As more CIOs and CTOs focus attention on selecting the best-fit IT infrastructure for their particular cognitive computing needs, vendors of semiconductor technologies are exploring new ways to optimize their investment in solutions at the edge of enterprise networks.
Revenue from the sale of Artificial Intelligence (AI) chipsets for edge inference and inference training will grow at 65 percent and 137 percent respectively between 2018 and 2023, according to the latest worldwide market study by ABI Research.
During 2018, shipment revenues from edge AI processing reached $1.3 billion, and by 2023 this figure is forecast to reach $23 billion. While it's a massive increase, that doesn’t necessarily favor current market leaders Intel and NVIDIA.
AI Chipset Market Development
According to the ABI assessment, there will be intense vendor competition to capture this revenue between established players and several prominent startup players.
"Companies are looking to the edge because it allows them to perform AI inference without transferring their data. The act of transferring data is inherently costly and in business-critical use cases where latency and accuracy are key, and constant connectivity is lacking, applications can’t be fulfilled," said Jack Vernon, industry analyst at ABI Research.
Moreover, locating AI inference processing at the edge also means that companies don’t have to share private or sensitive data with public cloud service providers, a scenario that has proven to be problematic in the healthcare and consumer sectors.
That said, edge AI is going to have a significant impact on the semiconductor industry. The biggest winners from the growth in edge AI are going to be those vendors that either own or are currently building intellectual properties for AI-related Application-Specific Integrated Circuits (ASICs).
By 2023, it's predicted that ASICs could overtake GPUs as the architecture supporting AI inference at the edge, both in terms of annual vendor shipments and revenues.
In terms of market competition, on the AI inferencing side, Intel will be competing with several prominent AI start-ups -- such as Cambricon Technology, Horizon Robotics, Hailo Technologies, and Habana Labs -- for dominance of this market segment.
NVIDIA with its GPU-based AGX platform has also been gaining momentum in industrial automation and robotics. While FPGA leader Xilinx can also expect an uptick in revenues on the back of companies using FPGAs to perform inference at the edge, Intel as an FPGA vendor is also pushing its Movidius and Mobileye chipset.
Outlook for AI Chipset Applications Growth
For AI training, NVIDIA will hold on to its current position as the market leader. However, other AI applications at the edge will likely favor alternative vendors.
"Cloud vendors are deploying GPUs for AI training in the cloud due to their high performance. However, NVIDIA will see its market share chipped away by AI training focused ASIC vendors like Graphcore, who are building high-performance and use-case specific chipsets," concluded Vernon.
Technology | Media | Telecommunications
Tuesday, March 26, 2019
Friday, March 22, 2019
Artificial Intelligence Technology Investment will Double
According to the latest findings in the BCG report, "The Most Innovative Companies 2019" -- savvy business leaders are the early adopters of artificial intelligence (AI). "All of the ten highest-ranking companies -- and many in the top 50 -- use AI, platforms, and ecosystems to enable themselves and others to pursue new products, services, and ways of working."
Worldwide spending on AI systems is forecast to reach $35.8 billion in 2019 -- that's an increase of 44 percent over the amount invested in 2018. International Data Corporation (IDC) expects spending on AI systems will more than double to $79.2 billion in 2022 with a compound annual growth rate (CAGR) of 38 percent over the 2018-2022 forecast period.
Artificial Intelligence Market Develpment
Global spending on AI systems will be led by the retail industry where companies will invest $5.9 billion this year on solutions such as automated customer service agents and expert shopping advisors & product recommendations.
Banking will be the second largest industry with $5.6 billion going toward AI-enabled solutions including automated threat intelligence & prevention systems and fraud analysis & investigation systems. Discrete manufacturing, healthcare providers, and process manufacturing will complete the top 5 industries for AI systems spending this year.
The industries that will experience the fastest growth in AI systems spending over the 2018-2022 forecast are federal or central government (44.3 percent CAGR), personal and consumer services (43.3 percent CAGR), and education (42.9 percent CAGR).
"Significant worldwide artificial intelligence systems spend can now be seen within every industry as AI initiatives continue to optimize operations, transform the customer experience, and create new products and services", said Marianne Daquila, research manager at IDC.
This is evidenced by use cases, such as intelligent process automation, expert shopping advisors & product recommendations, and pharmaceutical research and discovery exceeding the average five-year compound annual growth of 38 percent. The continued advancement of AI-related technologies will drive double-digit year-over-year spend into the next decade.
The AI use cases that will see the most investment this year are automated customer service agents ($4.5 billion worldwide), sales process recommendation and automation ($2.7 billion), and automated threat intelligence and prevention systems ($2.7 billion).
According to the IDC assessment, five other use cases will see spending levels greater than $2 billion in 2019: automated preventative maintenance, diagnosis and treatment systems, fraud analysis and investigation, intelligent process automation, and program advisors and recommendation systems.
Enterprise software will be the largest area of AI systems spending in 2019 with nearly $13.5 billion going toward AI applications and AI software platforms. AI applications will be the fastest growing category of AI spending with a five-year CAGR of 47.3 percent.
Hardware spending, dominated by servers, will be $12.7 billion this year as companies continue to build out the infrastructure necessary to support AI systems. Companies will also invest in IT services to help with the development and implementation of their AI systems and business services such as consulting and horizontal business process outsourcing related to these systems.
By the end of the forecast period, AI-related services spending will nearly equal hardware spending. Across the globe, there is a significant upside opportunity for vendors to focus more on professional services.
Outlook for AI Market Adoption Growth
On a geographic basis, the United States will deliver nearly two thirds of all spending on AI systems in 2019, led by the retail and banking industries. Western Europe will be the second largest region in 2018, led by banking, retail, and discrete manufacturing.
The strongest spending growth over the five-year forecast will be in Japan (58.9 percent CAGR) and Asia-Pacific (excluding Japan and China) (51.4 percent CAGR). China will also experience strong spending growth throughout the forecast (49.6 percent CAGR).
Worldwide spending on AI systems is forecast to reach $35.8 billion in 2019 -- that's an increase of 44 percent over the amount invested in 2018. International Data Corporation (IDC) expects spending on AI systems will more than double to $79.2 billion in 2022 with a compound annual growth rate (CAGR) of 38 percent over the 2018-2022 forecast period.
Artificial Intelligence Market Develpment
Global spending on AI systems will be led by the retail industry where companies will invest $5.9 billion this year on solutions such as automated customer service agents and expert shopping advisors & product recommendations.
Banking will be the second largest industry with $5.6 billion going toward AI-enabled solutions including automated threat intelligence & prevention systems and fraud analysis & investigation systems. Discrete manufacturing, healthcare providers, and process manufacturing will complete the top 5 industries for AI systems spending this year.
The industries that will experience the fastest growth in AI systems spending over the 2018-2022 forecast are federal or central government (44.3 percent CAGR), personal and consumer services (43.3 percent CAGR), and education (42.9 percent CAGR).
"Significant worldwide artificial intelligence systems spend can now be seen within every industry as AI initiatives continue to optimize operations, transform the customer experience, and create new products and services", said Marianne Daquila, research manager at IDC.
This is evidenced by use cases, such as intelligent process automation, expert shopping advisors & product recommendations, and pharmaceutical research and discovery exceeding the average five-year compound annual growth of 38 percent. The continued advancement of AI-related technologies will drive double-digit year-over-year spend into the next decade.
The AI use cases that will see the most investment this year are automated customer service agents ($4.5 billion worldwide), sales process recommendation and automation ($2.7 billion), and automated threat intelligence and prevention systems ($2.7 billion).
According to the IDC assessment, five other use cases will see spending levels greater than $2 billion in 2019: automated preventative maintenance, diagnosis and treatment systems, fraud analysis and investigation, intelligent process automation, and program advisors and recommendation systems.
Enterprise software will be the largest area of AI systems spending in 2019 with nearly $13.5 billion going toward AI applications and AI software platforms. AI applications will be the fastest growing category of AI spending with a five-year CAGR of 47.3 percent.
Hardware spending, dominated by servers, will be $12.7 billion this year as companies continue to build out the infrastructure necessary to support AI systems. Companies will also invest in IT services to help with the development and implementation of their AI systems and business services such as consulting and horizontal business process outsourcing related to these systems.
By the end of the forecast period, AI-related services spending will nearly equal hardware spending. Across the globe, there is a significant upside opportunity for vendors to focus more on professional services.
Outlook for AI Market Adoption Growth
On a geographic basis, the United States will deliver nearly two thirds of all spending on AI systems in 2019, led by the retail and banking industries. Western Europe will be the second largest region in 2018, led by banking, retail, and discrete manufacturing.
The strongest spending growth over the five-year forecast will be in Japan (58.9 percent CAGR) and Asia-Pacific (excluding Japan and China) (51.4 percent CAGR). China will also experience strong spending growth throughout the forecast (49.6 percent CAGR).
Monday, March 18, 2019
Virtual Customer Assistants Transform Online Support
Savvy CIOs and CTOs at innovative retailers and other progressive organizations are piloting and deploying new cognitive technologies that enhance their customer experience. This is an acceleration of the ongoing trend that's very likely to transform legacy online support applications.
According to the latest worldwide market study by Gartner, 37 percent of customer service leaders are either piloting or using artificial intelligence (AI) bots and virtual customer assistants (VCAs), and 67 percent of those leaders believe they are high-value tools in the contact center.
Virtual Customer Assistant Market Development
In recent years, no other channel technology has piqued customer care and support leaders’ interest more than AI bots and VCAs, according to Gartner’s Technology Roadmap Survey.
In the survey of 452 service leaders across all industries and business types, respondents showed that confidence is leading more companies to adopt the technologies -- with 68 percent of service leaders reporting they believe AI bots and VCAs will be of significant importance for them and their organizations in the next two years.
"While bots and VCAs are still emergent technologies, many service leaders have been impressed with their potential. As a result, we are seeing more adoption of these technologies into service technology portfolios," said Lauren Villeneuve, senior principal advisor at Gartner.
Service organizations that are integrating these technologies -- both customer-facing and employee rep-facing systems -- into their operations are using innovation and progressive strategies to ensure the success of the technology.
AI bots and VCAs are relatively new in the customer service space, so it’s critical that companies evaluate these technologies to ensure they are the right fit for their organization and customers.
Outlook for Customer Service App Innovation
Gartner research shows that deploying bots can deliver various benefits to the contact center, including:
According to the latest worldwide market study by Gartner, 37 percent of customer service leaders are either piloting or using artificial intelligence (AI) bots and virtual customer assistants (VCAs), and 67 percent of those leaders believe they are high-value tools in the contact center.
Virtual Customer Assistant Market Development
In recent years, no other channel technology has piqued customer care and support leaders’ interest more than AI bots and VCAs, according to Gartner’s Technology Roadmap Survey.
In the survey of 452 service leaders across all industries and business types, respondents showed that confidence is leading more companies to adopt the technologies -- with 68 percent of service leaders reporting they believe AI bots and VCAs will be of significant importance for them and their organizations in the next two years.
"While bots and VCAs are still emergent technologies, many service leaders have been impressed with their potential. As a result, we are seeing more adoption of these technologies into service technology portfolios," said Lauren Villeneuve, senior principal advisor at Gartner.
Service organizations that are integrating these technologies -- both customer-facing and employee rep-facing systems -- into their operations are using innovation and progressive strategies to ensure the success of the technology.
AI bots and VCAs are relatively new in the customer service space, so it’s critical that companies evaluate these technologies to ensure they are the right fit for their organization and customers.
Outlook for Customer Service App Innovation
Gartner research shows that deploying bots can deliver various benefits to the contact center, including:
- Greater capability and scale: AI bots are best equipped to resolve the simple issues customers are interested in self-serving in the first place. This allows service reps to focus on the more complex tasks and issues customers need direct help resolving.
- Faster chat speed: AI bots can drastically reduce customer wait time. For example, one company reported their chatbots responding to customer inquiries within five seconds of customer contact, while their typical service reps take an average of 51 seconds.
- Better gatekeeping: AI bots can learn to recognize other bots trying to gain access to systems, thus freeing service reps to focus only on actual customers.
IT vendors that offer information and guidance to Line of Business (LoB) leaders and other key client influencers are likely to gain a strategic competitive advantage. Mainstream businesses are seeking self-paced learning and mentoring support so that they can upskill their team's capabilities and discover how to apply AI, machine learning and deep learning technologies.
Wednesday, March 13, 2019
International Mobile Roaming Adapts to Policy Changes
Mobile roaming allows customers of one network operator (home network) to use the network of another network operator (visited network). The visited network is normally outside the geographical coverage area of the customer’s home network.
Mobile roaming has traditionally provided network operators with an opportunity to gain additional service revenues. However, regulatory policy interventions, such as the EU law to abolish roaming in member states, is having a negative impact on roaming revenues for many network operators across the globe.
Mobile Roaming Market Development
According to the latest market study by Juniper Research, mobile network operator revenues from international mobile roaming are expected to recover slightly, following a decline in 2017 after the introduction of RLAH (Roam Like at Home) in Europe and other markets.
However, overall mobile roaming revenues are expected to stay flat over the next 4 years, representing around 6 percent of total operator billed revenues and $51 billion in value.
RLAH enables mobile communication network subscribers to use their monthly voice, data and messaging allowance while roaming -- without incurring additional service charges.
Juniper found that driven by the introduction of RLAH packages in EU and other regions such as North America and Asia-Pacific, the mobile roaming market witnessed a significant rise in data usage and internet traffic.
In 2017, Juniper estimates that mobile data traffic grew by 200 percent globally, and by 260 percent within Western Europe.
“While the overall proportion of 'silent roamers' continues to fall in many markets, driven by RLAH and cheaper bundles, the market also witnessed operators extending RLAH to more countries over the past 12-18 months. Additionally, a number of neighboring countries are announcing roam-free intra-regional agreements, similar to the EU,” said Nitin Bhas, head of research at Juniper Research.
Juniper estimated that the proportion of silent roamers not using any data roaming services in 2018 accounted for 51 percent of total data roamers globally -- that's down from 72 percent in 2013.
Outlook for Further Mobile Roaming Changes
Following Britain’s decision to leave the EU, it has been reported that, in the event of a no-deal Brexit, mobile operators will be able to implement roaming charges. Under such a scenario, Juniper expects that the average roaming cost per active UK roamer could nearly double by the end of 2022 due to higher costs.
However, Juniper considers such a situation to be unlikely and instead mobile network operators will continue to focus on other revenue streams, such as providing managed services in the Internet of Things (IoT) sector.
Mobile roaming has traditionally provided network operators with an opportunity to gain additional service revenues. However, regulatory policy interventions, such as the EU law to abolish roaming in member states, is having a negative impact on roaming revenues for many network operators across the globe.
Mobile Roaming Market Development
According to the latest market study by Juniper Research, mobile network operator revenues from international mobile roaming are expected to recover slightly, following a decline in 2017 after the introduction of RLAH (Roam Like at Home) in Europe and other markets.
However, overall mobile roaming revenues are expected to stay flat over the next 4 years, representing around 6 percent of total operator billed revenues and $51 billion in value.
RLAH enables mobile communication network subscribers to use their monthly voice, data and messaging allowance while roaming -- without incurring additional service charges.
Juniper found that driven by the introduction of RLAH packages in EU and other regions such as North America and Asia-Pacific, the mobile roaming market witnessed a significant rise in data usage and internet traffic.
In 2017, Juniper estimates that mobile data traffic grew by 200 percent globally, and by 260 percent within Western Europe.
“While the overall proportion of 'silent roamers' continues to fall in many markets, driven by RLAH and cheaper bundles, the market also witnessed operators extending RLAH to more countries over the past 12-18 months. Additionally, a number of neighboring countries are announcing roam-free intra-regional agreements, similar to the EU,” said Nitin Bhas, head of research at Juniper Research.
Juniper estimated that the proportion of silent roamers not using any data roaming services in 2018 accounted for 51 percent of total data roamers globally -- that's down from 72 percent in 2013.
Outlook for Further Mobile Roaming Changes
Following Britain’s decision to leave the EU, it has been reported that, in the event of a no-deal Brexit, mobile operators will be able to implement roaming charges. Under such a scenario, Juniper expects that the average roaming cost per active UK roamer could nearly double by the end of 2022 due to higher costs.
However, Juniper considers such a situation to be unlikely and instead mobile network operators will continue to focus on other revenue streams, such as providing managed services in the Internet of Things (IoT) sector.
Monday, March 11, 2019
Digital Factory Investment will Reach $673 Billion
The manufacturing sector will undergo a transformation as new technologies enable innovative factory automation solutions. The 'Digital Factory' market will grow at a compound annual growth rate of 33 percent to reach $673 billion in 2026, according to the latest worldwide market study by ABI Research.
These new technology investments include the actual hardware for entire industrial robots, collaborative robots, connected PLCs, intelligent industrial battery management systems, electric motors, pumps, tank management systems and smart glasses.
Digital Factory Market Development
It also includes data and analytics service, device and app platform, device interconnections, network service, professional service and security service revenues for all the above applications plus asset tracking and other equipment monitoring.
Of these applications, only asset tracking solutions include connections both on and off the factory floor.
“Currently, most manufacturing equipment still communicates in proprietary protocols and connecting it in a cost-efficient way without too much custom code often requires the expertise of Industrial Internet of Things (IIoT) integration specialists such as Telit or PTC Kepware,” said Pierce Owen, principal analyst at ABI Research.
For new factories, ABI analysts have started to see how telecom service providers and network infrastructure vendors can deploy private LTE, but so far, it only works if the plant owner has the negotiating power to demand cellular connected equipment from all its suppliers.
According to the ABI assessment, these early deployments could build trust and open new opportunities for wireless cellular technology in factories.
The automotive industry leads the way in the adoption of most digital factory technology technologies and represents the largest opportunity globally with $139 billion in digital factory revenues forecast for 2030, but this does vary somewhat country to country.
For instance, by the end of 2022, digital factory revenues in electronics manufacturing will overtake those in the automotive industry in South Korea, the fifth largest 'Smart Manufacturing' market.
Outlook for Industry Transformation Applications
“The automotive industry has demonstrated a willingness to scale transformative technologies ranging from generative design and additive manufacturing to IIoT connectivity and robotics of all kinds more than any other industry, but other industries will start to catch up over the next decade,” Owen concluded.
The companies that follow automotive OEMs’ lead first and scale technologies with proven value will gain a competitive advantage. Likewise, vendors that not only compete at the highest level in automotive but also continuously pursue new types of customers in other industries will build sustainable relationships and advantages across the sector.
These new technology investments include the actual hardware for entire industrial robots, collaborative robots, connected PLCs, intelligent industrial battery management systems, electric motors, pumps, tank management systems and smart glasses.
Digital Factory Market Development
It also includes data and analytics service, device and app platform, device interconnections, network service, professional service and security service revenues for all the above applications plus asset tracking and other equipment monitoring.
Of these applications, only asset tracking solutions include connections both on and off the factory floor.
“Currently, most manufacturing equipment still communicates in proprietary protocols and connecting it in a cost-efficient way without too much custom code often requires the expertise of Industrial Internet of Things (IIoT) integration specialists such as Telit or PTC Kepware,” said Pierce Owen, principal analyst at ABI Research.
For new factories, ABI analysts have started to see how telecom service providers and network infrastructure vendors can deploy private LTE, but so far, it only works if the plant owner has the negotiating power to demand cellular connected equipment from all its suppliers.
According to the ABI assessment, these early deployments could build trust and open new opportunities for wireless cellular technology in factories.
The automotive industry leads the way in the adoption of most digital factory technology technologies and represents the largest opportunity globally with $139 billion in digital factory revenues forecast for 2030, but this does vary somewhat country to country.
For instance, by the end of 2022, digital factory revenues in electronics manufacturing will overtake those in the automotive industry in South Korea, the fifth largest 'Smart Manufacturing' market.
Outlook for Industry Transformation Applications
“The automotive industry has demonstrated a willingness to scale transformative technologies ranging from generative design and additive manufacturing to IIoT connectivity and robotics of all kinds more than any other industry, but other industries will start to catch up over the next decade,” Owen concluded.
The companies that follow automotive OEMs’ lead first and scale technologies with proven value will gain a competitive advantage. Likewise, vendors that not only compete at the highest level in automotive but also continuously pursue new types of customers in other industries will build sustainable relationships and advantages across the sector.
Wednesday, March 06, 2019
Global Blockchain Spending will Reach $12.4 Billion
Fintech solutions that incorporate distributed ledger technology continue to gain momentum. Worldwide spending on blockchain solutions is forecast to reach $2.9 billion in 2019 -- that's an increase of 88.7 percent from the $1.5 billion spent in 2018, according to the latest study by International Data Corporation (IDC).
IDC expects global market blockchain spending to grow at a robust pace over the 2018-2022 forecast period, with a five-year compound annual growth rate (CAGR) of 76 percent and total anticipated spending of $12.4 billion in 2022.
Blockchain Market Development
"Blockchain is maturing rapidly, and we have reached an inflection point where implementations are moving quickly beyond the pilot and proof of concept phase. That is why data on the actual spend on the technology is so vital: it provides the context in which blockchain is evolving," said James Wester, research director at IDC.
Global blockchain spending will be led by the financial sector, where the banking, securities and investment services, and insurance industries will invest more than $1.1 billion combined in blockchain solutions in 2019.
The manufacturing and resources sector, driven by the discrete and process manufacturing industries, and the distribution and services sector -- led by the retail and professional services industries -- are forecast to see blockchain spending of $653 million and $642 million respectively this year.
The manufacturing and resources sector will see the fastest growth in blockchain spending over the 2018-2022 forecast with a five-year CAGR of 77.6 percent, followed closely by the distribution and services sector with a CAGR of 77.1 percent.
Cross border payments & settlements and trade finance & post-trade or transaction settlements are the two blockchain use cases that will receive the most investment ($453 million and $285 million, respectively) in 2019. The banking industry will be the largest investor in both use cases.
Manufacturing will focus much of its blockchain investment in lot lineage or provenance use cases and asset or good management use cases while identity management use cases will receive significant investments from the banking, government, and healthcare provider industries.
From a technology perspective, IT services and business services (combined) will account for nearly 70 percent of all blockchain spending in 2019 with IT services receiving additional new investment over the forecast period.
Blockchain platform software will be the largest segment of spending outside of the services category and the second fastest growing category overall with a five-year CAGR of 81.2 percent, following IT services with a CAGR of 82.8 percent.
The United States will be the geographic region that will see the largest investment in blockchain applications during 2019 ($1.1 billion), followed by Western Europe ($674 million) and China ($319 million).
Outlook for Blockchain Applications Growth
According to the IDC assessment, blockchain has proven to remove a layer of uncertainty from a multifaceted ecosystem built on digital trust. In many use cases, incorporating blockchain into the mix has been better than the prior status quo.
With enterprises trying to find a balance between decentralizing their business processes while bringing common standards to the blockchain space, the future state of the blockchain world relies on collaboration and building bridges between organizations and communities.
In summary, IDC believes that 2019 will be a year of mainstream adoption for blockchain applications, but will rely heavily on reshaping the ideology of a distributed ledger revolution.
IDC expects global market blockchain spending to grow at a robust pace over the 2018-2022 forecast period, with a five-year compound annual growth rate (CAGR) of 76 percent and total anticipated spending of $12.4 billion in 2022.
Blockchain Market Development
"Blockchain is maturing rapidly, and we have reached an inflection point where implementations are moving quickly beyond the pilot and proof of concept phase. That is why data on the actual spend on the technology is so vital: it provides the context in which blockchain is evolving," said James Wester, research director at IDC.
Global blockchain spending will be led by the financial sector, where the banking, securities and investment services, and insurance industries will invest more than $1.1 billion combined in blockchain solutions in 2019.
The manufacturing and resources sector, driven by the discrete and process manufacturing industries, and the distribution and services sector -- led by the retail and professional services industries -- are forecast to see blockchain spending of $653 million and $642 million respectively this year.
The manufacturing and resources sector will see the fastest growth in blockchain spending over the 2018-2022 forecast with a five-year CAGR of 77.6 percent, followed closely by the distribution and services sector with a CAGR of 77.1 percent.
Cross border payments & settlements and trade finance & post-trade or transaction settlements are the two blockchain use cases that will receive the most investment ($453 million and $285 million, respectively) in 2019. The banking industry will be the largest investor in both use cases.
Manufacturing will focus much of its blockchain investment in lot lineage or provenance use cases and asset or good management use cases while identity management use cases will receive significant investments from the banking, government, and healthcare provider industries.
From a technology perspective, IT services and business services (combined) will account for nearly 70 percent of all blockchain spending in 2019 with IT services receiving additional new investment over the forecast period.
Blockchain platform software will be the largest segment of spending outside of the services category and the second fastest growing category overall with a five-year CAGR of 81.2 percent, following IT services with a CAGR of 82.8 percent.
The United States will be the geographic region that will see the largest investment in blockchain applications during 2019 ($1.1 billion), followed by Western Europe ($674 million) and China ($319 million).
Outlook for Blockchain Applications Growth
According to the IDC assessment, blockchain has proven to remove a layer of uncertainty from a multifaceted ecosystem built on digital trust. In many use cases, incorporating blockchain into the mix has been better than the prior status quo.
With enterprises trying to find a balance between decentralizing their business processes while bringing common standards to the blockchain space, the future state of the blockchain world relies on collaboration and building bridges between organizations and communities.
In summary, IDC believes that 2019 will be a year of mainstream adoption for blockchain applications, but will rely heavily on reshaping the ideology of a distributed ledger revolution.
Monday, March 04, 2019
Enterprise Demand for Agile, Data-Centric Architectures
Augmented analytics, continuous intelligence and explainable artificial intelligence (AI) are among the top trends in big data and analytics that have significant disruptive potential over the next three to five years, according to the latest worldwide market study by Gartner.
"The size, complexity, distributed nature of data, speed of action and the continuous intelligence required by digital business means that rigid and centralized architectures and tools break down,” said Donald Feinberg, vice president at Gartner. “The continued survival of any business will depend upon an agile, data-centric architecture that responds to the constant rate of change."
Gartner recommends that data and analytics leaders collaborate with senior business leaders about their critical business priorities and explore the ten top related trends.
Augmented Analytics
Augmented analytics is the next wave of disruption in the data and analytics market. It uses machine learning (ML) and AI techniques to transform how analytics content is developed, consumed and shared.
By 2020, augmented analytics will be a dominant driver of new purchases of analytics and business intelligence (BI), as well as data science and ML platforms, and of embedded analytics. Data and analytics leaders should plan to adopt augmented analytics as platform capabilities mature.
Augmented Data Management
Augmented data management leverages ML capabilities and AI engines to make enterprise information management categories including data quality, metadata management, master data management, data integration as well as database management systems (DBMSs) self-configuring and self-tuning.
It is automating many of the manual tasks and allows less technically skilled users to be more autonomous using data. It also allows highly skilled technical resources to focus on higher value tasks.
Augmented data management converts metadata from being used for audit, lineage and reporting only, to powering dynamic systems. Metadata is changing from passive to active and is becoming the primary driver for all AI and ML.
Through to the end of 2022, data management manual tasks will be reduced by 45 percent through the addition of ML and automated service-level management.
Continuous Intelligence
By 2022, more than half of major new business systems will incorporate continuous intelligence that uses real-time context data to improve decisions.
Continuous intelligence is a design pattern in which real-time analytics are integrated within a business operation, processing current and historical data to prescribe actions in response to events. It provides decision automation or decision support.
Continuous intelligence leverages multiple technologies such as augmented analytics, event stream processing, optimization, business rule management and ML.
Explainable AI
AI models are increasingly deployed to augment and replace human decision making. However, in some scenarios, businesses must justify how these models arrive at their decisions. To build trust with users and stakeholders, application leaders must make these models more interpretable and explainable.
Unfortunately, most of these advanced AI models are complex black boxes that are not able to explain why they reached a specific recommendation or a decision. Explainable AI in data science and ML platforms, for example, auto-generates an explanation of models in terms of accuracy, attributes, model statistics and features in natural language.
Graph Analytics
Graph analytics is a set of analytic techniques that allow for the exploration of relationships between entities of interest such as organizations, people and transactions.
The application of graph processing and graph DBMSs will grow at 100 percent annually through 2022 to continuously accelerate data preparation and enable more complex and adaptive data science.
Graph data stores can efficiently model, explore and query data with complex interrelationships across data silos, but the need for specialized skills has limited their adoption to date.
Graph analytics will grow in the next few years due to the need to ask complex questions across complex data, which is not always practical or even possible at scale using SQL queries.
Data Fabric
Data fabric enables frictionless access and sharing of data in a distributed data environment. It enables a single and consistent data management framework, which allows seamless data access and processing by design across otherwise siloed storage.
Through 2022, bespoke data fabric designs will be deployed primarily as a static infrastructure, forcing organizations into a new wave of cost to completely re-design for more dynamic data mesh approaches.
NLP Conversational Analytics
By 2020, 50 percent of analytical queries will be generated via search, natural language processing (NLP) or voice, or will be automatically generated. The need to analyze complex combinations of data and to make analytics accessible to everyone in the organization will drive broader adoption, allowing analytics tools to be as easy as a search interface or a conversation with a virtual assistant.
Commercial AI and ML
Gartner predicts that by 2022, 75 percent of new end-user solutions leveraging AI and ML techniques will be built with commercial solutions rather than open source platforms.
Commercial vendors have now built connectors into the Open Source ecosystem and they provide the enterprise features necessary to scale and democratize AI and ML, such as project & model management, reuse, transparency, data lineage, and platform cohesiveness and integration that Open Source technologies lack.
Blockchains
The core value proposition of blockchain and distributed ledger technologies is providing decentralized trust across a network of untrusted participants. The potential ramifications for analytics use cases are significant, especially those leveraging participant relationships and interactions.
It will be several years before four or five major blockchain technologies become dominant. Until then, technology end users will be forced to integrate with the blockchain technologies and standards dictated by their dominant customers or networks. This includes integration with your existing data and analytics infrastructure.
The costs of integration may outweigh any potential benefit. Blockchains are a data source, not a database, and will not replace existing data management technologies.
Persistent Memory Servers
New persistent-memory technologies will help reduce costs and complexity of adopting in-memory computing (IMC)-enabled architectures. Persistent memory represents a new memory tier between DRAM and NAND flash memory that can provide cost-effective mass memory for high-performance workloads.
It has the potential to improve application performance, availability, boot times, clustering methods and security practices while keeping costs under control. It will also help organizations reduce the complexity of their application and data architectures by decreasing the need for data duplication.
"The size, complexity, distributed nature of data, speed of action and the continuous intelligence required by digital business means that rigid and centralized architectures and tools break down,” said Donald Feinberg, vice president at Gartner. “The continued survival of any business will depend upon an agile, data-centric architecture that responds to the constant rate of change."
Gartner recommends that data and analytics leaders collaborate with senior business leaders about their critical business priorities and explore the ten top related trends.
Augmented Analytics
Augmented analytics is the next wave of disruption in the data and analytics market. It uses machine learning (ML) and AI techniques to transform how analytics content is developed, consumed and shared.
By 2020, augmented analytics will be a dominant driver of new purchases of analytics and business intelligence (BI), as well as data science and ML platforms, and of embedded analytics. Data and analytics leaders should plan to adopt augmented analytics as platform capabilities mature.
Augmented Data Management
Augmented data management leverages ML capabilities and AI engines to make enterprise information management categories including data quality, metadata management, master data management, data integration as well as database management systems (DBMSs) self-configuring and self-tuning.
It is automating many of the manual tasks and allows less technically skilled users to be more autonomous using data. It also allows highly skilled technical resources to focus on higher value tasks.
Augmented data management converts metadata from being used for audit, lineage and reporting only, to powering dynamic systems. Metadata is changing from passive to active and is becoming the primary driver for all AI and ML.
Through to the end of 2022, data management manual tasks will be reduced by 45 percent through the addition of ML and automated service-level management.
Continuous Intelligence
By 2022, more than half of major new business systems will incorporate continuous intelligence that uses real-time context data to improve decisions.
Continuous intelligence is a design pattern in which real-time analytics are integrated within a business operation, processing current and historical data to prescribe actions in response to events. It provides decision automation or decision support.
Continuous intelligence leverages multiple technologies such as augmented analytics, event stream processing, optimization, business rule management and ML.
Explainable AI
AI models are increasingly deployed to augment and replace human decision making. However, in some scenarios, businesses must justify how these models arrive at their decisions. To build trust with users and stakeholders, application leaders must make these models more interpretable and explainable.
Unfortunately, most of these advanced AI models are complex black boxes that are not able to explain why they reached a specific recommendation or a decision. Explainable AI in data science and ML platforms, for example, auto-generates an explanation of models in terms of accuracy, attributes, model statistics and features in natural language.
Graph Analytics
Graph analytics is a set of analytic techniques that allow for the exploration of relationships between entities of interest such as organizations, people and transactions.
The application of graph processing and graph DBMSs will grow at 100 percent annually through 2022 to continuously accelerate data preparation and enable more complex and adaptive data science.
Graph data stores can efficiently model, explore and query data with complex interrelationships across data silos, but the need for specialized skills has limited their adoption to date.
Graph analytics will grow in the next few years due to the need to ask complex questions across complex data, which is not always practical or even possible at scale using SQL queries.
Data Fabric
Data fabric enables frictionless access and sharing of data in a distributed data environment. It enables a single and consistent data management framework, which allows seamless data access and processing by design across otherwise siloed storage.
Through 2022, bespoke data fabric designs will be deployed primarily as a static infrastructure, forcing organizations into a new wave of cost to completely re-design for more dynamic data mesh approaches.
NLP Conversational Analytics
By 2020, 50 percent of analytical queries will be generated via search, natural language processing (NLP) or voice, or will be automatically generated. The need to analyze complex combinations of data and to make analytics accessible to everyone in the organization will drive broader adoption, allowing analytics tools to be as easy as a search interface or a conversation with a virtual assistant.
Commercial AI and ML
Gartner predicts that by 2022, 75 percent of new end-user solutions leveraging AI and ML techniques will be built with commercial solutions rather than open source platforms.
Commercial vendors have now built connectors into the Open Source ecosystem and they provide the enterprise features necessary to scale and democratize AI and ML, such as project & model management, reuse, transparency, data lineage, and platform cohesiveness and integration that Open Source technologies lack.
Blockchains
The core value proposition of blockchain and distributed ledger technologies is providing decentralized trust across a network of untrusted participants. The potential ramifications for analytics use cases are significant, especially those leveraging participant relationships and interactions.
It will be several years before four or five major blockchain technologies become dominant. Until then, technology end users will be forced to integrate with the blockchain technologies and standards dictated by their dominant customers or networks. This includes integration with your existing data and analytics infrastructure.
The costs of integration may outweigh any potential benefit. Blockchains are a data source, not a database, and will not replace existing data management technologies.
Persistent Memory Servers
New persistent-memory technologies will help reduce costs and complexity of adopting in-memory computing (IMC)-enabled architectures. Persistent memory represents a new memory tier between DRAM and NAND flash memory that can provide cost-effective mass memory for high-performance workloads.
It has the potential to improve application performance, availability, boot times, clustering methods and security practices while keeping costs under control. It will also help organizations reduce the complexity of their application and data architectures by decreasing the need for data duplication.
Friday, March 01, 2019
Why Mobile Payments and Fintech Disrupt eCommerce
Fintech innovation continues to disrupt the Global Networked Economy. The value of consumer spending on remote payments for digital and physical goods is estimated to have surpassed $3.3 trillion in 2018 -- that's up 10 percent on the 2017 total of $3 trillion.
A recent worldwide market study by Juniper Research found PayPal already accounts for 20 percent of all transactions made outside China, while the success of Alipay and Weixin Pay within China means that these two players combined now account for 45 percent of global payment volumes.
Mobile Payments Market Development
Mobile payments impact on eCommerce’s growth cannot be overestimated. The emergence of an app-based economy in the wake of Apple’s App Store launch in 2008 made many online retailers -- such as Amazon, eBay and Alibaba -- recognize the channel’s potential.
When digital and physical goods are taken together, mobile devices (including media tablets) are expected to account for nearly 51 percent of online transactions by value in 2018, a figure that rises to 68 percent in China.
The window of opportunity in the U.S. market for mobile payment providers like Apple Pay and Google Pay is closing fast. Despite high levels of support from retailers, only 14 percent of U.S. respondents currently use OEM-Pay (payment services provided by smartphone vendors) for in-store purchases.
Future growth is likely to be threatened by increasing deployments of contactless cards in the U.S. market, with Chase becoming the latest major bank to announce contactless Visa rollouts.
“Time is running out for OEM-Pay providers to establish a dominant position in the US,” said James Moar, senior analyst at Juniper Research. “Many of mobile payment’s benefits, like increased transaction speed, are not exclusive to smartphones, and our survey shows that the majority of users who have not adopted OEM-Pay are more interested in services like contactless cards than mobile-based payments.”
Juniper’s survey findings also confirm that online shopping is having a detrimental effect on physical retailers. Forty percent of survey respondents in both the U.S. and the UK report that they shop less in stores due to using online and mobile commerce.
In addition, the trend of ‘showrooming’, looking at physical goods in stores and then checking prices online was reported by 24 percent of UK survey respondents and 13 percent of U.S. respondents.
Outlook for Mobile Fintech Innovation
However, while mCommerce is a zero-sum game in the UK, with few users increasing overall retail spending, it may open up new retail opportunities in the U.S. market. Thirty percent of respondents report shopping more overall due to their use of mCommerce, not merely shopping more online.
Additionally, the survey shows that continued reliance on browser-based online purchasing is perpetuating non-biometric authentication methods, like passwords or PINs, presenting an ongoing security problem. Regardless, the future of mobile fintech innovation looks promising.
A recent worldwide market study by Juniper Research found PayPal already accounts for 20 percent of all transactions made outside China, while the success of Alipay and Weixin Pay within China means that these two players combined now account for 45 percent of global payment volumes.
Mobile Payments Market Development
Mobile payments impact on eCommerce’s growth cannot be overestimated. The emergence of an app-based economy in the wake of Apple’s App Store launch in 2008 made many online retailers -- such as Amazon, eBay and Alibaba -- recognize the channel’s potential.
When digital and physical goods are taken together, mobile devices (including media tablets) are expected to account for nearly 51 percent of online transactions by value in 2018, a figure that rises to 68 percent in China.
The window of opportunity in the U.S. market for mobile payment providers like Apple Pay and Google Pay is closing fast. Despite high levels of support from retailers, only 14 percent of U.S. respondents currently use OEM-Pay (payment services provided by smartphone vendors) for in-store purchases.
Future growth is likely to be threatened by increasing deployments of contactless cards in the U.S. market, with Chase becoming the latest major bank to announce contactless Visa rollouts.
“Time is running out for OEM-Pay providers to establish a dominant position in the US,” said James Moar, senior analyst at Juniper Research. “Many of mobile payment’s benefits, like increased transaction speed, are not exclusive to smartphones, and our survey shows that the majority of users who have not adopted OEM-Pay are more interested in services like contactless cards than mobile-based payments.”
Juniper’s survey findings also confirm that online shopping is having a detrimental effect on physical retailers. Forty percent of survey respondents in both the U.S. and the UK report that they shop less in stores due to using online and mobile commerce.
In addition, the trend of ‘showrooming’, looking at physical goods in stores and then checking prices online was reported by 24 percent of UK survey respondents and 13 percent of U.S. respondents.
Outlook for Mobile Fintech Innovation
However, while mCommerce is a zero-sum game in the UK, with few users increasing overall retail spending, it may open up new retail opportunities in the U.S. market. Thirty percent of respondents report shopping more overall due to their use of mCommerce, not merely shopping more online.
Additionally, the survey shows that continued reliance on browser-based online purchasing is perpetuating non-biometric authentication methods, like passwords or PINs, presenting an ongoing security problem. Regardless, the future of mobile fintech innovation looks promising.
Thursday, February 21, 2019
ICT Infrastructure Investment will Reach $4.6 Trillion
Business spending on information and communication technologies (ICT) may evolve over the next five years as the global economy puts pressure on organizations to increase technology investment because growth and competitiveness are increasingly dependent upon digital transformation, artificial intelligence (AI), and data analytics leadership.
Worldwide ICT spending on hardware, software, services and telecommunications will reach $4.6 trillion by 2022, representing average growth of 4 percent per year. Commercial customers will represent around 63.5 percent of total spending by 2022 ($2.9 trillion), while consumers will still account for 36.5 percent ($1.7 trillion), according to the latest market study by International Data Corporation (IDC).
Global ICT Market Development
Consumer spending growth will lag behind business and government spending due to increasing saturation in smartphones and media tablets. The fastest growth will come from the professional services segment (7 percent), including cloud and digital service providers, which will account for a rapidly increasing share of overall technology spending.
Other fast-growing segments include media (+6 percent), banking (+5 percent), retail (+5 percent), and manufacturing (+5 percent), while the slowest growth in commercial technology budgets will come from federal government, followed by wholesale and construction firms.
"In the short term, the trade war between the U.S. and China continues to add volatility to the outlook," said Stephen Minton, vice president at IDC. "Some firms are also facing the double whammy of weaker sales in China, an increasingly important export market for the manufacturing industry. Meanwhile, the impact in China itself could persist over a longer period of time, with manufacturing and financial services firms being the most exposed."
Countering negative sentiment around the economy in China is increasing demand for ICT solutions related to digital transformation. This is driving major investments by large enterprise and state-owned customers in industries such as retail, manufacturing, healthcare, and financial services, especially around cloud and AI.
In fact, digital transformation is also driving technology investment within Europe.
Companies in Western Europe are looking to embrace new technologies like AI and robotics to improve their business processes, also they are adopting more customer-centric approaches to IT spending decisions. This is especially true in customer-facing industries like retail, banking, transportation, and telecommunications.
Overall growth in Western Europe will slightly lag emerging markets in Asia-Pacific over the forecast period, but the U.S. market is set to post some of the strongest growth rates in spite of its relative maturity.
According to the IDC assessment, business investments in digital transformation, cloud, and AI will help drive overall U.S. growth of 4.5 percent over the forecast, equaling Latin America as the second fastest growing region for total ICT spending after China.
Outlook for Technology Applications Growth
"In the U.S., the professional services industry is expected to continue with strong technology growth and investments. The appetite for cloud-based delivery, new apps, and tech-fueled services show no signs of slowing, and thus we are optimistic about the growth opportunity for this industry," said Jessica Goepfert, vice president at IDC.
Consumer-driven industries such as retail and hospitality are benefitting from higher wages and disposable incomes. In response, firms in this space are working to develop and deliver unforgettable customer interactions. This takes shape as customizable experiences and infusing technology into their operations. For instance, hotels are implementing technology in guest rooms that can be controlled by mobile apps.
Worldwide ICT spending on hardware, software, services and telecommunications will reach $4.6 trillion by 2022, representing average growth of 4 percent per year. Commercial customers will represent around 63.5 percent of total spending by 2022 ($2.9 trillion), while consumers will still account for 36.5 percent ($1.7 trillion), according to the latest market study by International Data Corporation (IDC).
Global ICT Market Development
Consumer spending growth will lag behind business and government spending due to increasing saturation in smartphones and media tablets. The fastest growth will come from the professional services segment (7 percent), including cloud and digital service providers, which will account for a rapidly increasing share of overall technology spending.
Other fast-growing segments include media (+6 percent), banking (+5 percent), retail (+5 percent), and manufacturing (+5 percent), while the slowest growth in commercial technology budgets will come from federal government, followed by wholesale and construction firms.
"In the short term, the trade war between the U.S. and China continues to add volatility to the outlook," said Stephen Minton, vice president at IDC. "Some firms are also facing the double whammy of weaker sales in China, an increasingly important export market for the manufacturing industry. Meanwhile, the impact in China itself could persist over a longer period of time, with manufacturing and financial services firms being the most exposed."
Countering negative sentiment around the economy in China is increasing demand for ICT solutions related to digital transformation. This is driving major investments by large enterprise and state-owned customers in industries such as retail, manufacturing, healthcare, and financial services, especially around cloud and AI.
In fact, digital transformation is also driving technology investment within Europe.
Companies in Western Europe are looking to embrace new technologies like AI and robotics to improve their business processes, also they are adopting more customer-centric approaches to IT spending decisions. This is especially true in customer-facing industries like retail, banking, transportation, and telecommunications.
Overall growth in Western Europe will slightly lag emerging markets in Asia-Pacific over the forecast period, but the U.S. market is set to post some of the strongest growth rates in spite of its relative maturity.
According to the IDC assessment, business investments in digital transformation, cloud, and AI will help drive overall U.S. growth of 4.5 percent over the forecast, equaling Latin America as the second fastest growing region for total ICT spending after China.
Outlook for Technology Applications Growth
"In the U.S., the professional services industry is expected to continue with strong technology growth and investments. The appetite for cloud-based delivery, new apps, and tech-fueled services show no signs of slowing, and thus we are optimistic about the growth opportunity for this industry," said Jessica Goepfert, vice president at IDC.
Consumer-driven industries such as retail and hospitality are benefitting from higher wages and disposable incomes. In response, firms in this space are working to develop and deliver unforgettable customer interactions. This takes shape as customizable experiences and infusing technology into their operations. For instance, hotels are implementing technology in guest rooms that can be controlled by mobile apps.
Monday, February 18, 2019
Channel Partners will Drive New Cloud Computing Growth
The worldwide cloud computing infrastructure market had another strong quarter in Q4 2018, as spending grew 46 percent to nearly $23 billion. The total outlay on cloud infrastructure in 2018 exceeded $80 billion -- that's up from $55 billion in 2017 according to that latest market study by Canalys.
This investment makes cloud computing services one of the most important sectors in the IT industry, not just by the rate of growth, but also due to its expanding size.
Cloud Computing Infrastructure Market Development
Amazon Web Services (AWS) remained the dominant cloud service provider in Q4 2018; its market share of customer spend unchanged at 32 percent. Microsoft Azure grew its share to 16 percent against 14 percent in the same period a year ago. Google Cloud reached 9 percent for the first time, while Alibaba Cloud maintained its 4 percent share.
IBM, Salesforce, Oracle, NTT Communications, Tencent Cloud and OVH rounded out the top 10 cloud service providers.
"Cloud infrastructure services provide the core components needed to support digital transformation initiatives around building new customer experiences, deploying IoT to transform processes, using big data and analytics for better insights, and embedding machine learning and AI for automation,” said Matthew Ball, principal analyst at Canalys.
Market dynamics have changed over the last 12 months, with more businesses opting for multi-cloud and hybrid IT environments to use the strengths of different cloud service providers and deployment models dependent on application and data requirements, compliance, cost and performance.
The role of channel partners in cloud services is growing in importance as a direct result of these trends. In particular, understanding customer requirements, recommending services, deployment and integration, as well as simplifying the billing and management of multiple cloud services.
According to the Canalys assessment, cloud service providers are placing greater emphasis on building channel programs to support the growing network of partners beyond the largest systems integrators, especially as they extend to mid-market and SMB customers.
Canalys expects the share of cloud business supported by or with channel partners to increase in 2019. Cloud service providers must therefore find new ways to improve their own differentiation to partners and raise the maturity of their channel models.
Outlook for Cloud Channel Partner Innovation
Canalys expects a greater focus on rewarding partners with specialist expertise around specific cloud deployments, such as SAP HANA, analytics or security; on partners developing unique services on top of cloud; and on those driving customer adoption of cloud services.
Cloud service providers should build trust with their channel partners and not implement initiatives or change terms and conditions that drive more direct sales, according to Canalys. Instead, they must offer superior marketing resources that enable channel partners to differentiate hybrid multi-cloud service capabilities in this very competitive marketplace.
This investment makes cloud computing services one of the most important sectors in the IT industry, not just by the rate of growth, but also due to its expanding size.
Cloud Computing Infrastructure Market Development
Amazon Web Services (AWS) remained the dominant cloud service provider in Q4 2018; its market share of customer spend unchanged at 32 percent. Microsoft Azure grew its share to 16 percent against 14 percent in the same period a year ago. Google Cloud reached 9 percent for the first time, while Alibaba Cloud maintained its 4 percent share.
IBM, Salesforce, Oracle, NTT Communications, Tencent Cloud and OVH rounded out the top 10 cloud service providers.
"Cloud infrastructure services provide the core components needed to support digital transformation initiatives around building new customer experiences, deploying IoT to transform processes, using big data and analytics for better insights, and embedding machine learning and AI for automation,” said Matthew Ball, principal analyst at Canalys.
Market dynamics have changed over the last 12 months, with more businesses opting for multi-cloud and hybrid IT environments to use the strengths of different cloud service providers and deployment models dependent on application and data requirements, compliance, cost and performance.
The role of channel partners in cloud services is growing in importance as a direct result of these trends. In particular, understanding customer requirements, recommending services, deployment and integration, as well as simplifying the billing and management of multiple cloud services.
According to the Canalys assessment, cloud service providers are placing greater emphasis on building channel programs to support the growing network of partners beyond the largest systems integrators, especially as they extend to mid-market and SMB customers.
Canalys expects the share of cloud business supported by or with channel partners to increase in 2019. Cloud service providers must therefore find new ways to improve their own differentiation to partners and raise the maturity of their channel models.
Outlook for Cloud Channel Partner Innovation
Canalys expects a greater focus on rewarding partners with specialist expertise around specific cloud deployments, such as SAP HANA, analytics or security; on partners developing unique services on top of cloud; and on those driving customer adoption of cloud services.
Cloud service providers should build trust with their channel partners and not implement initiatives or change terms and conditions that drive more direct sales, according to Canalys. Instead, they must offer superior marketing resources that enable channel partners to differentiate hybrid multi-cloud service capabilities in this very competitive marketplace.
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