Gartner: Top 10 strategic technology trends in 2020

Two decades ago, at the start of the millennium, IT was deeply concerned about Y2K – and the iPhone, Twitter and Facebook didn’t exist. So what’s in store as a new decade begins?

Brian Burke

The year 2020 heralds another decade rich with disruptive technology trends. Some of these technologies are already commonplace, but the proliferation of new use cases and applications will see industry grappling with both benefits and opportunities. At Gartner, we predict that the key strategic technology trends in 2020 will include hyperautomation, blockchain and artificial intelligence security, among others. 

1. Automation 2020: Hyperautomation  

Hyperautomation takes applications for task automation to the next level. It enables the application of advanced technologies, such as artificial intelligence (AI) and machine learning, to increasingly automate processes and augment human requirements.

In some cases, it can mean the creation of a digital twin of the organisation – allowing visualisation of how functions, processes and key performance indicators interact to drive value.

But as no single tool can replace humans, hyperautomation will involve a combination of elements. Such tools include robotic process automation and intelligent business management software. 

2. Multiexperience is the new experience 

From 2020 onward, multiexperience will see the traditional idea of computing evolve from a single point of interaction to include multisensory and multitouchpoint interfaces, such as wearables and advanced computer sensors. Over the coming decade, this trend will become what is known as ambient experience.

But multiexperience currently focuses on immersive experiences that use augmented reality, virtual reality, mixed reality, multichannel human-machine interfaces and sensing technologies. 

3. Democracy, 2020 style

The democratisation of technology means providing people with easy access to technical or business expertise without extensive or expensive training. Already referred to as “citizen access”, this trend will focus on four key areas: application development, data and analytics, design, and knowledge.

Democratisation is expected to see the rise of citizen data scientists, programmers and other forms of DIY technology engagement. For example, it could enable more people to generate data models without having the skills of a data scientist. This would, in part, be made possible through AI-driven code generation.

4. Augmentation gets human 

The controversial trend of human augmentation focuses on the use of technology to enhance an individual’s cognitive and physical experiences. It comes with a range of cultural and ethical implications.

For example, using CRISPR (clustered, regularly interspaced, short palindromic repeats) technologies to augment genes has significant ethical consequences. Physical augmentation changes an inherent physical capability by implanting or hosting a technology within or on the body.

Applications include the use of wearables to improve worker safety in the mining industry. In other industries, such as retail and travel, wearables could be used to increase worker productivity. 

5. Greater transparency and traceability

The evolution of technology is creating a trust crisis. Particularly as consumers become more aware of how their personal data is collected and used, organisations are increasingly recognising the liability of storing and gathering data. But many are also using AI and machine learning more to make decisions in place of humans.

This is a further cause of concern, which is driving the need for processes such as explainable AI and AI governance. This trend requires a focus on these key elements of trust: integrity, openness, accountability, competence and consistency. More legislation similar to the European Union’s General Data Protection Regulation (GDPR) is likely to be enacted around the world in the coming years. 

6. The empowered edge

The growing edge computing trend is based on the idea that keeping traffic local and distributed will reduce latency. This involves a topology where information processing and content collection and delivery are placed closer to the sources of the information.

The empowered edge employs the technology on the internet of things (IoT). This extends to the role of devices as the basis for smart spaces and moves key applications and services closer to the people and devices that use them. By 2023, there could be more than 20 times as many smart devices at the edge of the network as in conventional IT roles. 

7. The distributed cloud

The distributed cloud refers to the dispersal of public cloud services to locations outside the cloud provider’s physical datacentres, while still in the control of the provider. In the distributed cloud, the provider is responsible for all aspects of cloud service architecture, delivery, operations, governance and updates.

The evolution from centralised public cloud to distributed public cloud ushers in a new era of cloud computing. The distributed cloud allows datacentres to be located anywhere. This solves both technical and regulatory issues, such as latency and data sovereignty. It also offers the combined benefits of a public cloud service and a private, local cloud. 

8. Even more autonomous things

Autonomous things, which include drones, robots, ships and appliances, exploit AI to perform tasks traditionally undertaken by humans. This technology operates on a spectrum of intelligence ranging from semiautonomous to fully autonomous and across a variety of environments including air, sea and land.

While currently, autonomous things mainly exist in controlled environments, such as warehouses, they will evolve to include open public spaces. Autonomous things will also move from standalone to collaborative swarms – such as the drone swarms used during the Winter Olympic Games in 2018.

9. Towards practical blockchain

Enterprise blockchain today takes a practical approach and implements only some of the elements of a complete blockchain. Everyone with permissioned access sees the same information, and integration is simplified by having a single shared blockchain.

In the future, true blockchain or “blockchain complete” will have the potential to transform industries, and eventually the economy, as complementary technologies such as AI and the IoT begin to integrate alongside blockchain.

This expands the type of participants to include machines, which will be able to exchange a variety of assets. For example, a car would be able to negotiate insurance prices directly with the insurance company based on data gathered by its sensors. Moreover, blockchain will be fully scalable by 2023.

10. Greater AI security 

Evolving technologies such as hyperautomation offer transformational opportunities in the business world. However, they also create security vulnerabilities through potential new points of attack. Security teams must address these challenges and be aware of how AI will impact the security space. 

Future AI security will have three key perspectives: firstly, protecting AI-powered systems, securing AI training data, and training pipelines and machine learning models; secondly, leveraging AI to enhance security defence, and using machine learning to understand patterns, uncover attacks and automate parts of the cybersecurity processes; thirdy, anticipating nefarious use of AI by attackers – identifying attacks and defending against them. 

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12 Emerging Internet of Things (IoT) Trends That Will Become Mainstream In 2018

In November, in a dive into what is driving enterprise interest in the Internet of Things (IoT) we found that, for the moment at least, enterprises are still wrestling with the problems the IoT poses rather than harvesting the benefits that it offers. There is nothing unusual in this given that the IoT is still a relatively new phenomena and there are considerable — and justified — security fears dominating enterprise strategies around the IoT.

But will security dominate IoT this year. And what about the Industrial IoT — will it move further away from the IoT as some have suggested or will they become closer? At the beginning of 2016 we saw that the really big tech vendors likes Microsoft were dedicating significant resources to building IoT incubators that would focus on enterprise, industry and smart cities. However, now, with security solutions getting "smarter" and enterprises actively looking to harvest consumer data harvested from the IoT, the connection between IoT and Industrial IoT is getting narrower and closer to Cisco’s idea of the Internet of Everything (IoE).

Mark Barrenechea, OpenText CEO and CTO shared that while we might not feel the immediate effects of the IoT, its potential impact is huge. Advances in IoT-connected biotechnology will take healthcare to the next level, with around-the-clock monitoring, targeted treatment, and even automated doses of medication. In smart cities, when everything is connected to the IoT grid, autonomous vehicles will eliminate car crashes caused by human error to save one million lives annually. “In the Intelligent Enterprise, the IoT will connect the global supply chain from end-to-end, enabling pervasive visibility, proactive replenishment, and predictive maintenance. With the IoT, data-driven decision making will become standard in all industries and in our daily lives,” he says. So what will happen with the IoT and the Industrial IoT, and what will enterprises be doing to optimize their investments?

1. Security

“The pace of change has exceeded the rate of human capability to absorb — the cup is already full. In 2018, the real issue is how to increase the ability for people to understand the changes and their implications more clearly, and to take concrete actions to take advantage of the potential upside,” says Erick Dean, Product Director of IoT, at San Francisco-based Splunk. As a result, he has security at the top of his list for IoT trends in 2018, but it’s not all that’s going to happen.

In 2018, security for IoT will be under heavy scrutiny. Cybersecurity risk will increase exponentially as people, processes and businesses continue to connect every part of people’s daily lives, as well as national economies. "We are looking into a future where attacks can be orchestrated not just from public networks, but from private devices such as a smartphones or a smart home,” he says. His other predictions for 2018 go as follows.

2. Major Adopters

Industrial asset management, fleet management in transportation, inventory management and government security will be the hottest areas for IoT growth in 2018. With increasing connectivity between people, data and things, the public sector will begin embracing smart cities, where sensors and automation enhance the reliability of services, especially in the areas of safety and environment. IoT sensor data enables use cases including improved air quality, optimized traffic patterns, reduced safety incidents, traffic fire incident prediction, and improved citizen identity.

3. Digital Transformation

Digital transformation initiatives — especially those centered around customer experience — will drive IoT expansion velocity. Building a technology infrastructure is relatively easy. The challenge is operationalizing data-driven decision-making that impacts the health of the business.

4. Machine Learning

Machine learning and AI represent a tremendous opportunity to IoT. Being able to predict when machinery will need to be repaired, self-optimizing production, and demand response are only a few application examples. With existing network infrastructure likely to be used for "connected things" the investment spend on analytics will be higher as companies find new ways to make sense of the vast amounts of smart device-generated data.

5. IoT Growing Up

Jeff Kavanaugh, VP and Senior Partner in India-based Infosys, told us that while problems persist, the IoT is starting to mature and that enterprises will start trying to monetize the data that is harvested from the IoT. Those that are using the IoT will also start to realize that IoT is difficult "to do."

According to Kavanaugh, connected devices will become smarter and more immersive, and expectations will increase to convert IoT data to insights and financial value. Algorithms and data visualization templates have now evolved so that new use cases can take advantage of earlier ones. The exponential adoption of IoT will drive down sensor and acquisition costs, enabling more and more viable business cases that have previously been too expensive.

6. Executive Expectations

He added that just as enterprise resource planning maturity raised expectations about foundational data consistency, robotic process automation will raise executive expectations about performance levels for repetitive processes. Companies will get better at scaling automation, moving from interesting proofs of concept to systemic enterprise processes that generate efficiency at scale.

Fast-moving technologies will influence colleges and universities to adopt greater computer programming and data analysis courses. However, universities must complement these with a focus on critical thinking and empathetic skills to meet the growing need of enduring skills in the digital world.

7. Revenue Model Challenges

Los Angeles-based Inspire is a company that simplifies consumer adoption of clean energy and smart home technologies. Patrick Maloney, CEO and of the company points out that despite the euphoria around the IoT, there are no guarantees that companies that make a business out of it are going to make money. There has been no shortage of innovation and new product offerings for the smart home this past year, driven largely by advancements in AI, automation, and voice-enabled technology. This is unlikely to change any time soon. However, he said, going to market is hard, retail shelves are crowded, and products aren’t highly differentiated making it difficult to maintain long-term growth. The revenue models for most smart home products and devices are transactional, one-time purchases.

Unless you are Amazon or Google, creating predictable and capital-efficient revenue streams is not likely. Companies that will succeed in the smart home space are those that can make the transition to a recurring revenue business model, and also create more value and efficiency for the consumer. “Smart homes shouldn’t just be smart for the sake of being smart, but instead improve consumers’ everyday lives. By focusing on smart home services, not just the hardware, we’ll see companies achieve both,” he says.

8. Blockchain

Mike Bell, EVP IoT & Devices at London, UK-based Canonical points to the rise of blockchain in IoT as one of the major emerging trends for 2017 and says that this and machine learning will become established elements of the IoT landscape over the course of the next 12 months. “Two of the most interesting IoT developments to emerge in 2017, with the most potential for innovation, were blockchain and machine learning. They likely won't go straight to market in the new year — we'll likely see more proofs of concept (PoC) instead — but, we have seen some fascinating PoCs already,” he said.

Machine learning has also yielded some interesting case studies to date. While it won't move entirely to edge there are some compelling examples so far, like retail shop security cameras with streaming video, where machine learning can be utilized to identify patterns of potential theft, perform facial without digging into customers' personal data, to head off security and privacy concerns.

9. Analytics Literacy

Alluvium is a New York City start-up that uses machine learning and artificial intelligence to turn massive streams of complex industrial data into simple insights enabling factories to reach operational stability. Its founder and CEO, Dean Conway, says that on the industrial IoT, organizations will move from making investments in digital infrastructure to making investments in digital literacy.

Conway predicts that the curve of investment in the industrial IoT will begin to bend toward analytics capabilities. This will likely manifest as a blend of hiring for new roles, such as data scientists and data engineers; a move to multi-cloud to investigate capabilities across incumbent cloud providers, such as Microsoft, Amazon, and Google; and, experimentation in investment with cutting edge analytics tools.

10. Mergers And Acquisitions

There will also be increased merger and acquisition activity for advanced IoT capabilities among large OEMs. This dovetails with the large appetite from industrial OEMs to bring advanced digital and analytics capabilities in-house as a means of accelerating their competitive advantage. Because software engineering and data science are not core competencies of OEMs, it will continue to be more efficient for these organizations to bring these capabilities into their stacks. As digital transparency continues to increase at every level of production the competition among OEMs at the software and services layer will emerge as the deciding differentiator in 2018.

11. Convergence And Employment

Joseph Bradley agrees that blockchain and deeper mining of data will be major trends in 2018, but also believes that the IoT will start driving changes in the jobs market.

As is Global Vice President for Digital and IoT Advanced Services at San Jose, Calif.-based Cisco he points out that the integration of social, business and political will force companies to enter what was previously known as a “no fly zone.” 3As competition for technology talent intensifies, silence won’t be an option for businesses. Millennials and generation Z — both of which will dominate the U.S. workforce by 2020 — will reshape the employment landscape due to their convictions and the expectation that employers demonstrate similar convictions,” he says.

To maintain a workforce and drive success, companies must to listen to their employee base and apply corporate principles to social and political activities. In 2018 and beyond, “taking a stand” will become the norm as companies hire upcoming generations who thrive on a values-driven corporate culture.

12. Next Generation Manufacturing

Chris Steck also works for Cisco as Head of Standardization, IoT & Industries. He says the IoT boom will facilitate the emergence of next generation manufacturing.  Manufacturing is buzzing about Industry 4.0, according to Steck,  the term for a collection of new capabilities for smart factories, that is driving what is literally the next industrial revolution. “IoT technologies are connecting new devices, sensors, machines, and other assets together, while Lean Six Sigma and continuous improvement methodologies are harvesting value from new IoT data. Early adopters are already seeing big reductions in equipment downtime (from 15 to 95%), process waste and energy consumption in factories. 

There are more than 50 billion connected devices in circulation today, generating an excess of eight zetabytes of data between them. And that number is only likely to expand. However, only one percent of Internet of Things (IoT) data is currently analyzed and utilized. But all this is changing. Soon, IoT deployments will include a holistic mobile and cloud platform, consisting of planning and analysis with digital twins, operational autonomy and augmented human and machine interactions using cognitive AI services, predictive analytics, and supporting applications.  This may be for the medium term but the early stages of this change will be seen over the course of 2018.

By David Roe

The Internet of Things in 2017: trends, technologies, market data and evolutions

The Internet of Things will connect existing systems and then augment those by connecting more things, thanks to wireless sensor networks and other technologies. Things on the 'edge' form mesh networks and can make their own automated decisions. But where and how, in the scale of hype to reality, can the Internet of Things profit suppliers and users today? What are the pragmatic steps needed to enable the Internet of Things and widespread deployment of wireless sensor networks that are feasible and based on an ROI and not the hope someone else will pay for this? Who is buying IoT in the short term? 

A look into some of the main IoT trends for 2017, based on research, observations and different sources.

In March 2017, market research firm Ovum released a list of essential IoT trends for 2017, in collaboration with Internet of Things World. That seemed like a good opportunity to cover some major key IoT trends and predictions too.

We tackle the 5 essential Internet of Things (IoT) trends worth watching in the overall Internet of Things market according to the the organizers of Internet of Things World 2017 and Ovum, add some context and comments and, while we were at it, add over a dozen IoT trends.

The growth of scalable IoT projects and rise of cross-industry IoT deployments

First things first: the 5 IoT trends as reported by the two mentioned parties. Ovum stresses that 2016 was an important year for the Internet of Things but that 2017 is even more important and disruptive, both for the IoT technology players and the many industries where IoT projects are being deployed.

In fact, here is already one IoT trend we can add: based on data regarding the increasing maturity, scalability and deployment of effective IoT projects, beyond the proof of concept stage, this move towards scalable IoT projects is an IoT trend for 2017 for sure. That was our IoT trend number 1.

M&A activity in the IoT market will increase as providers continue to differentiate their offerings

Today, the majority of ‘significant and disruptive’ IoT trends as Ovum puts it are still mainly happening in industrial settings such as manufacturing (Industry 4.0), transportation and utilities, certainly from an IoT spending perspective. Other IoT projects relate to automotive, retail, consumer IoT, ad hoc IoT-enabled smart city projects and so forth. Moreover, cross-industry IoT use cases and deployments are on the rise and will rise even more in 2017 which is IoT trend number 2. Update: according to June 2017 data by IDC on IoT investments, cross-industry IoT cases will reach $86 billion by the end of 2017. That is more than the second largest industry from an IoT investment perspective (transportation, good for $85 billion).

Taking all this into account and without further ado a look at those five key IoT trends for 2017, as reported by Ovum and Internet of Things World 2017.

IoT connectivity: LPWA technologies become mainstream

The first key IoT trend for 2017, according to Ovum (that’s IoT trend number 3 in our list so far) is the fact that LPWA(N) goes mainstream and is poised to support far more Internet of Things use cases.

The announcement doesn’t mention Low-Power Wide-Area Network (LPWAN) technologies in the unlicensed spectrum such as LoRa and Sigfox, to name just two. Ovum and Internet of Things World 2017 rather point out Narrowband IoT (NB-IoT) and LTE-M (Long Term Evolution for Machines). In other words: Ovum emphasizes the cellular LPWA evolutions or the two standards which have been standardized within the 3GPP (3rd Generation Partnership Project).

A nice overview of the cellular LPWA technologies Ovum mentions in an infographic from Sierra Wireless – source press release new LPWA modules

Among the main IoT use cases for LPWA which Ovum mentions: smart city applications, smart metering and the connected home.

Non-cellular LPWAN technologies such as LoRa and Sigfox are also used in many smart city projects and virtually all applications where a low-cost, low-bandwidth and long battery life technology is needed, precisely what LPWA, whether it’s cellular or not, is all about.

IoT connectivity: non-cellular LPWAN will prove to be underestimated

Although unlicensed LPWAN technologies today account for a relatively small portion of all IoT cases and investments, we’re pretty sure that, certainly in the increasing number of countries where nationwide coverage exists and in the many large cities and regions where they are planned, they will more than add to the fact that LPWA goes – more – mainstream, with an increasing number of IoT use cases and deployments as a result.

And that brings us to ‘our’ IoT trend number 4. If we look at the many projects where unlicensed spectrum LPWAN is being deployed (e.g. a LoRaWAN testbed in London), the advent of decent new actors in the field (e.g. TrackNet, which raised $7 million), the large companies which are investing in LPWAN players and ecosystems (take a look at the list of the investors in the latest Sigfox investment round) and the technological evolutions whereby multiple connectivity solutions get supported, among other reasons, we believe that the non-cellular LPWA market is underestimated and its growth is yet another IoT trend for 2017 as investments outside the Industrial Internet of Things will grow and companies will roll out low-risk pilots.

If you want an example of the – according to us, underestimated – role of non-cellular LPWA, take a look at what the Airport of Schiphol in The Netherlands is doing.

What is true though is that the non-cellular market evolved first and mainly outside of the US, according to us a reason why it’s underestimated (for now).

IoT security becomes a top IoT priority

This seems like an obvious prediction or, rather IoT trend (number 5), not just given the many security incidents in 2016. If IoT security would not become a core focus for enterprises and providers as Ovum and Internet of Things World put it, we would have a serious issue.

As mentioned previously, and as Ovum also states, security needs to be and will be part of every SERIOUS IoT deployment discussion. This is not just the case for consumer-oriented IoT but also for Industry 4.0 and the Industrial Internet of Things. As we tackled previously, security concerns remain a key showstopper in IIoT, where attacks are on the rise, as well.

64% of security professionals recognize the need to take precautions against IIoT attacks as they increase

Moreover, just security isn’t enough. While security concerns the protection of data and the related technologies, we also need to look at the protection of personal data, what privacy is all about. Blockchain (see below) is poised to play an increasing role here.

IoT regulation becomes a key priority

One of the reasons to do so is the regulatory context. Think about the GDPR and the ePrivacy Regulation, for instance.

In fact, Ovum states that IoT security is coming onto the radar for regulators, which for us is yet another IoT trend as such (that’s number 6 if we counted well). As we mentioned and as we suppose Ovum means, this is also the case outside the scope of EU regulations.

Even if the FTC seems to go for a self-regulation approach we do indeed see and expect regulatory plans and intentions rising. It’s important to note that in the context of regulatory frameworks such as the GDPR and eRegulation, there are specific aspects which need to be tackled regarding the Internet of Things and its technologies.

Analytics and machine learning

Time for IoT trend number 7. According to the announcement of Ovum, Big Data and machine learning will unlock new IoT opportunities.

With this key IoT trend, Ovum in fact summarizes several evolutions. One is the clear shift of the delivery of IoT data analytics to the point of data capture/aggregation or the edge. Indeed: the fog or fog computing. Once more, we believe that this too is an IoT trend for 2017 as such: the fast rise of fog computing (IoT trend number 8).

A second evolution in the context of Big Data, analytics and machine learning is the rise of new tools for streaming data analytics, Ovum states (IoT trend number 9). Both evolutions fit in a context of the enablement of leveraging IoT data to feed all sorts of artificial intelligenceapplications, including the feeding of machine-leaning engines.

The growth of as-a-service business models

IoT trend number 10 (five in the list of Ovum and Internet of Things World 2017): the disruptive impact of the IoT will drive the growth of new as-a-service business models.

Most definitely yes. In fact, if you look at a large majority of Industrial Internet of Things cases (look at the case of ABB Robotics, for example, there are plenty more) one of the key digital transformation effects on a business model level is the move towards information-based business models and as-a-service models, making quite some large players develop entirely new services and shifting business models.

We definitely also agree that these ‘innovative business models will continue to evolve in many IoT verticals’ as Ovum predicts, including as-a-service and event-based charging models.

The adoption of as-a-service IoT solutions

We’re adding IoT trend 11 for 2017 here: the growth of as-a-service-models IN the Internet of Things solutions and deployment ‘stack’.

Just as the Internet of Things continues to drive evolutions towards as-a-service model, companies with Internet of Things projects will increasingly use platforms and solutions to enable them in an as-a-service approach. Just one example: Internet of Things security as a service is poised to grow fast.

By 2021, overall market revenues for IoT managed security services are poised to surpass $11 Billion

IoT service providers will increasingly focus on a diversification regarding technologies

The reason: customer needs become more diverse. This is definitely another IoT trend (number 12).

As we see more complex and scalable IoT deployments this is an inevitable evolution. It happens on all levels. Although strictly not a service provider, Cisco for instance already supports several technologies for client projects. The same happens with service providers on other levels. According to Ovum, service providers will also focus more on developer outreach.

The growth and increasing diversity of an IoT channel

We’ve covered all the Ovum trends so let’s look at some more.

IoT trend number 13: an IoT channel will continue to emerge and grow as IT service firms, vendors and distributors seek to diversify revenues and offerings, adding IoT to their portfolios in the scope of their existing strengths in particular areas (e.g. verticals, security, etc.).

This will also happen outside or IT and telecom and among businesses that are not typically part of the IT channel. Examples include marketing firms, offering IoT solutions for which they’ll also need IoT technologies and facility management and smart building companies, convincing their existing channel partners to include IoT solutions in their offerings for existing and new end customers.

Ten more IoT trends and predictions for 2017

We have 13 IoT trends but let’s summarize some more and of course there are even more than those we mention next…

• Although 5G is not ready for prime-time, we’ll see industry consortium efforts grow to push the 5G agenda and market. This will happen within the Fog Consortium Group’s efforts and in new industry initiatives.
• The attention for blockchain and IoT convergence will grow, yet blockchain flaws will need to be fixed as public key is a no-brainer for quantum computers.
• As growth, securtity, analytics and connectivity will require more AI and IBM is boosting its Watson IoT spend and initiatives the battle for AI IoT dominance will increase, mainly for specific verticals.
• M&A activity in the IoT market will increase as providers continue to differentiate their offerings.
• Consumer IoT adoption will grow but regulatory uncertainties in specific regions will surface new security and privacy challenges, among others regarding voice assistants.
• Healthcare payers will step up their efforts to deploy new ways to connect IoT data with healthcare plans.
• Disappointment regarding early smart city IoT deployments will grow while new smart city IoT deployments will increasingly fit in the holistic smart city picture and will be driven by real challenges.
• Retailers will invest less in testing a variety of IoT use cases and focus more on the supply chain and use cases that offer immediate benefits.
• The adoption of wearables will grow faster than expected outside of the consumer wearables context and in verticals such as healthcare and manufacturing.
• IT and OT integration in the Industrial Internet is on the rise but hindred by security concerns, slowing down integration.
• The number of connected devices will grow and there will be more security breaches.

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Gartner’s Top 10 Strategic Technology Trends for 2017

Kasey Panetta


Artificial intelligence, machine learning, and smart things promise an intelligent future.

Today, a digital stethoscope has the ability to record and store heartbeat and respiratory sounds. Tomorrow, the stethoscope could function as an “intelligent thing” by collecting a massive amount of such data, relating the data to diagnostic and treatment information, and building an artificial intelligence (AI)-powered doctor assistance app to provide the physician with diagnostic support in real-time. AI and machine learning increasingly will be embedded into everyday things such as appliances, speakers and hospital equipment. This phenomenon is closely aligned with the emergence of conversational systems, the expansion of the IoT into a digital mesh and the trend toward digital twins.

Three themes — intelligent, digital, and mesh — form the basis for the Top 10 strategic technology trends for 2017, announced by David Cearley, vice president and Gartner Fellow, at Gartner Symposium/ITxpo 2016 in Orlando, Florida. These technologies are just beginning to break out of an emerging state and stand to have substantial disruptive potential across industries.

Intelligent

AI and machine learning have reached a critical tipping point and will increasingly augment and extend virtually every technology enabled service, thing or application.  Creating intelligent systems that learn, adapt and potentially act autonomously rather than simply execute predefined instructions is primary battleground for technology vendors through at least 2020.

Trend No. 1: AI & Advanced Machine Learning

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.  The combination of extensive parallel processing power, advanced algorithms and massive data sets to feed the algorithms has unleashed this new era.

In banking, you could use AI and machine-learning techniques to model current real-time transactions, as well as predictive models of transactions based on their likelihood of being fraudulent. 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..

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). However, intelligent apps are not limited to new digital assistants – every existing software category from security tooling to enterprise applications such as marketing or ERP will be infused with AI enabled capabilities.  Using AI, technology providers will focus on three areas — advanced analytics, AI-powered and increasingly autonomous business processes and AI-powered immersive, conversational and continuous interfaces. 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. Each of these areas will evolve to impact a larger segment of the market and support a new phase of digital business but these represent only one facet of intelligent things.  Existing things including IoT devices will become intelligent things delivering the power of AI enabled systems everywhere including the home, office, factory floor, and medical facility.

As intelligent things evolve and become more popular, they will shift from a stand-alone to a collaborative model in which intelligent things communicate with one another and act in concert to accomplish tasks. However, nontechnical issues such as liability and privacy, along with the complexity of creating highly specialized assistants, will slow embedded intelligence in some scenarios.

Digital

The lines between the digital and physical world continue to blur creating new opportunities for digital businesses.  Look for the digital world to be an increasingly detailed reflection of the physical world and the digital world to appear as part of the physical world creating fertile ground for new business models and digitally enabled ecosystems.

Trend No. 4: Virtual & Augmented Reality

Virtual reality (VR) and augmented reality (AR) transform the way individuals interact with each other and with software systems creating an immersive environment.  For example, VR can be used for training scenarios and remote experiences. 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.  Immersive experiences with AR and VR are reaching tipping points in terms of price and capability but will not replace other interface models.  Over time AR and VR expand beyond visual immersion to include all human senses.  Enterprises should look for targeted applications of VR and AR through 2020.

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. Using physics data on how the components of a thing operate and respond to the environment as well as data provided by sensors in the physical world, a digital twin can be used to analyze and simulate real world conditions, responds to changes, improve operations and add 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 collaborate with data scientists and IT professionals.  Digital twins of physical assets combined with digital representations of facilities and environments as well as people, businesses and processes will enable an increasingly detailed digital representation of the real world for simulation, analysis and control.

Trend No. 6: Blockchain

Blockchain is a type of distributed ledger in which value exchange transactions (in bitcoin or other token) are sequentially grouped into blocks.  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.  They promise a model to add trust to untrusted environments and reduce business friction by providing transparent access to the information in the chain.  While there is a great deal of interest the majority of blockchain initiatives are in alpha or beta phases and significant technology challenges exist.

Mesh

The mesh refers to the dynamic connection of people, processes, things and services supporting intelligent digital ecosystems.  As the mesh evolves, the user experience fundamentally changes and the supporting technology and security architectures and platforms must change as well.

Trend No. 7: Conversational Systems

Conversational systems can range from simple informal, bidirectional text or voice 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 shift from a model where people adapt to computers to one where the computer “hears” and adapts to a person’s desired outcome.  Conversational systems do not use text/voice as the exclusive interface but enable 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).

Trend No. 8: Mesh App and Service Architecture

The intelligent digital mesh will require changes to the architecture, technology and tools used to develop solutions. The mesh app and service architecture (MASA) is a multichannel solution architecture that leverages cloud and serverless computing, containers and microservices as well as APIs and events to deliver modular, flexible and dynamic solutions.  Solutions ultimately support multiple users in multiple roles using multiple devices and communicating over multiple networks. However, MASA is a long term architectural shift that requires significant changes to development tooling and best practices.

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. In particular new platforms and services for IoT, AI and conversational systems will be a key focus through 2020.   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. Security in the IoT environment is particularly challenging. Security teams need to work with application, solution and enterprise architects to consider security early in the design of applications or IoT solutions.  Multilayered security and use of user and entity behavior analytics will become a requirement for virtually every enterprise.

David Cearley is vice president and Gartner Fellow in Gartner Research and is a leading authority on information technology. Mr. Cearley analyzes emerging and strategic business and technology trends and explores how these trends shape the way individuals and companies derive value from technology.