As you think of the possibilities for using AI to redesign auto business processes, remember this about today’s AI systems: they use techniques that analyze large amounts of data, looking for patterns. With new techniques, they can increase the data available for use, but they need data to gain experience.

Governments are starting to embrace the possibility of creating their own cryptocurrencies.

As a second-order effect of the Internet, digital transformation can be broken down across the three major areas that it will transform: customer experience, operational processes, and business models. Although transforming the customer experience is the most visible manifestation of digital transformation, as I discuss in this Advisor, transforming internal processes through digitization, worker enablement, and performance management can also show great benefits.

Both the explosive growth of Agile adoption and the return to collaborative and experiential learning are part of a larger global transformation whereby people are seeking to cast off authority in exchange for autonomy and peer collaboration.

There is an ingrained optimistic spirit infusing the enterprise, creating a bias toward action, toward change, toward better things. And, a resulting need for speed: speed to market, shorter cycles, quicker turnaround, and more throughput. Faster, faster, faster! More Agile. But speed kills. Even avid practitioners of Agile — if we pay attention to some of the current conversations — are generally of the view that Agile is not merely about speed, and that breakneck speed can break necks and more, if “Agile” is simply an excuse to hurtle mindlessly into space.

Volume, value, and velocity are all essential in digital transformation. This Advisor looks at this V-cube service delivery model.

This Advisor discusses the risks and challenges of implementing prescriptive analytics in the context of machine learning.

In many market sectors, the journey to become more Agile is a strategic imperative. This Advisor looks at some of the reasons some organizations find this transition difficult. These challenges point to the practices, processes, and cultures of the past as potential hurdles.

When successfully deployed and business value-focused, a business architecture practice is a critical enabler for digital transformation.

How do end-user organizations feel about the potential for AI to disrupt their particular industries and lines of business? An ongoing Cutter Consortium survey that asked 62 organizations about their efforts to adopt and apply AI technology helps provide some insight into this question.

Passenger experience has been at the center of the airport’s evolution as an ecosystem driver and will continue to be so as digital technologies drive changes in the near future. The key is to enable happy passengers by providing a great experience throughout the passenger journey and, in turn, exploit the positive correlation between passenger happiness and spend per passenger. The focus for airports will be on providing a seamless passenger experience at two key stages of travel: pre-departure and post-arrival.

Entrepreneurial organizations typically have severely limited resources and many last only briefly; consequently, their ability and opportunity to implement knowledge management (KM) practices before suffering the consequences of “knowledge mismanagement” are limited. In fact, one might say that the flat managerial structure and agile business processes characteristic of entrepreneurship are in direct opposition to the somewhat time-consuming and structured processes traditionally associated with KM.

The three challenges described in this Advisor represent those that Agile teams face when attempting to follow enterprise architecture (EA)-level planning and design documents as well as the issues faced by Agile teams when transitioning their products to the operations team.

IT portfolio management is the continuous process of selecting and managing the optimum set of project-oriented initiatives to deliver maximum business value.

By putting the science of numbers, data, and analytical discovery to work we can find out if our assumptions about what is contained in the data are only opinion or truly fact.

Systems design has two perspectives: (1) blackbox (the encapsulated system is seen as a whole from the outside; the blackbox view is how the system performs when interacting with its context) and (2) whitebox (the system is seen as a set of interacting parts that collaborate to produce the blackbox behavior).

As the population of Southeast Asia grows exponentially, so does the reliance on smartphones and the Internet. This expansion of ecommerce is proving irresistible to the major technology players, which are jockeying for position at the top. This leaves little room for smaller players in banking, retail, transportation, and other services. Enterprises from Southeast Asia need to catch up with technological advancements and plan for the future as digitization becomes a top priority.

In this Advisor, I introduce the Agile Leadership Canvas, a rubric for guiding the Agile transformation conversation.

By implementing a service platform, our case study company combined complementary capabilities and resources from its existing business with insurtech capabilities — an essential part of the digitization of the insurance company.

As we do each year, we asked Cutter’s team of experts to weigh in on some of the technologies, trends, and strategies that will truly make waves in the months to come. We hope the articles in this issue of Cutter Business Technology Journal help clarify your organization’s path forward in today’s digital economy.

AI, in all its various forms — machine learning (ML), natural language processing (NLP), speech recognition, cognitive systems, intelligent agents, chatbots, and robotics — is generating intense interest across every industry. In effect, AI has sparked what can only be described as an explosion in technological innovation worldwide — innovation that is going to accelerate throughout the foreseeable future.

Endowing the old change management frameworks with the additional dimensions of technology and innovation could help change a company’s course. Along with process, people, leadership, and business, a new-age digital change management framework (DCMF) should emphasize developments in technology and innovation as well.

Practical application of big data requires a pathway that shows the activities and threads (or lanes) for actual implementation. The Big Data Framework for Agile Business (BDFAB) contains roles, deliverables, and business parameters that provide a sound basis for big data adoption.

Big data is not going anywhere soon. In the next few years, businesses of all sizes will be using some form of data analytics to make business decisions. More­over, as the Internet of Things (IoT) becomes more widespread, high-speed data processing, analytics, and reduced response times will be deemed more critical than ever. Meeting these requirements through the current centralized, cloud-based model faces a multitude of challenges. This is where fog computing can enhance and complement the cloud.

What we often regard as intractable problems are also ripe for disruption. While intractability is its own momentum, it’s also an invitation to change.