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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One way to better understand the customer is through data about that customer.
The ever-increasing demand for cloud computing services deployed across multiple cloud data centers (CDCs) necessitates a significant amount of power, resulting in high carbon emissions and a negative effect on the environment. In sustainable cloud computing, renewable energy resources power the cloud data centers, replacing the conventional fossil fuel–based grid electricity or brown energy to effectively reduce carbon emissions.
The objective of this Update is to present an overview of an Agile development framework (ADF) as a set of different perspectives covering artifacts, roles, and activities, as the elements that populate the framework. Using a set of views, it suggests how this set of perspectives and elements may help us, as business analysts, in our understanding of Agile development and where we could next explore the ADF in more detail.
Many enterprise architecture (EA) teams struggle with creating a program that demonstrates the level of strategic value that they believe EA should have. Taking actionable steps to remove many of the most common roadblocks to growing the strategic nature of your EA program takes time. For most programs beginning the journey to strategic engagement, I strongly recommend dividing up the enterprise into business segments and applying EA to one (or at most two) segment(s) at a time.
Our latest research indicates that organizations overwhelmingly view customer engagement/customer experience management as the most viable use case for applying AI. This finding comes from an ongoing Cutter Consortium survey covering the adoption and application of AI and machine learning technology, based on the initial responses from 105 participating organizations.
We can define the real test of maturity through a key set of characteristics that demonstrate acceptance of, and commitment to, the discipline.
Advisor
AI Banking Initiatives in India
In this Advisor, we highlight a few AI applications that Indian banks have implemented to enhance customer experience.
2018 is a defining year for the commercial adoption of blockchain. Initiatives in various industries have reached a maturity threshold, marked by a transition of focus from experimental proof of concept projects toward production use.