根據Gartner的定義，策略性技術趨勢（Strategic Technology Trends）指的是可能對企業或組織帶來重大影響的技術趨勢。重大影響因素涵蓋：（1）可能對業務、終端使用者或IT層面造成顛覆性效果；（2）需要大舉投入資金；（3）太晚採用相關技術便會導致風險。此外，策略性技術也將影響企業或組織的長期規劃、方案與行動方案。

近日（2015年10月4日）再次公布2016年十大策略性技術趨勢分析（Top 10 Strategic Technology Trends for 2016），共計三類十項策略性技術，如圖一所示， 2016年十大策略性技術趨勢分析共分為三類，包括數位網格(Digital Mesh)、智能設備(Smart Machines) 與新IT環境(New IT Reality)，十項策略性技術進一步說明如下[1-3]。

圖一、Gartner 2016年十大策略性技術趨勢

1.裝置網格(Device Mesh)
裝置網格指的是為數越來越多、用來存取應用程式與資訊或與其他人、社群、政府及企業互動的端點裝置。裝置網格包含行動裝置、穿戴式產品、消費性與家用電子裝置、自動裝置與環境裝置──例如物聯網(IoT)當中的感測器。

雖然有越來越多裝置透過各種網路連結後端系統，但往往是各自獨立運作。隨著裝置網格逐漸演進，Gartner認為連網模式將會擴大，裝置之間的合作性互動也將更上一層樓。

2. 環境使用體驗 (Ambient User Experience)
裝置網格將為持續不斷的新形態環境使用體驗(Ambient User Experience)提供基礎。具備擴充實境與虛擬實境功能的沉浸式環境握有極大商機，但其實只是體驗的其中一個面向而已。

環境使用體驗能跨越裝置網格、時間與空間的界線而保有延續性。這樣的體驗可在各式各樣的裝置與互動管道之間無縫流動，當使用者移動時也能混合實體、虛擬以及電子環境。

3. 3D列印材料( 3D Printing Materials)
3D列印技術不斷提升，已經可以利用鎳合金、碳纖維、玻璃、導電油墨、電子、藥品與生物材料等各式各樣的材料。這些創新技術持續帶動使用者需求，同時3D印表機的實際用途也拓展到更多產業，包括航太、醫療、汽車、能源與軍事。

適用於3D列印的材料種類越來越多，Gartner預計2019年以前將帶動企業用3D印表機出貨量達成64.1%的年複合成長率。在這樣的進展之下，必須重新構思組裝與供應鏈流程，才能善加利用3D列印技術。

4. 萬物聯網資訊(Information of Everything)
數位網格裡面的所有物件都能製造、利用並傳輸資訊。這樣的資訊不限於文字、語音或影像格式，範圍涵蓋感測與情境資訊。萬物聯網資訊可解決這種策略與技術的匯入，連結來源各異的各種資訊。

資訊其實一直存在且來源五花八門，但往往僅為不具備智慧特質的不完整片段資訊，因此無法利用。Gartner預估圖學資料庫(Graph Database)等語意學工具不斷進步，再加上其他資料分類與資訊分析技術逐漸崛起，都將賦予看似雜亂的大批資訊更多意義。

5. 先進機器學習(Machine Learning)
在先進機器學習方面，深度神經網路（Deep Neural Nets, DNNs）超越了典型運算與資訊管理技術，創造出能獨力自主學習如何理解各種事物的系統。資料來源爆炸加上資料日益複雜，讓手動分類與分析變得滯礙難行且不合經濟效益。深度神經網路能自動執行這些任務，如此一來要解決萬物聯網資訊趨勢所帶來的各項重大挑戰，也就不再遙不可及。

Gartner認為深度神經網路（是一種先進形式的機器學習，尤其適用於複雜的大型資料集）是讓智慧機器看起來「聰明」的關鍵所在。深度神經網路能讓硬體或軟體機器自行學習環境當中所有特徵，範圍小至枝微末節，最大則可掃描抽象類內容。相關領域持續快速演進，企業組織必須評估該如何應用相關技術以取得競爭優勢。

6. 自動代理與智慧物件(Autonomous Agents & Things)
機器學習提供了實現智慧機器自主（或至少半自主）運行的光譜，包含機器人、自駕車、虛擬個人助理以及智慧顧問。隨著實體智慧機器的進步，像是機器人得到極大的關注，以軟體為基礎的智慧機器有了更短期並更廣泛的影響，虛擬個人助理像是微軟的Cortana或蘋果的Siri都變得更為智慧，可以說是自動代理（Autonomous Agents）的前身。

助理的新興概念讓自動代理成為主要使用介面的環境使用體驗，使用者直接對著應用程式說話，而非與智慧型手機上的主選單、表單與按鍵互動，實際上就是智慧代理。

7. 適應性資安架構(Adaptive Security Architecture)
數位經濟及運算經濟的複雜性與新興的「駭客產業（Hacker Industry）」結合，顯著的提升組織的威脅面。仰賴網路外圍防禦及規則基礎的資安已不適當，特別是當組織採用了更多以雲端為基礎的服務，以及為了整合系統而開放API給客戶或合作夥伴。

IT領導者需專注於偵測並回應威脅，同時以更多傳統阻擋與其他方法防範攻擊。程式自我保護、使用者與實體行為分析都會協助實現適應性資安架構。

8. 進階系統架構(Advanced Systems Architecture )
數位網格與智慧機器需要精密的運算架構才能實現，而高能量、超高效率的神經型態架構（Neuromorphic Architecture）才能符合這種需求。以現場可程式化閘陣列（FPGA）驅動的架構是神經型態架構的重點技術，這樣的技術有顯著的好處，例如能夠在比每秒1兆次浮點運算（Teraflop）更高速的高能量效率下運行。

9. 網格應用程式與服務架構(Mesh App & Service Architecture )
整體的線性應用設計（例如三層架構，Three-tier Architecture）提供更鬆散的連接方式，即為應用程式和服務架構。這種透過軟體定義應用服務（Software Defined Application Services, SDAS)啟動的新管道促成網路規模的性能、彈性和敏捷性。微型服務結構不論對內部或者雲端來說，都是支援應用程式靈活地傳輸和規模性布建的新興模式。

容器（Container）技術竄起成為關鍵技術，讓結構發展與微型服務更靈活。引領手機與物聯網相關要件的應用程式與服務結構，創造了後台雲端計算的規模性與前端裝置的網格體驗的全面性解決方式。應用程式的開發小組必須創造新的現代架構，以提供靈活、有彈性、能夠變動的以雲端為基礎的應用程式與使用者體驗。

10. 物聯網架構與平台(IoT Architecture & Platform )
物聯網平台補充了網格應用程式和服務結構。管理、安全、與其他科技的整合，以及物聯網平台的標準，是建構、管理與保障物聯網的最基礎要素。從建築和技術的角度來看，物聯網平台構築IT的幕後工作，使物聯網成為現實。物聯網是數位網格的組成部份，環境使用體驗和新興而活躍的物聯網平台則是實現物聯網的主要元素。 (1500字；圖1)

Gartner Identifies the Top 10 Strategic Technology Trends for 2016

Analysts Explore Top Industry Trends at Gartner Symposium/ITxpo 2015, October 4-8 in Orlando

Gartner, Inc. today highlighted the top 10 technology trends that will be strategic for most organizations in 2016. Analysts presented their findings during the sold-out Gartner Symposium/ITxpo, which is taking place here through Thursday.

Gartner defines a strategic technology trend as one with the potential for significant impact on the organization. Factors that denote significant impact include a high potential for disruption to the business, end users or IT, the need for a major investment, or the risk of being late to adopt. These technologies impact the organization's long-term plans, programs and initiatives.

"Gartner's top 10 strategic technology trends will shape digital business opportunities through 2020," saidDavid Cearley, vice president and Gartner Fellow. "The first three trends address merging the physical and virtual worlds and the emergence of the digital mesh. While organizations focus on digital business today, algorithmic business is emerging. Algorithms — relationships and interconnections — define the future of business. In algorithmic business, much happens in the background in which people are not directly involved. This is enabled by smart machines, which our next three trends address. Our final four trends address the new IT reality, the new architecture and platform trends needed to support digital and algorithmic business."

The top 10 strategic technology trends for 2016 are:

The Device Mesh
The device mesh refers to an expanding set of endpoints people use to access applications and information or interact with people, social communities, governments and businesses. The device mesh includes mobile devices, wearable, consumer and home electronic devices, automotive devices and environmental devices — such as sensors in the Internet of Things (IoT).

"In the postmobile world the focus shifts to the mobile user who is surrounded by a mesh of devices extending well beyond traditional mobile devices," said Mr. Cearley.

While devices are increasingly connected to back-end systems through various networks, they have often operated in isolation from one another. As the device mesh evolves, we expect connection models to expand and greater cooperative interaction between devices to emerge.

Ambient User Experience
The device mesh creates the foundation for a new continuous and ambient user experience. Immersive environments delivering augmented and virtual reality hold significant potential but are only one aspect of the experience. The ambient user experience preserves continuity across boundaries of device mesh, time and space. The experience seamlessly flows across a shifting set of devices and interaction channels blending physical, virtual and electronic environment as the user moves from one place to another.

"Designing mobile apps remains an important strategic focus for the enterprise," said Mr. Cearley. "However, the leading edge of that design is focused on providing an experience that flows across and exploits different devices, including IoT sensors, common objects such as automobiles, or even factories. Designing these advanced experiences will be a major differentiator for independent software vendors (ISVs) and enterprises alike by 2018."

3D Printing Materials
Advances in 3D printing have already enabled 3D printing to use a wide range of materials, including advanced nickel alloys, carbon fiber, glass, conductive ink, electronics, pharmaceuticals and biological materials. These innovations are driving user demand, as the practical applications for 3D printers expand to more sectors, including aerospace, medical, automotive, energy and the military. The growing range of 3D-printable materials will drive a compound annual growth rate of 64.1 percent for enterprise 3D-printer shipments through 2019. These advances will necessitate a rethinking of assembly line and supply chain processes to exploit 3D printing.

"3D printing will see a steady expansion over the next 20 years of the materials that can be printed, improvement in the speed with which items can be printed and emergence of new models to print and assemble composite parts," said Mr. Cearley.

Information of Everything
Everything in the digital mesh produces, uses and transmits information. This information goes beyond textual, audio and video information to include sensory and contextual information. Information of everything addresses this influx with strategies and technologies to link data from all these different data sources. Information has always existed everywhere but has often been isolated, incomplete, unavailable or unintelligible. Advances in semantic tools such as graph databases as well as other emerging data classification and information analysis techniques will bring meaning to the often chaotic deluge of information.

Advanced Machine Learning
In advanced machine learning, deep neural nets (DNNs) move beyond classic computing and information management to create systems that can autonomously learn to perceive the world, on their own. The explosion of data sources and complexity of information makes manual classification and analysis infeasible and uneconomic. DNNs automate these tasks and make it possible to address key challenges related to the information of everything trend.

DNNs (an advanced form of machine learning particularly applicable to large, complex datasets) is what makes smart machines appear "intelligent." DNNs enable hardware- or software-based machines to learn for themselves all the features in their environment, from the finest details to broad sweeping abstract classes of content. This area is evolving quickly, and organizations must assess how they can apply these technologies to gain competitive advantage.

Autonomous Agents and Things
Machine learning gives rise to a spectrum of smart machine implementations — including robots, autonomous vehicles, virtual personal assistants (VPAs) and smart advisors — that act in an autonomous (or at least semiautonomous) manner. While advances in physical smart machines such as robots get a great deal of attention, the software-based smart machines have a more near-term and broader impact. VPAs such as Google Now, Microsoft's Cortana and Apple's Siri are becoming smarter and are precursors to autonomous agents. The emerging notion of assistance feeds into the ambient user experience in which an autonomous agent becomes the main user interface. Instead of interacting with menus, forms and buttons on a smartphone, the user speaks to an app, which is really an intelligent agent.

"Over the next five years we will evolve to a postapp world with intelligent agents delivering dynamic and contextual actions and interfaces," said Mr. Cearley. "IT leaders should explore how they can use autonomous things and agents to augment human activity and free people for work that only people can do. However, they must recognize that smart agents and things are a long-term phenomenon that will continually evolve and expand their uses for the next 20 years."

Adaptive Security Architecture
The complexities of digital business and the algorithmic economy combined with an emerging "hacker industry" significantly increase the threat surface for an organization. Relying on perimeter defense and rule-based security is inadequate, especially as organizations exploit more cloud-based services and open APIs for customers and partners to integrate with their systems. IT leaders must focus on detecting and responding to threats, as well as more traditional blocking and other measures to prevent attacks. Application self-protection, as well as user and entity behavior analytics, will help fulfill the adaptive security architecture.

Advanced System Architecture
The digital mesh and smart machines require intense computing architecture demands to make them viable for organizations. Providing this required boost are high-powered and ultraefficient neuromorphic architectures. Fueled by field-programmable gate arrays (FPGAs) as an underlining technology for neuromorphic architectures, there are significant gains to this architecture, such as being able to run at speeds of greater than a teraflop with high-energy efficiency.

"Systems built on GPUs and FPGAs will function more like human brains that are particularly suited to be applied to deep learning and other pattern-matching algorithms that smart machines use," said Mr. Cearley. "FPGA-based architecture will allow further distribution of algorithms into smaller form factors, with considerably less electrical power in the device mesh, thus allowing advanced machine learning capabilities to be proliferated into the tiniest IoT endpoints, such as homes, cars, wristwatches and even human beings."

Mesh App and Service Architecture
Monolithic, linear application designs (e.g., the three-tier architecture) are giving way to a more loosely coupled integrative approach: the apps and services architecture. Enabled by software-defined application services, this new approach enables Web-scale performance, flexibility and agility. Microservice architecture is an emerging pattern for building distributed applications that support agile delivery and scalable deployment, both on-premises and in the cloud. Containers are emerging as a critical technology for enabling agile development and microservice architectures. Bringing mobile and IoT elements into the app and service architecture creates a comprehensive model to address back-end cloud scalability and front-end device mesh experiences. Application teams must create new modern architectures to deliver agile, flexible and dynamic cloud-based applications with agile, flexible and dynamic user experiences that span the digital mesh.

Internet of Things Platforms
IoT platforms complement the mesh app and service architecture. The management, security, integration and other technologies and standards of the IoT platform are the base set of capabilities for building, managing and securing elements in the IoT. IoT platforms constitute the work IT does behind the scenes from an architectural and a technology standpoint to make the IoT a reality. The IoT is an integral part of the digital mesh and ambient user experience and the emerging and dynamic world of IoT platforms is what makes them possible.

"Any enterprise embracing the IoT will need to develop an IoT platform strategy, but incomplete competing vendor approaches will make standardization difficult through 2018," said Mr. Cearley.

Additional analysis can be found in the Gartner report “Top 10 Strategic Technology Trends for 2016: At a Glance.”

About Gartner Symposium/ITxpo
Gartner Symposium/ITxpo is the world's most important gathering of CIOs and senior IT executives. This event delivers independent and objective content with the authority and weight of the world's leading IT research and advisory organization, and provides access to the latest solutions from key technology providers. Gartner's annual Symposium/ITxpo events are key components of attendees' annual planning efforts. IT executives rely on Gartner Symposium/ITxpo to gain insight into how their organizations can use IT to address business challenges and improve operational efficiency.

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