In this issue, we examine some of these questions along with the drivers of AI global trends and their impli­cations — now and in the future. Our contributing authors provide insights on key opportunities, strategies, and approaches for realizing AI’s potential and discuss emerging issues and concerns, including how AI may impact jobs and businesses.

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.

“The purpose of a system is what it does” — referring to “system” as the company as a whole — means that a company’s statements of intent (“we are an innovative, digital native company”), or even its market analysis or the initiatives it has undertaken, are secondary to what a company actually does.

The industry is ripe for transformation in areas including customer service and marketing, claims management and fraud detection, and underwriting.

This Advisor explores one approach that has been particularly effective in making enterprise architects understand the realities of organizational change in their own context.

Digital transformation is commonplace in today’s economy. Digital transformation leaders and enterprise architects have a choice to make in developing their digital backbone. The digital backbone can be an asset in ensuring that digital transformation efforts are carried out in such a way that they are in align­ment with the enterprise and its approach to transformation. 

A strategic approach around big data not only includes the multiple analytical, architectural, project, and technical elements in a synergistic manner, but also pays due attention to the financial and people aspects, resulting in business value.

In this Advisor, we consider what leaders are expected to do within Agile organizations, then see how these duties translate to a set of desired skills and personality traits.

The existence of a digital backbone in an organization means that anyone aspiring and planning to transform different parts of the enterprise will be able to leverage the digital backbone in a consistent and sustainable way, ensuring that each effort connects to and leverages a common platform. 

Even radical approaches to change management, such as business process engineering or Lean, assume there is a desirable endpoint (however temporary) toward which change is directed. However, what if change happens so continuously that no fixed endpoint exists for any initiative, but instead organizations must constantly change, not just to succeed, but even to survive?

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.