Top 10 Strategic Technology Trends for 2017

Boreless · 2016-12-13T20:50:42+00:00

Published: 14 October 2016 ID: G00317560 Analyst(s): David W. Cearley | Mike J. Walker | Brian Burke Order Reprints You may request paper or digital reprints on the ensuing order form. Summary Gartner's top 10 trends will drive the future of the intelligent digital mesh. Enterprise architecture and technology innovation leaders must prepare for the impacts of these disruptive trends on people, businesses and IT departments, and determine how they can provide competitive advantage. Overview Key Findings An intelligent digital mesh is emerging to support the future of digital business and its underlying technology platforms and IT practices. The mesh focuses on people and the Internet of Things (IoT) endpoints, as well as the information and services that these endpoints access. Capabilities such as blockchains, distributed ledgers and digital twins will bring the physical and digital realms ever closer to supporting digital business initiatives. Artificial intelligence (AI) and machine learning are the means of injecting intelligence into new and existing apps and things to form the intelligent digital mesh. Relentless and ever-increasing security attacks require adaptive security architectures that emphasize security-aware solution design; AI-enabled user and entity behavior analytics; and new architecture, methods and tools to address IoT and intelligent digital mesh security. Recommendations Enterprise architecture and technology innovation leaders using enterprise architecture to master emerging and strategic trends must: Plan for a radical, long-term (2020 to 2025) evolution of the user experience for both customers and employees as conversational systems, augmented reality (AR), virtual reality (VR) and continuous/contextual user experiences radically change the way people interact with systems. Explore opportunities to create new systems that require AI and machine learning, and showcase their intelligent feature systems (such as virtual personal assistants [VPAs], robots and autonomous vehicles), and augment existing apps and things (for example, customer service, enterprise applications, consumer electronics and medical devices). Examine specific, targeted and high-value use cases to apply AR/VR, build digital twins to support IoT initiatives, and embrace blockchains and distributed ledgers in 2017 to 2019. Build a security mindset into application design and operations, while augmenting preventive controls and security monitoring with user and entity behavior analytics. Table of Contents Analysis Trend No. 1: Artificial Intelligence and Advanced Machine Learning Trend No. 2: Intelligent Apps Trend No. 3: Intelligent Things Trend No. 4: Virtual Reality and Augmented Reality Trend No. 5: Digital Twins Trend No. 6: Blockchains and Distributed Ledgers Trend No. 7: Conversational Systems Trend No. 8: Mesh App and Service Architecture Trend No. 9: Digital Technology Platforms Trend No. 10: Adaptive Security Architecture Gartner Recommended Reading Figures Figure 1. Top 10 Strategic Technology Trends for 2017 Figure 2. The Characteristics of Smart Machines Figure 3. Artificial Intelligence and Machine Learning Will Have Obvious and Inconspicuous Uses Figure 4. Forecast for Sales of Head-Mounted Displays, 2015-2020 Figure 5. Digital-Twin Models Are Digital-Entity Models for Assets Figure 6. Key Elements of Blockchains and Distributed Ledgers Figure 7. Conversational Systems Include New User Experience Design Elements Figure 8. The Shift to a Central Role for Event Processing in Digital Business Figure 9. Abstract System Model for Conversational Artificial Intelligence Platform Figure 10. User and Entity Behavior Analytics "Cool Vendors in Smart Machines, 2016" "Hype Cycle for Smart Machines, 2016" "Cool Vendors in Data Science, 2016" "Machine Learning Drives Digital Business" "Smart Machines See Major Breakthroughs After Decades of Failure" "Smart Machines Primer for 2016" [paste:font size="4"]"Hype Cycle for Smart Machines, 2016" ). By 2018, we expect that most of the world's largest 200 companies will exploit intelligent apps and use the full toolkit of big data and analytical tools to refine their offerings and improve their customer experience. Discover the many different types of intelligent apps that could be created with a focus on specialization and purpose. Customers may use one or a combination of intelligent apps. For example, customers may use an intelligent app to: Help with health (diet, exercise or psychological well-being) Act as a personal shopping assistant Act as a financial advisor Help with office-specific tasks, such as calendar management, email handling and external information monitoring Intelligent apps constitute a long-term trend that will evolve and expand the use of AI and machine learning in apps and services during the next 20 years. Establish a process to continually evaluate where your organization can apply AI today and over time. Use persona-based analysis to determine the opportunities. Compare the roadmaps for AI exploitation across your packaged app and service provider portfolio. Proceed with caution if your organization is developing applications — the underlying AI and machine-learning elements for creating intelligent apps are not ready for most application development projects at scale. Ensure such projects have a very high potential business value. Note that the competitive gaps and missed opportunity costs for laggards could be significant. Related research: "Gartner's 2016 Hype Cycles Highlight Digital Business Ecosystems" "Smart Machines Will Be the Catalyst for One of the Most Disruptive Eras in Retail" "Competitive Landscape: Virtual Personal Assistants, 2016" "IT Strategists Must Prepare for the Rise of Virtual Personal Assistants in the Workplace" "Smart Agents Will Drive the Switch From Technology-Literate People, to People-Literate Technology" "Hype Cycle for Emerging Technologies, 2016" "Using Algorithmic Retailing to Drive Competitive Advantage" [paste:font size="4"]1 while the military is studying the use of drone swarms to attack or defend military targets. 2 In the delivery market, the most effective solution may be to use an autonomous vehicle to move packages to the target area. Robots and drones on board the vehicle could then effect final delivery of the package. Challenge the status quo on robotics. Create business scenarios and business outcome journey maps to identify and explore the opportunities that will fulfill your organization's strategic plans. Seek opportunities to incorporate the use of emerging intelligent things in traditional manual and semiautomated tasks. For example, examine how distribution models shift as drones become safer and more effective, helping to enhance overall business performance. Expect the indirect impacts to be just as great as the direct impacts. Industry trends, such as autonomous vehicles, usher in new business designs. These require you to create proactive and predictive risk models that provide a clear view of how your organization will create value in digital ecosystems. Related research: "Toolkit: How to Create Business Scenarios That Drive Digital Disruption Innovation" "Volvo, Autoliv Create Unique Approach for Autonomous Vehicle Software" "Ford Autonomous Vehicle Plan Targets Mobility as a Service" "Your IoT Future Is Visible in the Mining Industry Today" "Market Trends: Personal Assistant Robots for the Home" "The P&C Insurance Industry Nears a Tipping Point on Drones" [paste:font size="4"]VisualSpection provides VR headgear that allows inspection teams in the field to improve efficiency by 30%. AR, which vendors are also marketing as mixed reality, is the best way to blend the real and virtual worlds. Using see-through displays, an AR device can track and overlay graphics onto real-world objects. Business provides the first use cases. They include DHL's use of wearables and AR in a warehouse toachieve a 25% improvement in the picking process. 3 Our research has found that 11% of organizations are already using AR, and 13% are piloting it. 4 The landscape of immersive consumer and business content and applications will evolve dramatically through 2021. The market for HMDs will grow and evolve significantly in 2017 and 2018. Figure 4 shows our forecast for sales of HMDs through 2020. In the near term, consumers will rapidly adopt HMDs, with video games being the first popular HMD app type. More-specialized HMDs, and VR and AR content solutions, will become available for businesses. Through 2021, HMD technology will improve drastically. "Market Guide for Augmented Reality" "Forecast Snapshot: Wearable Gesture Devices, Worldwide, 2016 Update" "Top 10 Wearable Technologies and Capabilities in 2017 and 2018" "Virtual Reality: What Marketers Need to Know Now" "What's Hot in Digital Commerce Marketing, 2016" "The First Three Steps in Evaluating the Role of Head-Mounted Displays for Field Service" [paste:font size="4"]"Use the IoT Platform Reference Model to Plan Your IoT Business Solutions" "Digital Business Is Transforming New Product Development Priorities" "Reframing Your Mindset to Match Digital-Era Reality" "Hype Cycle for the Internet of Things, 2016" "Envision the IoT-Enabled R&D Digital Laboratory of the Future" "Market Guide: MPM and MbM Software Enable Digital Manufacturing" "Industry Vision: Life Science R&D as a Digital Innovation Orchestration Engine" [paste:font size="4"]5 Although the hype surrounding blockchains concerns their use in the financial services industry, they have many potential applications beyond financial services, including music distribution, identity verification, title registry and supply chain. Smart contracts enabled by blockchain technology will drive the programmable economy. It is likely that blockchain technology will evolve and be rapidly accepted by the manufacturing, government, healthcare and education sectors. Today, bitcoin is the only proven blockchain. Its permissionless architecture not only supports bitcoin transactions, but also enables authoritative recording of events, immutable snippets of data and simple programmable scripts. These features are exciting, but come at a cost, including: Lack of scalability Lack of complete transparency Limitations concerning consumption of resources Operational risk from unintended centralization of resources (mining) Lack of alignment to, and accommodation of, existing legal and accounting frameworks Other blockchain technologies bring further adoption challenges, including a lack of: Standards Robust platforms Scalable distributed consensus systems Interoperability mechanisms There are three types of ledgers: Permissionless public ledgers: Operate for any (unknown/untrusted) user. Users can access the ledger and contribute transactions or new sets of data. Examples: The bitcoin blockchain or Ethereum. Permissioned private ledgers: Operate exclusively within a defined community of known/trusted participants, such as financial institutions and government agencies. The community (or designated authority) controls access and contribution to the ledger. Examples: Chain, Bankchain, SETL and Domus Tower. Permissioned public ledgers: Operate on behalf of a community of interest. The access controls are owned/managed by rules. Example: Ripple. A critical aspect of blockchain technology today is the unregulated, ungoverned creation and transfer of funds, exemplified by bitcoin. It is this capability that funds much of blockchain development, but also concerns regulators and governments. The debates about permissioned, permissionless, hybrid and private ecosystems and governance will force a more-robust analysis of distributed ledgers. As these analyses are completed, workable solutions will evolve. Blockchains and distributed ledgers make transactions simpler. Using a public blockchain can potentially remove the need for central authorities in arbitrating transactions. This is because trust is built into the model through immutable records on a distributed ledger. The potential of this technology to radically transform economic interactions should raise critical questions for society, governments and enterprises, for which there are no clear answers today. Begin evaluating blockchains and distributed ledgers, even if you don't aggressively adopt the technologies in the next few years. Most distributed-ledger initiatives are still in the early alpha or beta testing stage. Recent versions incorporate assets, data and executable programs allowing for customized applications. These ecosystems have value, but concerns remain about, for example, the viability of the technologies, startups, security (software and hardware), scalability, legality and interoperability. It is likely that development will continue in parallel for the immediate future, and it is probable that two or more ledger models will operate together. Develop clear language and definitions for internal discussions about the nature of the technology. Recognize that the terminology surrounding blockchains is in flux. This uncertainty masks the potential suitability of technology solutions to meet business use cases. Consequently, use extreme caution when interacting with vendors that have ill-defined/nonexistent blockchain offerings. Ensure you are clearly identifying how the term "blockchain" is being used and applied, both internally and by providers. Closely monitor distributed-ledger developments, including related initiatives, such as consensus mechanism development, sidechains and blockchains. Resources permitting, consider distributed ledger as proof-of-concept development. But, before embarking on a distributed-ledger project, ensure your team has the cryptographic skills to understand what is and isn't possible. Identify the integration points with existing infrastructures to determine the necessary future investments, and monitor the platform evolution and maturation. Related research: "Hype Cycle for Blockchain Technologies and the Programmable Economy, 2016" "Experiment With Blockchains for Data Management Innovation" "The Bitcoin Blockchain: The Magic and the Myths" "Innovation Insight for Blockchain Security" "Toolkit: Overview of Blockchain Use Cases" "What Insurance CIOs Need to Know About Blockchain" "How to Evolve Your Trade Finance Strategy With Smart Assets and Blockchain" [paste:font size="4"]"Smart Agents Will Drive the Switch From Technology-Literate People, to People-Literate Technology" "Hype Cycle for Human-Machine Interface, 2016" "How User Experience Can Make or Break Your Customer Experience" "Conversational AI to Shake Up Your Technical and Business Worlds" "Forecast Snapshot: VPA-Enabled Wireless Speakers, Worldwide, 2016" "Smartphones, Tablets and Things — It's Time to Integrate Your Mobile and IoT Strategies" [paste:font size="4"]"Mediated APIs: An Essential Application Architecture for Digital Business" "Articulating the Business Value of APIs" "Assessing Microservices for Cloud-Native Application Architecture and Delivery" "Orchestrating Docker Container-Based Cloud and Microservices Applications" "Use Agile and DevOps to Implement Lean IT and Improve Software Delivery" "CTO Alert: Master Event-Driven IT to Master Digital Business" "Add Event-Stream Processing to Your Business Analytics Repertoire" [paste:font size="4"]"IoT Communications Architecture Demystified" ). The CAP's NLP capabilities provide an abstraction that can potentially ease cross-protocol communication issues. The CAP's AI capabilities enable it to learn from data ingested from individual objects over time. This provides more value to the overall IoT system and can accelerate digital-twin efforts. Similarly, the CAP benefits from the IoT platform in several ways. The IoT platform provides the underlying infrastructure that facilitates communication and action among users, objects and applications. The IoT platform enables the CAP to reach out not only to apps, but also to individual objects and systems (and their associated data and analytics). The IoT provides data from more sources (input), as well as potential actions that affect the physical world (output). This allows for a richer CAP experience for the user, with more opportunities for automation and efficiency. Technology providers are already starting to experiment with the symbiotic relationship between the CAP and IoT-related platform services. In its August 2016 update, Microsoft's Skype division added the "If This Then That" (IFTTT) bot to its bot directory. 6 It can interact with more than 50 different types of IoT devices, ranging from cars to wearables to connected home devices. Related research: "Building a Digital Business Technology Platform" "The Platform Architect's Guide to Designing IoT Solutions" "Market Guide for IoT Platforms" "Cool Vendors in the Internet of Things, 2016" "Use the IoT Platform Reference Model to Plan Your IoT Business Solutions" "Conversational AI to Shake Up Your Technical and Business Worlds" [paste:font size="4"]7 design considerations must include levels of isolation between solution components. Different levels of security must be applied based on the risk exposure of different systems. Digital twins consolidate massive amounts of information on individual assets and groups of assets, often providing control of those assets. As the digital-twin trend evolves, twins will communicate with one another to create "digital factory" models of multiple linked digital twins. Digital twins of assets will be linked to other digital entities for people (digital personas), processes (law enforcement) and spaces (digital cities). Understanding the links across these digital entities, isolating elements where needed and tracking interactions will be vital to support a secure digital environment. A number of factors can help secure the IoT environment. Ensure that device hardware and software are resistant to attacks and are secure (for example, by implementing secure software updates). Secure all access and communication channels with appropriate access control, authentication or encryption, and closely monitor API access to systems, particularly where these APIs are intentionally opened for outside entities. Use established security technologies as a baseline to secure IoT platforms. Monitor user and entity behavior, particularly in IoT scenarios. Implement sufficient security monitoring and management practices for edge devices, including secure updates. However, the IoT edge is a new frontier for many IT security professionals, creating new vulnerability areas. It often requires new remediation tools and processes that must be factored into IoT platform efforts. Related research: "The Fast-Evolving State of Security Analytics, 2016" "CISOs Need to Understand the Components of Their Information Security Programs" "Market Guide for User and Entity Behavior Analytics" "Best Practices and Success Stories for User Behavior Analytics" "Hype Cycle for Application Security, 2016" "A Primer for Building Resilience and Security Into Internet of Things Solution Architecture" "DevSecOps: How to Seamlessly Integrate Security Into DevOps" [paste:font size="5"]"Smart Agents Will Drive the Switch From Technology-Literate People, to People-Literate Technology" "Hype Cycle for the Internet of Things, 2016" "Hype Cycle for Application Architecture, 2016" "Five Steps for Event-Triggered Multichannel Marketing" [paste:font size="5"]Evidence "Drones Autonomously Build a Walkable Rope Bridge," New Atlas, 22 September 2015. "How Swarming Drones Could Change the Face of Air Warfare," DefenseNews, 17 May 2016. "DHL Successfully Tests Augmented Reality Application in Warehouse," DHL, 26 January 2015. "Microsoft Introduces New Bots Into the Skype Bot Directory," MSPoweruser, 3 August 2016. "The Jeep Hackers Are Back to Prove Car Hacking Can Get Much Worse," Wired, 1 August 2016.

Thread starter Boreless
Start date Dec 13, 2016

Boreless

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