Technology seems to be moving at the speed of light these days, so we decided to ask Cutter’s team of experts for their insights on some of the technologies and trends that are going to be game changers in 2016 and beyond. In true Cutter IT Journal fashion, our call produced a wide range of opinions on what everyone from C-suite executives to technology managers should plan for as they strive to meet their business and technology goals.

Organizations developing Internet of Things (IoT) connected solutions face a number of considerations, including decisions about which wireless and network protocols to use, device connectivity issues, messaging protocols, security, scalability, and data storage and analysis requirements.

A new pilot application developed by US retailer Sears to help customers find and compare tires offers a good example of the types of natural language processing (NLP)–powered customer engagement and customer experience applications we are seeing.

In the difficult global competition today and ahead of us, finding solace in victimhood serves no one. As in the past and in the future, events will be dictated by teams of people believing all things are possible. Setting big goals, establishing metrics, and monitoring performance become important, but the most important metric will be counting the myriad of small successes found in daily challenges and the continual pursuit of even more complex ones. Is your organization so brave as to measure something this mundane?

When a company adopts new ways of working and embeds them throughout the organization, it is imperative that all new employees, in addition to having the skills necessary to do the work, are also either already practicing the company's ways of working or are very willing to embrace them. Without this, the company runs the risk of diluting its Agile "gene pool." All change initiatives are fragile, and introducing additional critical or dissenting opinions can upset the balance and be detrimental to the change effort.

I’ve been an enterprise architect since 1984, and the main thrust for EA over all those years has been about giving direction to architectural evolution.

In looking at some of the key trends and developments affecting the market for, and the application of, data management and analytics that organizations should track in 2016, the Internet of Things (IoT) promises to be exceedingly disruptive to almost every industry. It’s a given that companies must consider how they can take advantage of connected products and services and plan for the significantly increased data workloads that will come with deployment of sensor-enabled products.

Business continues to change under the increasing impact of IT and globalization. In today's world, cloud computing makes it possible for a small company to access the resources such as accounting and management tools just like those used by larger companies at a relatively small price. Outsourcing makes it possible to create a business from an assembly of services, with innovation itself often outsourced. Crowdfunding is creating specialty startups outside the normal bounds of investment, and enormous growth in mergers is making acquisition a critical and routine source of new business ideas.

Traditional technology adoption models describe a process that’s phased and driven by validated requirements analyses. These traditional models have defined the technology adoption process for decades. Emerging hardware, software, and networking technologies like the Internet of Things (IOT), automated reasoning, cashless payment systems, real-time analytics, augmented/virtual reality, 3D printing, and always-on tablets are changing the way business operates.

It's one thing to espouse the virtues of Agile by giving examples of young organizations such as Amazon, Netflix, Spotify, and others that are built on new architectures and tools. It's entirely another scenario when speaking to older enterprises that must manage significant technical debt, as well as business and technical architectural complexities and interdependencies, often with strict regulatory requirements, across simultaneous legacy and cloud projects. All this adds up to an environment fraught with fragility and risk.

For the IoT to be successful, it is essential that connected devices provide a friendly user experience. This is especially important when it comes to consumer products for such market segments as smart homes, health and fitness, connected cars, and gaming. But I think it also holds true — although to a lesser degree — for the wider deployment of connected equipment and smart machines in business environments. Simply put, consumers and businesses will resist using devices, appliances, and equipment that are too difficult to set up or too confusing to operate. Consequently, for many IoT scenarios, we can expect to see connected devices increasingly utilize voice- or speech-powered interfaces that offer hands-free operation for the user. However, voice and speech will not replace other forms of UIs like touch and gesture; certainly not any time soon. Rather, they will be combined with these technologies to provide multi-modal interfaces designed to optimize interaction with connected devices.

API is among the current IT buzzwords (or, should we say, buzz acronyms?). You can spot such hot acronyms from time to time because they are on everyone’s lips, and everyone appears to know what they stand for so there’s no point in explaining them. Yet it’s sort of like running into an old friend — someone you know you know — and carrying on a casual conversation while you try to figure out who in the world that person is, where you’ve met, and what that person’s name is.

The Internet of Things (IoT) promises to cause disruption in almost every industry. Companies need to examine how they can take advantage of connected products and services and plan for the significantly increased data workloads that will likely come with the deployment of sensor-enabled products. However, an expected surge in product innovation also means that companies should carefully consider how they will deal with the potential rise of new, more agile competitors whose business models will be based primarily on IoT products and services. Here are some points about the IoT I've been discussing with colleagues that organizations may want to consider as we head into 2016 and beyond.

Today we are witnessing a new round of interest in AI and knowledge-based computing that is currently being called cognitive computing. This new round of commercial AI is based on the hugely more powerful computing platforms we have available today. Moreover, it is based on new AI techniques — with the emphasis on neural networks rather than business rules. Business rules provided the basis of some great expert systems, but they didn’t provide a basis for software systems that could learn and adapt — and neural networks do provide these advantages.

IT service leaders are under constant pressure to deliver reliable and available services within the budgetary constraints of the business. They look for opportunities to optimize their support model, extracting repetitive, nonvalued inefficiencies and effort that inflate support costs. The shift-left service strategy focuses on moving issue resolution and request fulfillment to the lowest cost level in the tiered-model service organization, with a focus on "one and done" — providing the internal customer with resolution at the service desk (Level 1) or self-service portal (Level 0).

Enterprises and organizations are hybrid "sociotechnical" systems of people, along with the things made by people. They consist of complex collections of physical things, software things, and the mental states of human minds.

It is interesting to explore some ideas from knowledge management (KM) on how people and organizations respond when faced with new knowledge or ideas. Studies that look at how innovations diffuse within an enterprise suggest that the process follows four simple steps. Here are a couple KM ideas to help gauge progress along these four steps.

The most important development I see taking place in 2016 (and beyond) concerning analytics and decision support is the growing commercialization of cognitive systems. Cognitive systems are now having an impact on the consumer and the enterprise worlds by changing the way data is analyzed, and the way that people interact with computers.

A train is only as good as its fastest carriage. Agile can claim to have increased the speed and quality of solutions development through the Agile Manifesto, the Agile principles, and the many popular Agile practices (e.g., user stories, daily standups, and the wall). However, an important discovery by many of us in practice is that faster and higher-quality development in itself is not enough. In fact, faster time to development can lead to problems.

While theoretical discussions of decisions involving IT-related ethics are interesting, this past year highlighted the real effects of ignoring IT ethics in business decisions.

The prevalence of smartphones and other mobile devices is dramatically transforming how healthcare is delivered to consumers and how medicine is practiced in general. Consumers are increasingly using their mobile devices to arrange for a healthcare professional to come to their home, or to engage in a virtual doctor visit via real-time video consultation. Healthcare practitioners are employing mobile devices to assist them with various practices, ranging from collaborating with colleagues to remotely monitoring patients.

I have seen — and am sure that many of you have, as well — architecture cartoons, cost-benefit numbers, and trade-off-matrices that look pretty but lack the integrity that we need from these artifacts. This is not to say that these representations do not hold potential. They do, if we are able to tease out the signal from the noise, and if we are able to bring out the nuances related to where on the fact-to-fiction spectrum a particular data point lies.

Emerging technologies continue to challenge IT as the pace of innovation and introduction of disruptive new platforms continues to accelerate. We are on the verge of huge changes across every area of technology and society. Dominant themes include mobility, interconnection, agility, and global participation. The technologies that support these trends involve Cloud computing, artificial intelligence, big data, the Internet of Things (IoT), mobility, modularization, Internet connectivity, and the digitization of everything.

As has been our tradition for the last several years, we've compiled the most intriguing articles published by the Agile Product Management & Software Engineering Excellence practice this year for today's Advisor. How did we come up with this list? We chose the articles that garnered the most feedback from Cutter Members and clients and those that created controversy among Cutter Senior Consultants and Fellows.

As has been our tradition for the last several years, we've compiled the five most intriguing articles published by the Business Technology & Digital Transformation Strategies practice this year for today's Advisor. How did we come up with this list? We chose the articles that garnered the most feedback from Cutter Members and clients and those that created controversy among Cutter Senior Consultants and Fellows.