IDC: Top 2017 Predictions

2017_predictions.pngIDC released its 10 IT industry predictions for 2017 in a webcast with Frank Gens, IDC’s senior vice president and chief analyst. The predictions covered many trends driving success today and in the future, from how the entire global economy will be re-shaped by digital transformation, the transition of all enterprises from being “digital immigrants” to being “digital natives,” the scaling up of innovation accelerators, the emergence of “the 4thplatform” (a new set of technologies that will become mainstream in ten years), drastic changes in how enterprises connect to their customers, and the ecosystem becoming as important for business success as IP. Here are IDC’s ten predictions:

By 2020, 50% of the G2000 will see the majority of their business depend on their ability to create digitally-enhanced products, services, and experiences.

We will see a “deep core” transformation of what enterprises are all about and how they behave in the marketplace. By the end of 2017, revenue growth from information-based products will be twice that of the rest of the portfolio for a third of G2000 companies. By 2021, a third of CEOs and COOs of G2000 companies will have spent at least 5 years in a tech leadership role. In 2019, worldwide spending on digital transformation initiatives will reach $2.2 trillion, almost 60% larger than 2016.

By 2019, 3rd Platform technologies and services will drive nearly 75% of IT spending – growing at 2X the rate of the total market.

Last year, IDC predicted that 3rd platform technologies and services—cloud, big data/analytics, social, and mobile—will drive 60% (not 75%) of OIT sepnding by 2019. The increase is due to a “snowball effect,” as these technologies are no longer “emerging” but have become the default choice. The innovation accelerators of the 3rdplatform—AI, IoT, AR/VR, robotics, 3D printing, and next-gen security (buttressed by blockchain)—will become mainstream.

By 2020, 67% of enterprise IT infrastructure and software will be for cloud-based offerings.

What clouds are and what they can do will change, IDC predicts: The cloud will be distributed with 60% of IT done off-premise and 85% by multi-cloud by 2018 and 43% of IoT will be processed at the edge in 2019; the cloud will be trusted and by 2020 it will be where trusted and secured IT lives, enhanced by blockchain-based security; the cloud will be concentrated and by 2020, the top 5 cloud Iaas/PaaS players will control at least 75% of the market share (vs about 50% in 2016).

By 2019, 40% of digital transformation initiatives – and 100% of IoT initiatives – will be supported by AI capabilities.

Top 3 AI use cases in terms of spending, says IDC, are: medical diagnostics and treatment, quality management in manufacturing, and automated service agents in retail. By 2018, 75% of developer teams will include AI functionality in one or more applications or services. Last year this prediction was at 50%  and the acceleration is due to the fact that the cloud is “democratizing adoption” of AI functionality. By 2019, over 110 million consumer devices with embedded intelligent assistants will be installed in U.S. households. In 2017-2020 period, 7 of the Top 10 AI use cases will be industry-focused and will account for 85% of top 10 use case investment. We will see a “battle of AI platforms,” with a strong competition for developers in AI space.

In 2017, 30% of consumer-facing G2000 companies will experiment with AR/VR as part of their marketing efforts.

More and more companies will connect with consumers through “immersive interfaces” including augmented reality and virtual reality. In 2018, the monthly active user base of consumers using mobile augmented reality apps (e.g., Pokemon Go) will exceed 400 million. By 2020, over 20% of commercial media on Facebook will be 360-degree VR, as social goes “immersive.” Dark horse scenario: 20% of all social media is 360-degree by 2020. In 2019, companies will deploy earworn wearables, with AI-enabled voice interface, as digital assistants for customer-facing roles (in retail, for example).

By 2018, the number of Industry Collaborative Clouds will triple to more than 450.

By 2020, almost 60% of enterprises will actively participate in compliance Clouds. By 2020, 75% of F500 companies will be suppliers of digital services through Industry Collaborative Clouds. 90%+ of Industry Collaborative Clouds will partner with a Cloud mega-platform provider.

By year end 2017, over 70% of the Global 500 will have dedicated digital transformation/innovation teams.

60% of F100 companies had already formed a dedicated team or a business unit focused on digital transformation. By 2018, enterprises pursuing digital transformation strategies will expand their developer teams by 2-3X. By 2019, more than 50% of the value of software will be monetized through “things” and consumer and business services. By 2020, DX teams will source 80%+ of their solution components from open source communities.

By 2020, over 70% of Cloud services providers’ revenues will be mediated by channel partners/brokers.

There will be a complete “reboot of the channel community,” as cloud providers will need help reaching potential customers and supporting them cloud services. By 2018, major IT distributors will have transitioned at least a third of their business from hardware sales to cloud services sales/brokering. By 2018, most cloud providers outside of the top 10 will offer brokered access to their leading competitors’ cloud services. By 2021, the “cloud broker” landscape serving SMBs will become highly industry-specific, offering cloud-based business services.

By 2020, all enterprises’ performance will be measured by a demanding new set of benchmarks in leadership, customer engagement, digitization of new and traditional offerings, operational efficiency and organizational agility. At least 1/3 of leaders in every industry will fail to clear these digital transformation hurdles.

New benchmarks will include 35% improvement in Net Promoter Score, 100% growth in revenues from information-based products, 20% of processes are self-healing, and 50% reduction in management layers. These performance levels will be “the new normal” for all enterprises.

By 2020, 1/3 of Health/Life Sciences and CP companies will begin to develop the first products and services tightly integrating 3rd Platform technologies with the human body. “Augmented Humanity” offerings will be mainstream in the mid- 2020s.

The 4th Platform will be the integration of digital technologies with human biosystems, and the use of digital technologies to engineer biological systems at the cellular and subcellular level.  “The 4thplatform is us,” says IDC. These set of technologies will provide humans with a wide variety of enhancements and we will see early adopters from 2021 to 2026.  Ethical and legal issues will emerge, and there a lot of controversy and debate will surround the emergence of the 4th Platform.

What will see as a result of all of these changes, says IDC, is the transformation of the traditional enterprise value chain to a new “enterprise social graph” or “the enterprise innovation graph,” linking the enterprise to its various communities: developers, channel, industry platforms, data providers , and customers and fans, as we already see today with Amazon, Apple, and Salesforce.

Originally published on Forbes.com

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Streaming Music: Age Demographics

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Americans increasingly use smartphones for more than voice calls, texting

Pew: Listening to music and shopping on the go are especially popular among smartphone owners ages 18 to 29: 87% have listened to an online radio or music service on their phone, compared with 41% of those 50 and over, and 73% have shopped online through their mobile device, versus 44% of older users.

Wall Street Journal: Last year less than 2% of consumers above the age of 45 opted to pay for an on-demand music service such as Apple Inc.’s Apple Music or Spotify AB’s Premium, while 11% of 18- to 24-year-olds did so and 8% of 25- to 34-year-olds paid, according to a survey by research firm MusicWatch Inc.

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McKinsey Updates Estimates of Big Data Potential Value

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Source: McKinsey, 2011

[In 2011], we estimated the potential for big data and analytics to create value in five specific domains. Revisiting them today shows uneven progress and a great deal of that value still on the table (exhibit). The greatest advances have occurred in location-based services and in US retail, both areas with competitors that are digital natives. In contrast, manufacturing, the EU public sector, and healthcare have captured less than 30 percent of the potential value we highlighted five years ago. And new opportunities have arisen since 2011, further widening the gap between the leaders and laggards.

Source: McKinsey, 2016

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Acquisitions and Investments by Media Companies Since 2010

 

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Investments and acquisitions by Verizon, Comcast, Discovery, Time Warner, and Disney

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Investments and acquisitions by Hearst, tronc, The Washington Post Company, News Corp., The New York Times Company, and Gannett

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Investments and acquisitions by Facebook, Google, Twitter, and Snapchat

Source: Columbia Journalism Review

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The Deep Learning Market: $1.7 Billion in 2022

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MarketsAndMarkets:

The deep learning market is expected to be worth $1,722.9 Million by 2022, growing at a CAGR of 65.3% between 2016 and 2022. The deep learning market has a huge potential across various industries such as advertisement, finance, and automotive. The major factors driving the deep learning market globally are the robust R&D for the development of better processing hardware and increasing adoption of cloud-based technology for deep learning.

The market for the data mining application is expected to grow at the highest rate between 2016 and 2022

The deep learning market for data mining application is expected to grow at the highest CAGR between 2016 and 2022. The increasing usage of deep learning in data analytics, cyber security, fraud detection, and database systems is fueling the growth of data mining applications in the deep learning market. Medical industries generate huge amounts of data sets related to medication, patient details, and diagnosis. This data is converted into valuable patterns and is used to forecast future trends. Thus, data mining is expected to witness the highest growth rate in the medical industry.

Deep learning hardware market expected to grow at the highest rate between 2016 and 2022

The high growth rate of the hardware market for deep learning is attributed to the growing need for hardware platforms with a high computing power to run deep learning algorithms. There is increasing competition among established as well as startup players, leading to new product developments including both hardware development and software platforms to run deep learning algorithms and programs. For instance, Graphcore (a U.K.-based company) is developing the intelligent processing unit (IPU) for machine learning technology for use in applications from driverless cars to cloud computing. Some of the companies involved in the development of hardware for the deep learning technique are Google, Inc. (U.S.), Microsoft Corporation (U.S.), Intel Corporation (U.S.), Qualcomm, Inc. (U.S.), IBM Corporation (U.S.), and others.

North America leads the deep learning market in terms of market size

North America is currently leading the deep learning market and is projected to be in the leading position for the next few years owing to the wide adoption of deep learning technology. The growth of the deep learning market in North America is attributed to the high government funding, presence of leading players, and strong technical base.

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Augmented Intelligence (#AI)

 

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Look Ma, No Drivers: Transportation Automation

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Fake News on Social Media: What Difference Does it Make?

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Pew Research Center:

Among social media users, Democrats – and liberal Democrats in particular – are a bit more likely than Republicans to say they have ever modified their views on a social or political issue, or on a particular political candidate, because of something they saw on social media. (Democrats and Republicans include independents and nonpartisans who “lean” toward these parties.)…

…the majority of social media users are not swayed by what they see in their networks. Some 82% of social media users say they have never modified their views on a particular candidate – and 79% say they have never changed their views on a social or political issue – because of something they saw on social media.

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What is Machine Learning

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Online Shopping on Twitter

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