaptability, accountability, and overall value from their production models.
The Wisdom of Crowds® research methodology relies on data collected from various industry users to accurately represent the dynamics of usage, deployment trends, and product perceptions within the market. The comprehensive nature of the feedback provides a well-rounded perspective of contemporary realities and future aspirations when it comes to AI and machine learning utilization. To learn more about the insights shared in this study and the latest advancements in AI, visit Dresner Advisory's website.
About Dresner Advisory Services
Dresner Advisory Services, founded by Howard Dresner, is focused on delivering strategic insights in the fields of AI, data analytics, business intelligence (BI), performance management, and enterprise resource planning (ERP). The firm aims to enhance understanding and application of technology in business settings, contributing significantly to the discourse around these pivotal areas in today's organizational environments.
Topics Business Technology）
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