Banking and financial services companies were among the first to apply artificial intelligence (AI) in strategic applications. Initially, this took place in the mid- to late 1980s in the form of expert and knowledge-based systems for credit and loan approval and mortgage processing, and so on, and then in the early to mid-1990s, when neural network-based applications for credit and bank card fraud detection, and profitability management, began to be deployed.

Given the risk/reward tradeoff inherent in disruptive technology adoption, this Advisor aims to identify the motives, pressures, and efforts that influence continued adoption intention and usage of a disruptive technology after the initial adoption stage.

An organization is likely to base its digital disruption upon the markets and geographies in which it already operates, and the existing workforce understands the customers and needs of both the current market and the current geographies. It is therefore essential that leaders utilize their existing resource pool by providing employees with the learning and tailored development to facilitate their transition to the digital era.

In this Advisor, Sheila Cox describes how effective delegation requires determining the ability to perform the specific task at hand and using the appropriate leadership style.

Organizations should focus their attention not on integrating, storing, or even analyzing data, but on the effective use of time.

Analytics can be performed at various points in the deployment of a solution. Certainly, there are situations where “localized” analytics may be more appropriate than analytics performed in the cloud, and still others where analytics on the organization’s network might be more appropriate. The location of analytics can also determine where and when to integrate data into the analytical solution.

In this Advisor, we present a sample of core thinking — a set of practices needed to build a Lean/Agile organization — grouped under three different categories: (1) foundational thinking, (2) designing, and (3) redesigning.

With the arrival of private blockchain platforms that integrate nonfunctional requirements arising from typical market conditions (i.e., privacy, confidentiality, controlled access), the barriers to creation of a digital economy become less significant and easier to overcome.

This Advisor describes several EA techniques in an IoT context.

Agile-at-scale relates to scaling Agile methods for software development use enterprise-wide or on large software development efforts. Scaling has been key as organizations try to tap the benefits of Agile methods to deliver their software products quicker, more cheaply, and with higher quality.

In this Advisor, I describe some important AI developments we are seeing with the IoT.

The Internet offered wide access, and the smartphone offered direct and personalized access to the insurance customer. What can AI offer?

Can the same path to Agile transformation work for every organization? Does every organization need to go through the same number of steps? Do the organization’s culture, technological landscape, and customer needs necessitate a customized model of such a transformation? In this Advisor, we identify the five elements of design thinking as key principles that every Agile transformation should follow.

We have developed a simple yet powerful framework to help business leaders navigate the digital landscape based on four business-focused questions that are at the core of effective governance of digital. We call these questions the four “ares.” In our previous Advisor, we discussed the first two of the “ares”: Are we doing the right things? and Are we doing them the right way? This Advisor explores the two that remain.

When we discuss the concept of “a culture transformed,” we can draw many parallels against the way a society votes and spends, but that’s out of scope. What is not out of reach is your influence over your teams and whether you can embrace the change that is upon us all. It’s up to you to set the tone of the conversation within the organization.

In this Advisor, we examine how fog architecture addresses cybersecurity for next-generation networks.

In this Advisor, I introduce an Agile development framework (ADF); not a mainstream Agile offering like Scrum, but rather something I tend to carry around in my head when trying to think about the various views, products, roles, and tasks that a multidisciplined team can bring to bear for different types of Agile projects.

Customer expectations are shaped by their interactions with Uber, Amazon, and Apple — where each interaction is intuitive, easy, and instant. In customers’ eyes, the age, size, and complexity of the organization or industry are all irrelevant: all they care about is having a great experience. Traditional organizations have no choice but to step up their game to stay relevant.

Your business architecture knowledgebase should include content for each business architecture domain that you have determined to be applicable for your organization (most or all usually apply). The content for each domain includes names, attributes, and relationships to business architecture domains as well as other domains (e.g., system applications). The knowledgebase can be created and refined over time.

Artificial intelligence (AI) has reached the point where most major organizations are now investing in the technology. But, a key question I have had for some time now is: to what extent are organizations deriving measurable benefits from the AI applications they have deployed? Fortunately, the latest results from our ongoing survey examining the adoption and application of AI technology in the enterprise offer some insight into this question.

In this Advisor, I highlight the need to understand the optimal granularity level in analytics to maximize business value. I also point to the need for business owners and strategists to incorporate context in analytics in a balanced manner in ascertaining the granularity levels. Granularity levels can vary dynamically depending on the needs of the business. Due consideration to such dynamicity ensures that time, cost, and corresponding use of resourcing in undertaking analytics are all utilized to provide maximum value to the business.

APIs are bringing about new opportunities by creating new channels for partnerships, promoting brands, and experimenting with customer-influenced innovative solutions and alternate business models. In this Advisor, I explore the spectrum of APIs. Knowing the spectrum of APIs and how they work helps formulate and guide API and software strategy, aids in decision making on interfacing architecture, and helps assess readiness from business, technical, compliance, and risk perspectives.

Traditional analytics is generally restricted to merely providing a better understanding of historical data or predicting future business outcomes. Consequently, the potential of traditional analytical processes is limited as they only offer insights and patterns based on data provided but they lack the ability to offer or make business recommendations. Prescriptive analytics, however, is substantially different and more powerful because it allows businesses to not only make predictions but also suggests an optimal solution.

This Advisor considers the impact of the Internet of Things (IoT) on traditional business and technology architectures and introduces the role of EA as an effective methodology for developing and implementing IoT strategies. 

Actions, words, and intent should echo and support the foundation of your principles. Guided by your moral compass, work to establish an IT organizational culture based on what’s important to your customers and to you. In leading your IT service and support organization, establish trust and confidence in your service delivery with your business customers.