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There are 10 trends that infrastructure and operations (I&O) leaders must start preparing for to support digital infrastructure in 2020. “This past year, infrastructure trends focused on how technologies like artificial intelligence (AI) or edge computing might support rapidly growing infrastructure and support business needs at the same time,” said Ross Winser, senior research director at Gartner. “While those demands are still present, our 2020 list of trends reflect their ‘cascade effects,’ many of which are not immediately visible today,” said Winser. I&O leaders are encouraged to take a step back from “the pressure of keeping the lights on” and prepare for key technologies and trends likely to significantly impact their support of digital infrastructure in 2020 and beyond. They are: Trend no. 1: Automation strategy rethink In recent years, there has been a significant range of automation maturity across clients: Most organizations are automating to some level, in many cases attempting to refocus staff on higher-value tasks. However, automation investments are often made without an overall automation strategy in mind. “As vendors continue to pop up and offer new automation options, enterprises risk ending up with a duplication of tools, processes, and hidden costs that culminate to form a situation where they simply cannot scale infrastructure in the way the business expects,” said Winser. “We think that by 2025, top performing leaders will have employed a dedicated role to steward automation forward and invest to build a proper automation strategy to get away from these ad hoc automation issues.” Trend no. 2: Hybrid IT versus disaster recovery (DR) confidence “Today’s infrastructure is in many places — colocation, on-premises data centers, edge locations, and in cloud services. The reality of this situation is that hybrid IT will seriously disrupt your incumbent disaster recover (DR) planning if it hasn’t already,” said Winser. Often, organizations heavily rely on “as a service (aaS)” offerings, where it is easy to overlook the optional features necessary to establish the correct levels of resilience. For instance, by 2021, the root cause of 90% of cloud-based availability issues will be the failure to fully use cloud service provider native redundancy capabilities. “Organizations are left potentially exposed when their heritage DR plans designed for traditional systems have not been reviewed with new hybrid infrastructures in mind. Resilience requirements must be evaluated at design stages rather than treated as an afterthought two years after deployment,” said Winser. Trend no. 3: Scaling DevOps agility For enterprises trying to scale DevOps, action is needed in 2020 to find an efficient approach for success. Although individual product teams typically master DevOps practices, constraints begin to emerge as organizations attempt to scale the number of DevOps teams. “We believe that the vast majority of organizations that do not adopt a shared self-service platform approach will find that their DevOps initiatives simply do not scale,” said Winser. “Adopting a shared platform approach enables product teams to draw from an I&O digital toolbox of possibilities, all the while benefiting from high standards of governance and efficiency needed for scale.” Trend no. 4: Infrastructure is everywhere — so is your data “Last year, we introduced the theme of ’infrastructure is everywhere’ that the business needs it. As technologies like AI and machine learning (ML) are harnessed as competitive differentiators, planning for how explosive data growth will be managed is vital,” said Winser. In fact, by 2022, 60% of enterprise IT infrastructures will focus on centers of data, rather than traditional data centers. “The attraction of moving selected workloads closer to users for performance and compliance reasons is understandable. Yet we are rapidly heading toward scenarios where these same workloads run across many locations and cause data to be harder to protect. Cascade effects of data movement combined with data growth will hit I&O folks hard if they are not preparing now.” Trend no. 5: Overwhelming impact of IoT Successful IoT projects have many considerations, and no single vendor is likely to provide a complete end-to-end solution. “I&O must get involved in the early planning discussions of the IoT puzzle to understand the proposed service and support model at scale. This will avoid the cascade effect of unforeseen service gaps, which could cause serious headaches in future,” said Winser. Trend no. 6: Distributed cloud Distributed cloud is defined as the distribution of public cloud services to different physical locations, while operation, governance, updates, and the evolution of those services are the responsibility of the originating public cloud provider. “Emerging options for distributed cloud will enable I&O teams to put public cloud services in the location of their choosing, which could be really attractive for leaders looking to modernize using public cloud,” said Winser. However, the nascent nature of many of these solutions means a wide range of considerations must not be overlooked. “Enthusiasm for new services like AWS Outposts, Microsoft Azure Stack, or Google Anthos must be matched early on with diligence in ensuring the delivery model for these solutions is fully understood by I&O teams who will be involved in supporting them," said Winser. Trend no. 7: Immersive experience “Customer standards for the experience delivered by I&O capabilities are higher than ever. Previous ‘value adds’ like seamless integration, rapid responses, and zero downtime are now simply baseline customer expectations,” said Winser. As digital business systems reach deeper into I&O infrastructures, the potential impact of even the smallest of I&O issues expands. “If the customer experience is good, you might grow in mind and market share over time; but if the experience is bad, the impacts are immediate and could potentially impact corporate reputation rather than just customer satisfaction.” Trend no. 8: Democratization of IT Low-code is a visual development approach to application development that is becoming increasingly appealing to business units. It enables developers of varied experience levels to create applications for web and mobile with little or no coding experience, largely driving a “self-service” model for business units instead of turning to central IT for a formal project plan. “As low-code becomes more commonplace, the complexity of the IT portfolio increases. And when low-code approaches are successful, I&O teams will eventually be asked to provide service. Starting now, it is in I&O leaders’ best interest to embed their support and exert influence over things that will inevitably affect their teams, as well as the broader organization,” said Winser. Trend no. 9: Networking — What’s Next? In many cases, network teams have excelled in delivering highly available networks, which is often achieved through cautious change management. At the same time, the pace of change is tough for I&O to keep up with, and there are no signs of things slowing down. The continued pressure to keep the lights shining brightly has created unexpected issues for the network. “Cultural challenges of risk avoidance, technical debt and vendor lock-in all mean that some network teams face a tough road ahead. 2020 needs to be the time for cultural shifts, as investment in new network technologies is only part of the answer,” said Winser. Trend no. 10: Hybrid digital infrastructure management (HDIM) As the realities of hybrid digital infrastructures kick in, the scale and complexity of managing them is becoming a more pressing issue for IT leaders. Organizations should investigate the concept of HDIM, which looks to address the primary management issues of a hybrid infrastructure. "This is an emerging area, so organizations should be wary of vendors who say they have tools that offer a single solution to all their hybrid management issues today. Over the next few years, though, we expect vendors focused on HDIM to deliver improvements that enable IT leaders to get the answers they need far faster than they can today,” said Winser. Article published by icrunchdata Image credit by Getty Images, E+, alengo Want more? For Job Seekers | For Employers | For Influencers
IEEE Computer Society (IEEE CS) tech experts unveiled their annual predictions for the future of tech, presenting what they believe will be the most widely adopted technology trends in 2020. The tech future forecast by this organization of computer professionals consistently ranks as one of its most anticipated announcements. "These predictions identify the top dozen technologies that have substantial potential to disrupt the market in the year 2020," said Cecilia Metra, IEEE CS President. "In 2020 we expect to see ever-increasing adoption of artificial intelligence (AI) in various use cases such as AI@Edge, cognitive robots and drones, as well as with verticals that include cybersecurity, cyber-physical systems, and adversarial machine learning (ML)," said Dejan Milojicic, Hewlett Packard Enterprise Distinguished Technologist and IEEE CS past president (2014). "We are also anticipating a breakthrough in the adoption of non-volatile memory, digital twins, and additive materials. We are excited about our predictions and the bets we have made for 2020 technology trends," said Milojicic. The top 12 technology trends predicted to reach adoption in 2020 are: 1. AI at the edge (AI@Edge). The last decade has seen an explosion of ML in our daily interactions with the cloud. The availability of massive crowd-sourced labeled data, the increase in computer power efficiency at lower cost, and the advances of ML algorithms, lay the foundation of this disruption. As techniques improve and become robust enough to automate many activities, there is an increased demand for using ML in new ways that are more pervasive than the initial cloud use cases. Combined with ubiquitous connectivity such as 5G, and intelligent sensors such as the Internet of Things (IoT), ML applications will rapidly move to the "edge," the physical world close to us all. In the upcoming years, we expect to see the widespread deployment of ML in areas that will have a far greater impact on our daily lives, such as assisted driving, industrial automation, surveillance, and natural language processing. 2. Non-volatile memory (NVM) products, interfaces, and applications. NVM Express (NVMe) SSDs will replace SATA and SAS SSDs within the next few years, and NVMe-oF will be the dominant network storage protocol in five years.  NVMe enables NAND tiering technologies and programming functions that increase endurance, enable computational storage, and allow more memory-like access to data. Emerging memory technologies such as MRAM, ReRAM, and PCM will provide future higher performance NVMe devices. 3. Digital twins, including cognitive twins. Digital twins are a reality in the manufacturing industry, and major IoT platforms, like Siemens MindSphere, are supporting them. They have also become a widespread tool in complex system operations; railways and power plants have been used in cities since Jan 1, 2019. The Singapore administration uses digital twins for planning, simulation, and operations in Singapore. Cognitive digital twins are in the early stages of trial and experimentation. 4. AI and critical systems. AI will be deployed increasingly in more systems that affect the health, safety and welfare of the public. These systems will better utilize scarce resources, prevent disasters, and increase safety, reliability, comfort, and convenience. Despite the technological challenges and public fears, these systems will improve the quality of life for millions of people worldwide. Within five years, there will be a significant increase in the application of AI in critical infrastructure systems, or "critical systems," that directly affect the health, safety, and welfare of the public and in which failure could cause loss of life, serious injury, or significant loss of assets or privacy. Critical systems include power generation and distribution, telecommunications, road and rail transportation, healthcare, banking, and more. 5. Practical delivery drones. Parcel delivery is an industry of enormous economic impact, and yet has evolved relatively slowly over the decades. It can still be frustratingly slow, wasteful, labor-intensive, and expensive. These inefficiencies, combined with recent developments in drone technology, leave the field ripe for disruption. Several companies have recently worked to develop practical delivery drones, which may now be ready to completely transform this industry, and consequently society as a whole. 6. Additive manufacturing. 3D printing has existed since at least the early 1980s but has largely been confined to part prototyping and small-scale production of special-purpose or exotic pieces. Currently, new processes, materials, hardware, software, and workflows are bringing 3D printing into the realm of manufacturing, especially for mass customization. Unlike traditional manufacturing, additive manufacturing makes it economically viable to produce a high volume of parts where each one is different. For instance, companies like SmileDirect now use 3D printers to generate tens of thousands of molds each day, each customized to make an orthodontic aligner for an individual person. Stronger and more robust materials, finer resolution, new finishing techniques, factory-level management software, and many other advances are increasing the adoption of 3D printing in industries such as healthcare, footwear, and automotive. In 2020, we expect to see this trend continue as other industries discover the benefits of mass customization and the opportunity to print parts that are not easy or affordable to produce using traditional means. 7. Cognitive skills for robots. Robots are spreading more and more from the manufacturing floors into spaces occupied by humans. There is a need for robots in such environments to be able to adapt to new tasks through capabilities such as increased comprehension of the environments within which they are situated. We predict that recent breakthroughs in large-scale simulations, deep reinforcement learning, and computer vision, collectively will bring forth a basic level of cognitive abilities to robots that will lead to significant improvements in robotic applications over the next few years. 8. AI and ML applied to cybersecurity. Cybersecurity is one of the key risks for any business today. The growing attack surface includes amateur threats, sophisticated distributed denial of service attacks, and skilled nation-state actors. Defense depends on security analysts who are rare, lack adequate training, and have high turnover rates. AI and ML can help detect threats and offer recommendations to security analysts. AI and ML can drive down response times from hundreds of hours to seconds and scale analyst effectiveness from one or two incidents to thousands daily. It can preserve corporate knowledge and use it to automate tasks and train new analysts. We predict advancing the adoption of AI and ML applied to cybersecurity through a partnership among members of industry, academia, and government on a global scale. 9. Legal related implications to reflect security and privacy. Data collection and leveraging capabilities are becoming more sophisticated and sensitive, often incorporating live feeds of information from sensors and various other technologies. These enhanced capabilities have yielded new streams of data and new types of content that raise policy and legal concerns over possible abuse: nefarious actors and governments may repurpose these capabilities for reasons of social control.  Similarly, new technology capabilities also strain the abilities of average people to discern the difference between legitimate and fraudulent technology content, such as accepting an authentic video versus a "deep fake." As such, the next year will prove critical to maintaining the fragile balance between preserving the social benefits of technology, on the one hand, and preventing undesirable repurposing of these new technology capabilities for social control and liberty deprivation, on the other. More aggressive legal and policy tools are needed for detecting fraud and preventing abuse of these enhanced technology capabilities. 10. Adversarial ML. ML generally assumes that the environment is not maliciously manipulated during the training and evaluation of models. In other words, most ML models have inadequately considered the ways in which an adversary can attack and manipulate the model's functionality. Yet, security researchers have already demonstrated that adversarial, malicious inputs can trick ML models into desired outcomes, even without full information about a target model's parameters. As ML becomes incorporated into other systems, the frequency of malicious attacks on ML will rise. As such, security research into adversarial ML and countermeasures aimed at detecting manipulation of ML systems will become critically important. Similarly, recognition of the fallibility and manipulability of ML systems will begin to inform policymaking and legal paradigms. 11. Reliability and safety challenges for intelligent systems. Intelligent systems, capable of making autonomous decisions, are nowadays attracting an increasing economic investment worldwide. We expect that they will be increasingly adopted in several fields, including smart cities, autonomous vehicles, and autonomous robots. Depending on the application field, the autonomy of intelligent systems has been formalized by defined levels. Of course, the higher the level of intelligence and consequent autonomous capabilities, the stronger the requirements in terms of reliability and safety for the intelligent systems' operation in the field, where reliability is defined as the likelihood of correct operation for a given amount of time, while safety refers to the ability to avoid catastrophic consequences on the environment and users. Guaranteeing the required high levels of reliability and safety that are mandated for highly autonomous intelligent systems will be one of the major technological challenges to be faced by 2020, to enable a smarter world. 12. Quantum computing. The quest for practical quantum computing will move forward in 2020, yet remain incomplete. At the beginning of 2020, experimental quantum computer demonstrations consume about 1/10,000 the energy of the world's largest supercomputers while outperforming them by 1,000x or more – yet the demonstrated applications look like quantum computer self-tests. If quantum computers are destined to be successful, they will come about by increasing relevance and generality, having already demonstrated a computational advantage. We project demonstrations to become more compelling in the next year. For example, a quantum computer might perform a chemical simulation impossible by any standard supercomputer, leading to a more nuanced debate about whether the chemical that may be discovered will be useful to society. Promising tech The tech predictions analysis included a review of technologies that are considered very promising yet are not likely to reach broad adoption until after 2020. Such technologies include: Seamless assisted reality Virtual reality for business Distributed (cooperative) robotics Simulating whole world Autonomous vehicles Printable bio-materials and tissue Technologies that were reviewed yet considered to have already reached broad adoption are: Photonic-based communication in data centers Facial recognition 5G Multi-agent systems Security of IoT devices Disaggregated servers Blockchain The IEEE CS team of leading technology experts includes: Mary Baker, HP Inc. Tom Coughlin, Coughlin Associates Erik DeBenedictis, Entrepreneur Paolo Faraboschi, Hewlett Packard Enterprise VP and Fellow Eitan Frachtenberg, Data Scientist Danny Lange, VP of AI at Unity Phil Laplante, Professor, Penn State Andrea Matwyshyn, Professor and Assoc. Dean of Innovation, Penn State Law - University Park, and Professor, Penn State Engineering Avi Mendelson, Professor, Technion and NTU Singapore Cecilia Metra, Professor, Bologna University and IEEE CS President Dejan Milojicic, Hewlett Packard Enterprise Distinguished Technologist and IEEE Computer Society President 2014 Roberto Saracco, Chair of the Symbiotic Autonomous Systems Initiative of IEEE-FDC Jeffrey Voas, NIST At the end of the coming year, the IEEE CS tech experts will review the past predictions to determine how closely they match up to technology's reality. Visit the 2020 Tech Trends page to access free downloads of the exclusive technology content. Article published by icrunchdata Image credit by IEEE Computer Society Want more? For Job Seekers | For Employers | For Influencers
Entering into a new decade, boards and C-suite leaders around the world are concerned with the escalating competition for specialized talent, their organizations' culture, and the ability to advance their digital maturity and embrace the transformative opportunities of technology. Business leaders contend that coupled with the ongoing economic uncertainty and unknown future regulatory changes, these risks could impact their ability to effectively compete, grow their business and achieve operational targets in 2020 and beyond. This is according to findings from the "Executive Perspectives on Top Risks 2020" survey conducted recently by consulting firm Protiviti and North Carolina State University Poole College of Management's Enterprise Risk Management (ERM) Initiative. Now in its eighth year, the latest survey identified top concerns on the minds of over 1,000 board members and C-suite executives from organizations in a variety of industries around the globe. Nearly sixty-eight percent of survey respondents' organizations have annual revenues between $100 million and $10 billion. The Top 10 Risks for 2020 Survey respondents were asked to rate 30 macroeconomic, strategic, and operational risks. Of those, the top 10 risks identified are as follows: Regulatory changes and scrutiny may impact operational resilience and production and delivery of products and services Economic conditions may significantly restrict growth opportunities Succession challenges and ability to attract and retain top talent may be more difficult Limited operational resilience of legacy IT infrastructure and digital capabilities may restrict the organization's ability to compete with "born digital" players Resistance to change may restrict organizational agility Preparedness to manage cyber threats may be insufficient Ensuring privacy/identity management and information security/system protection may be challenging Company culture may not empower timely identification and escalation of risk issues Sustaining customer loyalty and retention may be increasingly difficult Adoption of AI-enabled technologies may require new skills that are either in short supply or require significant upskilling/reskilling of existing employees "Nearly half of the top risks this year are related to culture and attracting and retaining top talent. This is happening at a time when organizations need to execute increasingly complex strategies to navigate the rapidly changing digitally-based business environment," said Jim DeLoach, a Protiviti managing director and co-author of the report. "As the future of work evolves, businesses need to upskill and reskill existing employees – particularly as digital innovations, such as artificial intelligence, natural language processing, and robotics become a mainstay in organizations – to ensure they remain competitive with 'born digital' companies and are future-proofed for the next decade," said DeLoach. While several of the risks remain consistent with findings from previous years, including concerns around regulation, cyber threats, operational resilience, privacy management, and information security, this year's results show an escalation of anxiety related to overall economic issues across domestic and international markets – climbing from number 11 last year to the number two risk concern for 2020. Dr. Mark Beasley, professor of Enterprise Risk Management and director of NC State's ERM Initiative and co-author of the report said, "As expectations of key stakeholders regarding risk management and oversight remain high, organizations need to offer greater transparency about the nature and magnitude of risks undertaken in executing an organization's corporate strategy." "Dynamic forces including board pressure, volatile markets, intensifying competition, changing workplace dynamics, and shifting customer preferences are leading to increasing calls for management to design and implement effective risk management capabilities and response mechanisms, to identify, assess, and manage the organization's key risk exposures," said Beasley. Given the relative riskiness of the business environment, now may be the time for boards and C-suites to closely examine how their organizations approach risk management and oversight in the digital age to pinpoint aspects requiring significant improvement. To that end, the Protiviti-NC State report includes a call to action , offering executives and directors diagnostic questions to consider when evaluating their own risk assessment and risk management processes. These diagnostic questions address five topical areas: Assessing impact of leadership and culture on our risk management process, e.g., is the organization's culture affecting how employees engage in risk management processes and conversations and, if so, how do we know? Ensuring a sufficiently robust risk management approach, e.g., is the risk management process supported by an effective, robust methodology that is definable, repeatable, and understood by key stakeholders? Evaluating whether the risk focus is sufficiently comprehensive, e.g., to what extent is the company's focus on external risks linked to geopolitical shifts, emerging disruptive innovations, and changes in macroeconomic factors? Clarifying accountabilities for managing risks, e.g., is there actionable, current risk information that is widely shared to enable more informed decision-making? Communicating an enterprise view of top risks and board risk oversight, e.g., is there a periodic board-level dialogue regarding management's appetite for risk-taking and whether the organization's risk profile is consistent with that risk appetite? The report, along with an infographic and a podcast series, are available for complimentary download here .  Article published by icrunchdata Image credit by Getty Images, Caiaimage, Andy Roberts Want more? For Job Seekers | For Employers | For Influencers
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