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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Among the most important developments concerning AI and blockchain are the new, emerging business models, enabled by these technologies, that are beginning to appear in various industries. This is especially true when it comes to fintech, and the combining of blockchain and AI to create new financial platforms that can provide virtual banking services to people who currently are not served or who are underserved by more traditional banking services offers a good example.
As part of an ongoing series on artificial intelligence (AI) in the enterprise, in this Executive Update, we turn specifically to AI development platform preferences, including open source and commercial providers’ development tools and AI-as-a-service platforms.
Based on our client experience, a significant opportunity to improve the business value of both enterprise architecture (EA) and Agile lies in combining their practices. Several frameworks could help in this sense, and with the right vision in mind, companies can increase their ROI for both EA and Agile. In practice, we have seen several ways in which organizations combine EA with Agile thinking and methods to break through the anti-patterns and improve results. This Advisor highlights a useful example from a Netherlands central government client and comes down to the adoption of Agile architectural approaches described in SAFe 4.5.
About a decade ago, Cutter Consortium published my Executive Update series on the project-volatility metric, which examined the notion of project volatility and set forth the assumptions that underlie my own project-planning approach. The framework has grown tremendously. Thus, we are returning to this Update series with a revised Part II and a plethora of Updates to come.
Some of the more interesting developments with artificial intelligence (AI) involve its application in media and entertainment. There is a great deal of innovation underway to utilize AI in practically all aspects of media and entertainment — from content creation, procurement, categorization, and distribution to display, intellectual property (IP) protection, marketing, audience measurement, and customer service.
By learning to simply recognize complexity when we see it — and learning that we cannot engage with it through reductionism — could save ourselves a lot of pain and allow our efforts to focus on quality, rather than on trying to do the impossible. By seeking to understand complexity instead of hiding it, we can build better-quality software with less stress.
Do not underestimate the pace of evolution of cloud technologies. If no one in the organization watches (and understands) the new cloud delivery technologies, you may choose the wrong one, or you may be misled by a vendor that will fail to mention a better option because the vendor does not offer it.
Many of the principles that were developed for the data warehouse are just as relevant today when considering the evolution to a digital business. Underpinning these principles is the implicit need for the active use and management of a coherent layer of metadata. In discussing the broader digital business, it may help to delineate the various systems and applications that occupy the landscape of such a business.