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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Artificial intelligence (AI) strategy, at its core, must closely align with a company’s business objectives, ensuring synergy between the corporate strategy and the AI strategy.
Artificial intelligence (AI) and machine learning (ML) are technologies that can solve problems and do a world of good. But we must not forget that they are fallible and require human oversight. AI/ML developers must adhere to a strong code of ethics and employ ethicists to audit new applications. They must also ensure valid and reliable data testing and remain vigilant to the possibility that the technology may not work as intended.
Based on recent findings from a Cutter Consortium survey on customer experience (CX) management in the enterprise, most organizations appear to have somewhat guarded expectations of artifical intelligence’s potential to influence CX.
A business architecture initiative such as business capability modeling can be a challenging endeavor in many organizations. Typically, little clarity exists as to what a business capability is, what business capabilities are used for, and why a business needs them. The challenge is to address these concerns while succinctly articulating why adopting business capability modeling is a good idea.
In Part VI of this Executive Update series on customer experience (CX) management, we examine findings covering the various advanced technologies on organizations’ radar regarding their CX efforts.
Examples of unintended consequences abound in government and the social sciences, but also occur in engineering, business, management, IT governance, and other areas. In this Advisor, we explore some examples.
This Advisor looks at two fundamental project metrics that everyone uses at all levels in the IT organization: size and flow.
This Executive Update describes the unique challenges to quality in the big data domain as well as various approaches to handling and resolving those challenges.