Data Analytics & Digital Technologies

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Strategic advice & alerts to leverage data analytics & new technologies

Leverage data and the technologies that generate it, from IoT to AI/machine learning, wearables, blockchain, and more, to improve decision-making, enrich collaboration and enable new services.

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Data Analytics & Digital Technologies
Advisor

Designing Cognitive Computing Systems: 3 Recommendations

by Kevin Desouza, by Lena Waizenegger, by Gregory Dawson

Designing cognitive computing systems (CCSs) requires a strong case for the investment into those systems. Organizations must not only be able to justify the initial investment into developing a CCS, but also think through the investments that will be needed to ensure it can be refined and enhanced over time.


Chintamani Joshi
Executive Update

Monetizing Your APIs

by Chintamani Joshi

This Executive Update presents a framework in the form of processes, techniques, measurement metrics, and best practices to guide you toward successful API monetization.


Figure 1 —  Does your organization currently use — or plan to use — open source AI technology?
Advisor

Open Source or Commercial AI Provider's Platform?

by Curt Hall

Based on responses so far, an ongoing Cutter Consortium survey on the adoption and application of AI technology provides some insight into the issue of enterprise AI adoption trends.


siau
Article

Building Trust in Artificial Intelligence, Machine Learning, and Robotics

by Keng Siau, by Weiyu Wang

Keng Siau and Weiyu Wang examine prevailing concepts of trust in general and in the context of AI applications and human-computer interaction in particular. They discuss the three types of characteristics that determine trust in this area: human, environment, and technology. They emphasize that trust building is a dynamic proc­ess and outline how to build trust in AI systems in two stages: initial trust formation and continuous trust development.


Raj Ramesh
Article

AI Is Driving New Business Models: How Do We Adapt?

by Raj Ramesh

Raj Ramesh discusses business model transformation with a focus on the insurance sector. He covers the potential of AI in insurance and then expands his discussion to the ingredients necessary for AI to provide good value to the business in any sector.


AI opportunities
Article

AI Enables Efficient and Effective Digital Government

by Vipin Jain, by Seema Jain

Vipin Jain and Seema Jain discuss the opportunities emerging from artificial intelligence and how cognitive technologies will fundamentally change the way government works. They outline how the US public sector is currently adopting and planning to embrace AI and ML in various applications. They also highlight priorities for federally funded research in the US. To help developers in conceiving and developing AI appli­cations, the authors present an AI adoption frame­work and briefly discuss the categories of AI-branded services available from leading cloud service providers. They finish with a consideration of whether AI is a job creator or a job destroyer.


Digital adopters of AI
Article

Transforming Banks Through AI

by Hema Kumaran, by Prema Sankaran, by Raj Gururajan

Hemamalini Kumaran, Prema Sankaran, and Raj Gururajan discuss how AI is transforming the banking sector. They outline how Indian and US banks are using AI to gain significant benefits and offer an enhanced customer experience. The authors examine the key drivers that inspire banks to embrace AI, the challenges involved in implementing it, and what needs to be considered in applying AI to best serve customers.


ccs
Article

9 Recommendations for Designing, Developing, Deploying, and Refining Cognitive Computing Systems

by Kevin Desouza, by Lena Waizenegger, by Gregory Dawson

This article draws your attention to the design, devel­opment, deployment, and refinement of cognitive computing systems (CCSs). While CCSs are deployed in a variety of fields yielding benefits exceeding expectations, there are also major failures. Lack of appreciation for the differences inherent in developing a CCS versus a traditional software system is key to these failures. To assist in developing successful CCSs and to derive benefits from them, the authors offer a set of nine key recommendations based on their examination of over two dozen systems. They conclude that CCSs will be a dominant technol­ogy that will permeate all business operations for the foreseeable future.