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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Malni Kumarathunga and Athula Ginige address the important topic of sustainable agri-food ecosystems, an issue that affects all of us. The amount of global food waste is alarming and, not surprisingly, has a huge detrimental impact on natural resources. Blockchain can enhance trust along the supply chain and improve the situation, especially for smallholder farmers. The authors’ suggested model simultaneously reduces greenhouse gas emissions, allows for better resource use, and improves the livelihood of farmers.
Horst Treiblmaier elaborates on the complex concepts of blockchain and sustainability, both of which are comprehensive and frequently misunderstood. He illustrates how the technology offers a multitude of capabilities (e.g., immutability of data, shared access, programmability, security) that can yield numerous beneficial outcomes for sustainability efforts.
During the next decade, the healthcare industry will undergo a profound transformation as many important technologies, including AI, reach mainstream adoption. Clinical workflow will become more agile by virtue of AI and advanced analytics that automate decision-making processes. The emergence of these technologies requires a transformation from mere digital health to data-driven healthcare given the fundamental role of data in automated decision-making.
Ali Arabnya and Amin Khodaei explore blockchain’s potential to create the sustainable energy grid of the future. One of the defining features of the technology is decentralization, which perfectly matches with the idea of distributing the production, trading, and consumption of energy. This transition is going to be complex, and the authors do an excellent job of outlining what needs to be done and which challenges need to be overcome to produce more robust and efficient energy systems.
This Advisor explores three strategies tech companies can employ to avoid being damaged in the current atmosphere of treacherous geopolitics: lobbying, bandwagoning, and corporate de-risking. While some policymakers and pundits may view these strategies as violating the ideals of economic efficiency, new geopolitical realities dictate more corporate flexibility in pursuing healthy bottom lines.
This Advisor examines results from a recent Cutter Consortium survey on enterprise adoption of generative artificial intelligence. Based on our survey findings, approximately one-third of organizations currently indicate they plan to integrate large language models into their own applications, while nearly half are taking a wait-and-see approach.
Arthur D. Little’s Michael Papadopoulos, Nicholas Johnson, Michael Eiden, Philippe Monnot, Foivos Christoulakis, and Greg Smith debunk the idea that security concerns about LLMs are entirely new. They examine each concern to show that these issues are merely new manifestations of existing security threats — and thus manageable. “LLMs highlight and stress test existing vulnerabilities in how organizations govern data, manage access, and configure systems,” they assert. The article concludes with a list of 10 specific ways to improve LLM-adoption security.
Cutter Expert Curt Hall takes a fascinating dive into data on key GAI trends and examines findings from a Cutter survey of more than 100 organizations worldwide. Hall calls the rate of adoption of GAI tools “amazing.” Hall‘s article looks at enterprise adoption of LLMs, strategy and oversight for GAI adoption and usage, and enterprise experience with GAI to date.