Strategic advice to leverage new technologies
Technology is at the heart of nearly every enterprise, enabling new business models and strategies, and serving as the catalyst to industry convergence. Leveraging the right technology can improve business outcomes, providing intelligence and insights that help you make more informed and accurate decisions. From finding patterns in data through data science, to curating relevant insights with data analytics, to the predictive abilities and innumerable applications of AI, to solving challenging business problems with ML, NLP, and knowledge graphs, technology has brought decision-making to a more intelligent level. Keep pace with the technology trends, opportunities, applications, and real-world use cases that will move your organization closer to its transformation and business goals.
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In much the same way ”design-for-producibility” is key to successful hardware production, “architect-for-real-ability” is key to capability realization. Everyone involved from the beginning in the specification, development, and operation of a capability needs to perform as, an organized, integrated team.
Computer vision and imaging technology is having a considerable impact in the insurance industry. A number of developments are driving this trend. From a product/market perspective, the growing availability of cloud platforms and services — including commercial computer vision and imaging applications tailored for specific insurance use cases — has made the technology more practical for insurers to implement. This Advisor explores the opportunities, benefits and applications of AI and computer vision in the insurance sector.
The edition of The Cutter Edge explores the power and peril of AI technology, challenges to low-code technology adoption as well as solutions, and more!
If the ultimate goal of artificial intelligence (AI) is to efficiently replicate and exceed human thought for the good of humanity, then building trust requires that AI incorporate the multitude of sound human decision capabilities. Just reading this statement makes it clear that the journey toward AI ethics is no easy road.
In this Advisor, we explore three critical technologies that organizations are interested in using to support their enterprise IPA initiatives: natural language processing (NLP), intelligent virtual assistants/smartbots, and intelligent optical character recognition (iOCR). This data is based on a survey recently conducted by Cutter Consortium of how organizations are adopting or planning to adopt IPA.
As industries have become completely unpredictable, modern strategic planning requires distinct skills to determine competitive environments. This Advisor explores how troubleshooting can help you identify the competitive environment for your industry, how strategy is the design of your solution, and how your enterprise is the implementation of that solution.
Ben Porter uses several case studies to show how organizations have made progress in amplifying the value of analytics by demonstrating three actions: recognizing how value is created, focusing on delivering that value, and understanding the changes that must be adopted to ensure long-term value. He describes the four fundamental requirements for successful analytics projects (sponsor, tools, team, and project/problem) and closes with the critical assertion that value creation from analytics requires teamwork between IT, business, and analytics professionals.
Michael Papadopoulos and Philippe Monnot take a deep dive into ML projects. They address the “very powerful tendency to anthropomorphize ML and AI, imbuing it with human characteristics.” As we increasingly describe them in human terms, we often fail to make a critical distinction in the way humans and machines interpret the world.