Gartner: Top 10 Strategic Technology Trends for 2018 - Part 1

Gartner highlighted the top strategic technology trends that will impact most organizations in 2018.

Gartner defines a strategic technology trend as one with substantial disruptive potential that is beginning to break out of an emerging state into broader impact and use, or which are rapidly growing trends with a high degree of volatility reaching tipping points over the next five years.

"Gartner's top 10 strategic technology trends for 2018 tie into the Intelligent Digital Mesh. The intelligent digital mesh is a foundation for future digital business and ecosystems," said David Cearley, VP and Gartner Fellow. "IT leaders must factor these technology trends into their innovation strategies or risk losing ground to those that do."

The first three strategic technology trends explore how artificial intelligence (AI) and machine learning are seeping into virtually everything and represent a major battleground for technology providers over the next five years.

The next four trends focus on blending the digital and physical worlds to create an immersive, digitally enhanced environment.

The last three refer to exploiting connections between an expanding set of people and businesses, as well as devices, content and services to deliver digital business outcomes.

The top 10 strategic technology trends for 2018 are:

1. AI Foundation

Creating systems that learn, adapt and potentially act autonomously will be a major battleground for technology vendors through at least 2020. The ability to use AI to enhance decision making, reinvent business models and ecosystems, and remake the customer experience will drive the payoff for digital initiatives through 2025.

"AI techniques are evolving rapidly and organizations will need to invest significantly in skills, processes and tools to successfully exploit these techniques and build AI-enhanced systems," said Cearley. "Investment areas can include data preparation, integration, algorithm and training methodology selection, and model creation. Multiple constituencies including data scientists, developers and business process owners will need to work together."

2. Intelligent Apps and Analytics

Over the next few years, virtually every app, application and service will incorporate some level of AI. Some of these apps will be obvious intelligent apps that could not exist without AI and machine learning. Others will be unobtrusive users of AI that provide intelligence behind the scenes. Intelligent apps create a new intelligent intermediary layer between people and systems and have the potential to transform the nature of work and the structure of the workplace.

Over the next few years, virtually every app, application and service will incorporate some level of AI.

"Explore intelligent apps as a way of augmenting human activity and not simply as a way of replacing people," said Cearley. "Augmented analytics is a particularly strategic growing area which uses machine learning to automate data preparation, insight discovery and insight sharing for a broad range of business users, operational workers and citizen data scientists."

AI has become the next major battleground in a wide range of software and service markets, including aspects of enterprise resource planning (ERP). Packaged software and service providers should outline how they'll be using AI to add business value in new versions in the form of advanced analytics, intelligent processes and advanced user experiences.

3. Intelligent Things

Intelligent things are physical things that go beyond the execution of rigid programming models to exploit AI to deliver advanced behaviors and interact more naturally with their surroundings and with people. AI is driving advances for new intelligent things (such as autonomous vehicles, robots and drones) and delivering enhanced capability to many existing things (such as Internet of Things [IoT] connected consumer and industrial systems).

"Currently, the use of autonomous vehicles in controlled settings (for example, in farming and mining) is a rapidly growing area of intelligent things. We are likely to see examples of autonomous vehicles on limited, well-defined and controlled roadways by 2022, but general use of autonomous cars will likely require a person in the driver's seat in case the technology should unexpectedly fail," said Cearley. "For at least the next five years, we expect that semiautonomous scenarios requiring a driver will dominate. During this time, manufacturers will test the technology more rigorously, and the nontechnology issues such as regulations, legal issues and cultural acceptance will be addressed."

4. Digital Twin

A digital twin refers to the digital representation of a real-world entity or system. Digital twins in the context of IoT projects is particularly promising over the next three to five years and is leading the interest in digital twins today.

Well-designed digital twins of assets have the potential to significantly improve enterprise decision making. These digital twins are linked to their real-world counterparts and are used to understand the state of the thing or system, respond to changes, improve operations and add value. Organizations will implement digital twins simply at first, then evolve them over time, improving their ability to collect and visualize the right data, apply the right analytics and rules, and respond effectively to business objectives.

"Over time, digital representations of virtually every aspect of our world will be connected dynamically with their real-world counterpart and with one another and infused with AI-based capabilities to enable advanced simulation, operation and analysis," said Cearley. "City planners, digital marketers, healthcare professionals and industrial planners will all benefit from this long-term shift to the integrated digital twin world."

5. Cloud to the Edge

Edge computing describes a computing topology in which information processing, and content collection and delivery, are placed closer to the sources of this information. Connectivity and latency challenges, bandwidth constraints and greater functionality embedded at the edge favors distributed models. Enterprises should begin using edge design patterns in their infrastructure architectures — particularly for those with significant IoT elements.

While many view cloud and edge as competing approaches, cloud is a style of computing where elastically scalable technology capabilities are delivered as a service and does not inherently mandate a centralized model.

"When used as complementary concepts, cloud can be the style of computing used to create a service-oriented model and a centralized control and coordination structure with edge being used as a delivery style allowing for disconnected or distributed process execution of aspects of the cloud service," said Cearley.

Read Gartner: Top 10 Strategic Technology Trends for 2018 - Part 2

Related Links

Hot Topics

The Latest

High-Business Impact Outages Cost Financial Services and Insurance Sectors $2.2 Million Per Hour

Artificial intelligence (AI) is core to observability practices, with some 41% of respondents reporting AI adoption as a core driver of observability, according to the State of Observability for Financial Services and Insurance report from New Relic ...

Conversational APM: How GenAI Is Transforming Observability

Application performance monitoring (APM) is a game of catching up — building dashboards, setting thresholds, tuning alerts, and manually correlating metrics to root causes. In the early days, this straightforward model worked as applications were simpler, stacks more predictable, and telemetry was manageable. Today, the landscape has shifted, and more assertive tools are needed ...

Cloud Backup as a Business Asset: Why Your Backup Strategy Needs to Evolve

Cloud adoption has accelerated, but backup strategies haven't always kept pace. Many organizations continue to rely on backup strategies that were either lifted directly from on-prem environments or use cloud-native tools in limited, DR-focused ways ... Eon uncovered a handful of critical gaps regarding how organizations approach cloud backup. To capture these prevailing winds, we gathered insights from 150+ IT and cloud leaders at the recent Google Cloud Next conference, which we've compiled into the 2025 State of Cloud Data Backup ...

Private Cloud Outlook 2025: A Definitive Cloud Reset

Private clouds are no longer playing catch-up, and public clouds are no longer the default as organizations recalibrate their cloud strategies, according to the Private Cloud Outlook 2025 report from Broadcom. More than half (53%) of survey respondents say private cloud is their top priority for deploying new workloads over the next three years, while 69% are considering workload repatriation from public to private cloud, with one-third having already done so ...

Two-Thirds of Organizations Significantly at Risk of Software Outage within Next Year

As organizations chase productivity gains from generative AI, teams are overwhelmingly focused on improving delivery speed (45%) over enhancing software quality (13%), according to the Quality Transformation Report from Tricentis ...

MongoDB's Market Woes Shed Light on Hard Truths About Vendor Lock-in

Back in March of this year ... MongoDB's stock price took a serious tumble ... In my opinion, it reflects a deeper structural issue in enterprise software economics altogether — vendor lock-in ...

MEAN TIME TO INSIGHT Podcast - Episode 15: DIY Network Automation

In MEAN TIME TO INSIGHT Episode 15, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses Do-It-Yourself Network Automation ... 

Checkmate VPN Intruders with Personal SASE Service

Zero-day vulnerabilities — security flaws that are exploited before developers even know they exist — pose one of the greatest risks to modern organizations. Recently, such vulnerabilities have been discovered in well-known VPN systems like Ivanti and Fortinet, highlighting just how outdated these legacy technologies have become in defending against fast-evolving cyber threats ... To protect digital assets and remote workers in today's environment, companies need more than patchwork solutions. They need architecture that is secure by design ...

Observability 2.0: The Convergence of AI, OpenTelemetry, and Unified Data

Traditional observability requires users to leap across different platforms or tools for metrics, logs, or traces and related issues manually, which is very time-consuming, so as to reasonably ascertain the root cause. Observability 2.0 fixes this by unifying all telemetry data, logs, metrics, and traces into a single, context-rich pipeline that flows into one smart platform. But this is far from just having a bunch of additional data; this data is actionable, predictive, and tied to revenue realization ...

Challenges of DIY Network Automation

64% of enterprise networking teams use internally developed software or scripts for network automation, but 61% of those teams spend six or more hours per week debugging and maintaining them, according to From Scripts to Platforms: Why Homegrown Tools Dominate Network Automation and How Vendors Can Help, my latest EMA report ...

Gartner: Top 10 Strategic Technology Trends for 2018 - Part 1

Gartner highlighted the top strategic technology trends that will impact most organizations in 2018.

Gartner defines a strategic technology trend as one with substantial disruptive potential that is beginning to break out of an emerging state into broader impact and use, or which are rapidly growing trends with a high degree of volatility reaching tipping points over the next five years.

"Gartner's top 10 strategic technology trends for 2018 tie into the Intelligent Digital Mesh. The intelligent digital mesh is a foundation for future digital business and ecosystems," said David Cearley, VP and Gartner Fellow. "IT leaders must factor these technology trends into their innovation strategies or risk losing ground to those that do."

The first three strategic technology trends explore how artificial intelligence (AI) and machine learning are seeping into virtually everything and represent a major battleground for technology providers over the next five years.

The next four trends focus on blending the digital and physical worlds to create an immersive, digitally enhanced environment.

The last three refer to exploiting connections between an expanding set of people and businesses, as well as devices, content and services to deliver digital business outcomes.

The top 10 strategic technology trends for 2018 are:

1. AI Foundation

Creating systems that learn, adapt and potentially act autonomously will be a major battleground for technology vendors through at least 2020. The ability to use AI to enhance decision making, reinvent business models and ecosystems, and remake the customer experience will drive the payoff for digital initiatives through 2025.

"AI techniques are evolving rapidly and organizations will need to invest significantly in skills, processes and tools to successfully exploit these techniques and build AI-enhanced systems," said Cearley. "Investment areas can include data preparation, integration, algorithm and training methodology selection, and model creation. Multiple constituencies including data scientists, developers and business process owners will need to work together."

2. Intelligent Apps and Analytics

Over the next few years, virtually every app, application and service will incorporate some level of AI. Some of these apps will be obvious intelligent apps that could not exist without AI and machine learning. Others will be unobtrusive users of AI that provide intelligence behind the scenes. Intelligent apps create a new intelligent intermediary layer between people and systems and have the potential to transform the nature of work and the structure of the workplace.

Over the next few years, virtually every app, application and service will incorporate some level of AI.

"Explore intelligent apps as a way of augmenting human activity and not simply as a way of replacing people," said Cearley. "Augmented analytics is a particularly strategic growing area which uses machine learning to automate data preparation, insight discovery and insight sharing for a broad range of business users, operational workers and citizen data scientists."

AI has become the next major battleground in a wide range of software and service markets, including aspects of enterprise resource planning (ERP). Packaged software and service providers should outline how they'll be using AI to add business value in new versions in the form of advanced analytics, intelligent processes and advanced user experiences.

3. Intelligent Things

Intelligent things are physical things that go beyond the execution of rigid programming models to exploit AI to deliver advanced behaviors and interact more naturally with their surroundings and with people. AI is driving advances for new intelligent things (such as autonomous vehicles, robots and drones) and delivering enhanced capability to many existing things (such as Internet of Things [IoT] connected consumer and industrial systems).

"Currently, the use of autonomous vehicles in controlled settings (for example, in farming and mining) is a rapidly growing area of intelligent things. We are likely to see examples of autonomous vehicles on limited, well-defined and controlled roadways by 2022, but general use of autonomous cars will likely require a person in the driver's seat in case the technology should unexpectedly fail," said Cearley. "For at least the next five years, we expect that semiautonomous scenarios requiring a driver will dominate. During this time, manufacturers will test the technology more rigorously, and the nontechnology issues such as regulations, legal issues and cultural acceptance will be addressed."

4. Digital Twin

A digital twin refers to the digital representation of a real-world entity or system. Digital twins in the context of IoT projects is particularly promising over the next three to five years and is leading the interest in digital twins today.

Well-designed digital twins of assets have the potential to significantly improve enterprise decision making. These digital twins are linked to their real-world counterparts and are used to understand the state of the thing or system, respond to changes, improve operations and add value. Organizations will implement digital twins simply at first, then evolve them over time, improving their ability to collect and visualize the right data, apply the right analytics and rules, and respond effectively to business objectives.

"Over time, digital representations of virtually every aspect of our world will be connected dynamically with their real-world counterpart and with one another and infused with AI-based capabilities to enable advanced simulation, operation and analysis," said Cearley. "City planners, digital marketers, healthcare professionals and industrial planners will all benefit from this long-term shift to the integrated digital twin world."

5. Cloud to the Edge

Edge computing describes a computing topology in which information processing, and content collection and delivery, are placed closer to the sources of this information. Connectivity and latency challenges, bandwidth constraints and greater functionality embedded at the edge favors distributed models. Enterprises should begin using edge design patterns in their infrastructure architectures — particularly for those with significant IoT elements.

While many view cloud and edge as competing approaches, cloud is a style of computing where elastically scalable technology capabilities are delivered as a service and does not inherently mandate a centralized model.

"When used as complementary concepts, cloud can be the style of computing used to create a service-oriented model and a centralized control and coordination structure with edge being used as a delivery style allowing for disconnected or distributed process execution of aspects of the cloud service," said Cearley.

Read Gartner: Top 10 Strategic Technology Trends for 2018 - Part 2

Related Links

Hot Topics

The Latest

High-Business Impact Outages Cost Financial Services and Insurance Sectors $2.2 Million Per Hour

Artificial intelligence (AI) is core to observability practices, with some 41% of respondents reporting AI adoption as a core driver of observability, according to the State of Observability for Financial Services and Insurance report from New Relic ...

Conversational APM: How GenAI Is Transforming Observability

Application performance monitoring (APM) is a game of catching up — building dashboards, setting thresholds, tuning alerts, and manually correlating metrics to root causes. In the early days, this straightforward model worked as applications were simpler, stacks more predictable, and telemetry was manageable. Today, the landscape has shifted, and more assertive tools are needed ...

Cloud Backup as a Business Asset: Why Your Backup Strategy Needs to Evolve

Cloud adoption has accelerated, but backup strategies haven't always kept pace. Many organizations continue to rely on backup strategies that were either lifted directly from on-prem environments or use cloud-native tools in limited, DR-focused ways ... Eon uncovered a handful of critical gaps regarding how organizations approach cloud backup. To capture these prevailing winds, we gathered insights from 150+ IT and cloud leaders at the recent Google Cloud Next conference, which we've compiled into the 2025 State of Cloud Data Backup ...

Private Cloud Outlook 2025: A Definitive Cloud Reset

Private clouds are no longer playing catch-up, and public clouds are no longer the default as organizations recalibrate their cloud strategies, according to the Private Cloud Outlook 2025 report from Broadcom. More than half (53%) of survey respondents say private cloud is their top priority for deploying new workloads over the next three years, while 69% are considering workload repatriation from public to private cloud, with one-third having already done so ...

Two-Thirds of Organizations Significantly at Risk of Software Outage within Next Year

As organizations chase productivity gains from generative AI, teams are overwhelmingly focused on improving delivery speed (45%) over enhancing software quality (13%), according to the Quality Transformation Report from Tricentis ...

MongoDB's Market Woes Shed Light on Hard Truths About Vendor Lock-in

Back in March of this year ... MongoDB's stock price took a serious tumble ... In my opinion, it reflects a deeper structural issue in enterprise software economics altogether — vendor lock-in ...

MEAN TIME TO INSIGHT Podcast - Episode 15: DIY Network Automation

In MEAN TIME TO INSIGHT Episode 15, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses Do-It-Yourself Network Automation ... 

Checkmate VPN Intruders with Personal SASE Service

Zero-day vulnerabilities — security flaws that are exploited before developers even know they exist — pose one of the greatest risks to modern organizations. Recently, such vulnerabilities have been discovered in well-known VPN systems like Ivanti and Fortinet, highlighting just how outdated these legacy technologies have become in defending against fast-evolving cyber threats ... To protect digital assets and remote workers in today's environment, companies need more than patchwork solutions. They need architecture that is secure by design ...

Observability 2.0: The Convergence of AI, OpenTelemetry, and Unified Data

Traditional observability requires users to leap across different platforms or tools for metrics, logs, or traces and related issues manually, which is very time-consuming, so as to reasonably ascertain the root cause. Observability 2.0 fixes this by unifying all telemetry data, logs, metrics, and traces into a single, context-rich pipeline that flows into one smart platform. But this is far from just having a bunch of additional data; this data is actionable, predictive, and tied to revenue realization ...

Challenges of DIY Network Automation

64% of enterprise networking teams use internally developed software or scripts for network automation, but 61% of those teams spend six or more hours per week debugging and maintaining them, according to From Scripts to Platforms: Why Homegrown Tools Dominate Network Automation and How Vendors Can Help, my latest EMA report ...