Gartner’s Top 10 Strategic Technology Trends for 2017

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Well, it looks like the preview I shared last week wasn’t that far off the mark, although some analysis was lacking.  So, without further ado:

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As I’ve noted, the Gartner Symposium is underway this week in Orlando, and David Cearley, VP of Research, has identified what he (and Gartner) believe will be the top ten strategic technologies that have the potential to be significantly disruptive over the next five years.   These break into three themes (intelligent, digital, and mesh) and are just beginning to break out of an emerging state.   Some old ones from previous years are still on the list, some new, expected ones appeared, and then there are a few unexpected surprises.

To quote Cearley “Gartner’s top 10 strategic technology trends for 2017 set the stage for the Intelligent Digital Mesh.  The first three embrace ‘Intelligence Everywhere,’ how data science technologies and approaches are evolving to include advanced machine learning and artificial intelligence allowing the creation of intelligent physical and software-based systems that are programmed to learn and adapt. The next three trends focus on the digital world and how the physical and digital worlds are becoming more intertwined. The last four trends focus on the mesh of platforms and services needed to deliver the intelligent digital mesh.”

Intelligent

Trend No. 1: AI & Advanced Machine Learning

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Well, not really the T-800, however artificial intelligence (AI) and advanced machine learning (ML) are made up of technologies and processes like deep learning and neural networks. What began as algorithms to automate manual tasks, borrowing from advanced statistical techniques, has developed into a broader framework and architecture that learns like a human might, and can use historical data to predict the future.

Applied AI and machine learning (ML), which include technologies such as deep learning, neural networks and natural-language processing, can also encompass more advanced systems that understand, learn, predict, adapt and potentially operate autonomously. Systems can learn and change future behavior, leading to the creation of more intelligent devices and programs.

Examples include eye-gazing technologies in retail stores and sensory data from smartphones that create propensity-to-buy models. Organizations seeking to drive digital innovation with this trend should evaluate a number of business scenarios in which AI and machine learning could drive clear and specific business value and consider experimenting with one or two high-impact scenarios.

Cearley noted, “Applied AI and advanced machine learning give rise to a spectrum of intelligent implementations, including physical devices (robots, autonomous vehicles, consumer electronics) as well as apps and services (virtual personal assistants, smart advisors). These implementations will be delivered as a new class of obviously intelligent apps and things as well as provide embedded intelligence for a wide range of mesh devices and existing software and service solutions.”

Trend No. 2: Intelligent Apps

Intelligent apps, which include technologies like virtual personal assistants (VPAs), have the potential to transform the workplace by making everyday tasks easier (prioritizing emails) and its users more effective (highlighting important content and interactions). Using AI technology, app and service providers will focus on three areas — advanced analytics, AI-powered and increasingly autonomous business processes and AI-powered conversational interfaces.  The virtual personal assistants, or VPNs, will make tasks such as scheduling meetings and managing emails and other messaging much easier. VPNs and virtual customer assistants (which promise to enhance customer service and sales) should transform work and the how firms are staffed.

By 2018, Gartner expects most of the world’s largest 200 companies to exploit intelligent apps and utilize the full toolkit of big data and analytics tools to refine their offers and improve customer experience.

Trend No. 3: Intelligent Things

New intelligent things generally fall into three categories: robots, drones and autonomous vehicles. Like intelligent apps, intelligent things could not exist without AI or ML. As intelligent things evolve and become more popular, they will shift from a stand-alone to a collaborative intelligent things model. However, nontechnical issues such as liability and privacy, along with the complexity of creating highly specialized assistants, will slow embedded intelligence in industrial IoT and other business scenarios.  Intelligent things will leverage AI and ML to interact with humans and surroundings. Prominent examples are self-driving cars, drones, the artifacts that will increasingly make up the smart kitchen and smart home. Gartner predicts that these will increasingly be woven together into a fabric that will enhance our lives.  What the future of interconnected devices will be in the home and our lives has been envisioned for more than a decade and we’re now getting to a point where the technology is catching up to that vision.

Digital

Trend No. 4: Virtual & Augmented Reality

Virtual reality (VR) and augmented reality (AR) transform the way individuals interact with each other and software systems, deriving visual aspects from the digital mesh. For example, VR can be used for training scenarios. AR, which enables a blending of the real and virtual worlds, means businesses can overlay graphics onto real-world objects, such as hidden wires on the image of a wall.  Cearley says, “The landscape of immersive consumer and business content and applications will evolve dramatically through 2021. VR and AR capabilities will merge with the digital mesh to form a more seamless system of devices capable of orchestrating a flow of information that comes to the user as hyper-personalized and relevant apps and services. Integration across multiple mobile, wearable, Internet of Things (IoT) and sensor-rich environments will extend immersive applications beyond isolated and single-person experiences. Rooms and spaces will become active with things, and their connection through the mesh will appear and work in conjunction with immersive virtual worlds.”

Trend No. 5: Digital Twin

Within three to five years, billions of things will be represented by digital twins, a dynamic software model of a physical thing or system. A digital twin operates at the intersection of metadata, condition or state, event data, and analytics. Using data provided by sensors, a digital twin creates a software model that understands its state, responds to changes, improves operations and adds value. Digital twins function as proxies for the combination of skilled individuals (e.g., technicians) and traditional monitoring devices and controls (e.g., pressure gauges). Their proliferation will require a cultural change, as those who understand the maintenance of real-world things must collaborate with data scientists and IT professionals who utilize digital twins.

Cearley predicts that within the next half decade, hundreds of millions of things will have digital twins. They will be used by enterprises to plan for equipment service, to operate factories, to predict when equipment will fail, to improve operational efficiency, and to aid new product development; they will become smart controls and monitoring for the operation to an ever increasing extent.

Trend No. 6: Blockchain

This one isn’t a shock as much press as we’ve seen this past eighteen months.  Blockchain is a type of distributed ledger in which value exchange transactions (in bitcoin or other token) are sequentially grouped into blocks. The “blockchain” term is hyped to include a loosely combined set of technologies and processes that variously spans middleware, database, security, analytics/AI, monetary and identity management concepts. Blockchain and distributed-ledger concepts are gaining traction because they hold the promise of transforming industry operating models in industries such as music distribution, identify verification and title registry. Bitcoin, however, is the only proven blockchain, and the majority of blockchain initiatives are in alpha or beta phases.

Mesh

Trend No. 7: Conversational Systems

Conversational user interfaces (UIs) can range from simple informal, bidirectional conversations such as an answer to “What time is it” to more complex interactions such as collecting oral testimony from crime witnesses to generate a sketch of a suspect. Conversational systems utilize conversational UI, but not necessarily as the exclusive interface, enabling people and machines to use multiple modalities (e.g., sight, sound, tactile, etc.) to communicate across the digital device mesh (e.g., sensors, appliances, IoT systems).  Speaking of, there was a head-to-head between the Google Now Assistant released with the Pixel and iPhone’s Siri.  Apple has a lot of catching up to do.

Trend No. 8: Mesh App and Service Architecture

The intelligent digital mesh will require changes to the architecture, technology and tools used for solutions. The current solution is the mesh app and service architecture (MASA), a multichannel solution architecture that supports multiple users in multiple roles using multiple devices and communicating over multiple networks. These are apps and services architecture that are more loosely connected rather than linear, monolithic designs.  However, true digital businesses will need to come up with a more effective solution due to the MASA’s challenges.

Trend No. 9: Digital Technology Platforms

Digital technology platforms are the building blocks for a digital business and are necessary to break into digital. Every organization will have some mix of five digital technology platforms: Information systems, customer experience, analytics and intelligence, the Internet of Things and business ecosystems. Companies should identify how industry platforms will evolve and plan ways to evolve their platforms to meet the challenges of digital business.

Trend No. 10: Adaptive Security Architecture

The evolution of the intelligent digital mesh and digital technology platforms and application architectures means that security has to become fluid and adaptive, and the combination of the digital mesh with digital technology platforms creates a bigger attack surface for bad actors. Security in the IoT environment is particularly challenging. Security teams need to work with application, solution and enterprise architects to build security into the overall DevOps process to create a DevSecOps model.  As Cearley notes, “the IoT edge is a new frontier for many IT security professionals creating new vulnerability areas and often requiring new remediation tools and processes that must be factored into IoT platform efforts.”

This week’s TED talk involves a wearable bioelectronics monitor that could allow doctors to monitor patients at home with the same degree of accuracy as they’d get during their stay at a hospital, a direct application of several of the technologies outlined by Gartner.

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