Thursday, 2 April 2020

Here’s What You Need to Know About Digital Transformation

According to the new Cisco Annual Internet Report 2018-2023, there will be 29.3 billion networked devices by 2023, up from 18.4 billion in 2018, (9.8% compound annual growth rate) globally and 5.3 billion total Internet users (66% of the population) by 2023, up from 3.9 billion (51% of the population) in 2018.

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In addition to the many, many billions of users and devices connecting to global IP networks, the new report also projects faster speeds for wired and wireless networks (driven by new fiber deployments and cable standards as well as Wi-Fi6 and 5G).

◉ Globally, the average fixed broadband speed will grow 2.4-fold from 2018 to 2023, from 45.9 Mbps in 2018 to 110.4 Mbps.

◉ Globally, the average Wi-Fi speeds from mobile devices will grow 3.0-fold from 2018 to 2023, from 30.3 Mbps in 2018 to 92 Mbps by 2023.

◉ Globally, the average mobile (cellular) connection speed will grow 3.3-fold from 2018 to 2023, from 13.2 Mbps in 2018 to 43.9 Mbps by 2023.

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Better network performance (faster speeds and lower latencies) serve as the foundation for other network innovations and application advancements for consumer and business users. Network users demand and expect more from their online experiences. Ubiquitous access and millisecond responsiveness are now table stakes characteristics (not features). Next-gen applications must be customized and tailored to individual user preferences. This “new normal” adds complexity and scale that are often difficult for service providers and IT teams to keep with and support. Fortunately, artificial intelligence (AI) and machine learning (ML) are helping to automate many types of repetitive network jobs/processes and develop new insights into online user behaviors and preferences.

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And with the many next-gen applications being created, new models of business are being created as well. Artificial Intelligence and Machine learning and many other applications are now taking advantage of the digital transformation which is very much underway thus creating new models of business and impacting various industries.

AI Platforms and applications are enabling enterprises to leverage ML capabilities and provide enhanced accuracy and user experiences. AI is projected to be utilized everywhere from edge to core to cloud. Technology providers should continue to partner and support rapid deployment, interoperability, and standardization of AI solutions.

Take a look at our executive insights on “Reimagine your applications”. Across almost all business sectors there is an increased demand for new or enhanced applications that increase workforce productivity or improve customer experiences.

IT departments are often challenged to transform infrastructures to accommodate new technologies. The Internet of Things (IoT), artificial intelligence (AI), machine learning (ML), and business analytics are changing how developers build smart applications to simplify customer transactions and deliver new business insights.

Take the music industry, for example, Watson BEAT helped create a better soundtrack than an original composition with the help of a cognitive machine. The IBM® Spectrum Computing team asked IBM Watson® Beat to come up with killer beats for its latest Red Bull Racing video—and the AI composer used its neural network to lay down a unique track.

Or look to the Automotive industry, where self-driving cars use Artificial Intelligence. Next-gen applications such as “Reinforcement learning” have found its way in revolutionizing the automotive industry by creating autonomous driving cars and the financial services industry with new ways of portfolio management.

Tesla, for example, uses AI and effectively crowdsources its data from all of its vehicles with its internal and external sensors. While this will help Tesla refine its self-driving systems, this data holds tremendous value in its own right. Researchers at McKinsey and Co estimate that the market for vehicle-gathered data will be worth $750 billion a year by 2030.

Another example of a next-gen application is predictive analytics which involves using advanced analytic techniques that leverage historical data to uncover real-time insights and to predict future events. Predictive analytics can help transform the way a business operates and can be used for many Industrial IoT solutions- using sensor data to predict equipment failure, weather patterns, crop rotation, and yield predictions and various other impacts on agriculture and the food industry and many other IoT solutions.

New next-gen applications and their rapidly evolving use cases and real-life examples are being built every day—the most successful of which will involve shifting technologies and evolving business models as we digitally transform.

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