Blockchain Enables Digital Transformation in Retail

Distributed ledger solutions have the capability to ensure the provenance of any asset, via consensus. Blockchain could ensure that the original inspection certificates are not false and, if a problem did develop, could show that the provenance of the materials used by vendors is known.

Several retail industry applications are a perfect fit for this emerging technology. Blockchain versatility offers retailers transparency in the supply chain, customer loyalty management and operational efficiencies, among other significant benefits.

Retail Blockchain Market Development

According to the latest worldwide market study by Juniper Research, annual revenues from blockchain retail asset tracking will reach $4.5 billion by 2023.

Juniper’s new study findings uncovered that retailers can opt for different types of deployment approaches for their preferred blockchain applications.

It pointed out that some retailers -- such as Alibaba or JD.com -- are launching their own BaaS (Blockchain-as-a-Service) platforms, while other retailers -- including Walmart -- have opted to partner with specialist service providers.

Juniper forecasts that the number of retailers using blockchain in the U.S. market alone will grow by over 7,500 percent between 2018 and 2023 to reach nearly 15,000 retailers by the end of 2023.

Juniper assessed 17 blockchain vendors, scoring their level of agility, presence and innovation, on the complexity of their blockchain solutions and prospects in the field.

Juniper has ranked the 5 leading vendors in the space as follows: IBM, Digital Asset​, NEM, Applied Blockchain and R3.

According to the Juniper assessment, IBM has established itself as the leading provider of blockchain technology; combining agnostic blockchain solutions, extensive commercial deployments and high-profile partnerships.

Meanwhile, Digital Asset has built a solid customer base for which it develops tailored real-world blockchain application solutions, especially in tracking and settling financial assets.

Outlook for Blockchain Application Growth

Juniper forecasts that significant blockchain-related revenues will be achieved in three key regions -- Far East & China, North America and Western Europe.

Juniper also forecasts that countries will spend over $72 million on blockchain for land registry by 2023. Over $38 million is expected to be spent by European registries by that time; Sweden’s Lantmäteriet and HM Land Registry in the UK have already invested significantly in trial solutions.

How AI Innovation Transforms Supply Chain Planning

Business leaders that anticipate market demand opportunities or risks -- and then respond quickly in a dynamic way -- will gain a significant competitive advantage. Today, agility is a key benefit of a modern supply chain.

Global revenue from demand planning applications will generate over $8 billion by 2025, as Artificial Intelligence (AI) capabilities offered by forward-thinking IT vendors and service providers continue to improve data-driven supply chain transformation.

Supply Chain AI Market Development

According to the latest worldwide market study by ABI Research, the growing e-commerce sector and the need for supply chain AI solutions in the Asian market are also responsible for this forecasted growth.

With the volume and variety of valuable data proliferating inside and outside the typical enterprise, AI and machine learning capabilities are becoming integral to successful supply chain planning.

Only with these cognitive computing technologies can companies leverage demand sensing, which uncovers the hidden relationships between hundreds of demand drivers and their effect on actual product sales.

As AI technologies and machine learning models become increasingly sophisticated and enterprises get better at collecting complex data, demand sensing capabilities, and therefore supply chain efficiency, will improve further.

"It is becoming vital for enterprises to understand how product demand is impacted by continual shifts that occur internally in the supply chain and externally in the market," said Nick Finill, senior analyst at ABI Research.

The need for more advanced, machine learning-based demand sensing capabilities means that complex data from outside of the enterprise is very valuable. Relying exclusively on internal data, such as historical sales figures, is no longer enough in the current climate of global supply chains.

Being able to digest and analyze structured and unstructured data from the external market -- such as weather data, social media posts, and economic indicators -- will become a critical need as global supply chains transform.

Demand planning software vendors are playing a crucial role in driving innovation and a more demand-driven approach to business planning within the supply chain. Savvy vendors in this space are creating compelling products and services for companies in need of external technical expertise.

Outlook for Supply Chain AI Applications

"Forecasting demand is only half of the equation, however," said Finill. "Companies must understand how to effectively execute demand-driven planning and involve the entire business in a coordinated, holistic response that maximizes profitability for the wider enterprise."

According to the ABI assessment, companies that can make value-based operational decisions driven by reliable demand sensing capabilities will have a compelling advantage over those that can’t.

B2B Virtual Cards will Expand Global Online Payments

Despite having existed for more than a decade, virtual cards have been applied to a limited range of business cases for much of their history; primarily Business to Business (B2B) travel purchasing and commercial vehicle fleet management.

However, the benefits of card virtualization are starting to evolve outside this narrow application, which is already having an impact on adjacent sectors -- including a move by several fintech players into the business to consumer space, thereby augmenting online account security through the use of their virtual cards.

Virtual Card Market Development

According to the latest worldwide market study by Juniper Research, the annual value of virtual cards (e.g. temporary card numbers only available for a single transaction or limited time) used by businesses will grow by 90 percent over the next four years -- exceeding $1 trillion by 2022.

This is up from an estimated annual value of $568 million in 2019. However, Juniper analysts believe that the technology will struggle to establish itself among several other global online payment methods -- making up a small proportion of B2B money transfer transactions overall.

The key benefits of virtual cards are that they can be used as anti-fraud measures, as even if the card details are intercepted, they cannot be used by the fraudster.

The new market study findings note that financial services will be the fastest growing adopter of virtual cards, with transaction volumes growing at an average of 18.3 percent between 2019 and 2022.

Commercial cards are well-established in fleet businesses, but virtual card growth will be slow here due to the need for payments at a point-of-sale (POS) when purchasing fuel for vehicles.

According to the Juniper assessment, healthcare has the potential to become the highest value sector for B2B virtual cards, representing $277 billion in transactions by 2022, but adoption may be low within this sector.

As an example, the research findings anticipate that only 4 percent of healthcare institutions globally will adopt virtual cards, due to the relatively high processing charges.

Outlook for Virtual Card Application Growth

Juniper expects virtual cards for consumers to generate over $14 billion in revenues for card providers by 2022, primarily from remote purchases.

Companies offering these services are typically positioned as protecting consumers’ privacy, offering other digital ID-based services alongside their virtual cards.

"Virtual cards offer a number of financial management possibilities, for both business and consumer use," said James Moar, senior analyst at Juniper Research. "However, the limits of the technology currently mean that virtual cards need to be part of a wider payment or security product."

IT Security Solutions Spending will Reach $133.8 Billion

Cybersecurity investment continues to be a top priority for most IT organizations. Worldwide spending on security-related hardware, software, and services is forecast to reach $103.1 billion in 2019 -- that's an increase of 9.4 percent over 2018. The pace of growth will continue as industries invest heavily in IT security solutions to meet a wide range of cyber threats.

According to the latest market study by International Data Corporation (IDC), worldwide spending on IT security solutions will achieve a compound annual growth rate (CAGR) of 9.2 percent over the 2018-2022 forecast period and total $133.8 billion in 2022.

IT Security Market Development

Three industries will spend the most on security solutions in 2019 -- banking, discrete manufacturing, and federal or central government -- will invest more than $30 billion combined. Three other industries (process manufacturing, professional services, and telecommunications) will each see spending greater than $6 billion this year.

The industries that will experience the fastest spending growth over the forecast period will be state or local government (11.9 percent CAGR), telecommunications (11.8 percent CAGR), and the resource industries (11.3 percent CAGR). This spending growth will make telecommunications the fourth largest industry for security spending in 2022 while state or local government will move into the sixth position ahead of professional services.

"When examining the largest and fastest growing segments for security, we see a mix of industries – such as banking and government – that are charged with guarding highly sensitive information in regulated environments. In addition, information-based organizations like professional services firms and telcos are ramping up spending, said Jessica Goepfert, program vice president at IDC.

Managed security services will be the largest technology category in 2019 with firms spending more than $21 billion for around-the-clock monitoring and management of security operations centers. Managed security services will also be the largest category of spending for each of the top five industries this year.

The second largest technology category in 2019 will be network security hardware, which includes unified threat management, firewalls, and intrusion detection and prevention technologies. The third and fourth largest investment categories will be integration services and endpoint security software.

The technology categories that will see the fastest spending growth over the forecast will be managed security services (14.2 percent CAGR), security analytics, intelligence, response and orchestration software (10.6 percent CAGR), and network security software (9.3 percent CAGR).

From a geographic perspective, the United States will be the single largest market for IT security solutions with spending forecast to reach $44.7 billion in 2019. Two industries – discrete manufacturing and the federal government – will account for nearly 20 percent of the U.S. total.

The second largest market will be China where security purchases by three industries -- state or local government, telecommunications, and central government – will comprise 45 percent of the national total. Japan and the UK are the next two largest markets with security spending led by the consumer sector and the banking industry respectively.

Outlook for IT Security Application Growth

Large and very large businesses will be responsible for roughly two-thirds of all IT security-related spending in 2019. These two segments will also see the strongest spending growth over the forecast with CAGRs of 11.1 percent for large businesses and 9.4 percent for very large businesses.

Medium and small businesses will spend nearly $26 billion combined on IT security solutions in 2019. Across the globe, consumers are forecast to spend nearly $5.7 billion on security-related products and services this year.

Why Digital Government is Gaining New Momentum

"Artificial Intelligence (AI) promises to drive growth of the United States economy, enhance our economic and national security, and improve our quality of life. The United States is the world leader in AI research and development (R&D) and deployment." Those words are from the U.S. President's executive order issued on February 11, 2019.

Will the U.S. government's IT organizations be ready to play their part in assuring the nation's eminence in cognitive computing? Clearly, they must evolve. By 2023, about half the roles that government CIOs will oversee do not exist in government IT organizations today, according to the latest market study by Gartner.

Digital Government Market Development

Meanwhile, the transition to digital government is slowly gaining momentum. Gartner analysts also found that 53 percent of digital initiatives in government organizations have moved from the design stage to early stages of delivering digitally-driven outcomes. This is up from 40 percent last year.

Additionally, 39 percent of governments expect cloud computing services to be a technology area where they will spend the greatest amount of new or additional funding in 2019.

"These findings demonstrate that leadership has become more comfortable with cloud delivery models and has moved away from concerns regarding security and data ownership," said Cathleen Blanton, research vice president at Gartner.

The move to digital business means that government IT organizations must adapt to new skills requirements. For example, as cloud computing services become more prevalent, the number of data center management roles will decline. Furthermore, the emergence of digital business is changing how governments think about new IT services.

In the future, government IT will also accomplish more diversified tasks than today. Public sector agencies will rely on government IT services to address inclusion, citizen experience and digital ethics. Those fields require new types of skill sets such as researchers, designers and social scientists.

Government CIOs must employ experts to model and explain how citizens and businesses will need to respond to regulations and policies, and what impact that will have on society, the global networked economy and government revenue.

At the same time, government IT will need to assign new roles to support their digital transformation and introduce emerging technologies in diverse businesses and mission areas. As artificial intelligence (AI) and the Internet of Things (IoT) advance, machine learning trainers, conversational specialists and robotic process automation experts will replace the prior experts in legacy IT.

Gartner predicts that by 2023, over 80 percent of new technology solutions adopted by government agencies will be delivered and supported using an anything-as-a-service (XaaS) model.

XaaS summarizes several categories of IT, including those delivered in the cloud as a subscription-based service. It also encompasses managed desktop, help desk and network services, voice over IP and unified communications.

Adoption of XaaS models is increasing globally -- primarily driven by cloud services -- and the government is no exception. The model offers an alternative approach. It’s an effective way to scale digital government because it can provide localized offerings as well as nation-wide services.

Outlook for Government Application Innovation

The XaaS model also creates new challenges for government CIOs. In the early stages of adoption, agencies may turn less to their IT department to deliver solutions, as they are now able to acquire XaaS solutions without the involvement or the resources of traditional IT employees.

Gartner believes this is potentially dangerous, as agencies often lack the knowledge to negotiate complex contracts and individual groups may be independently acquiring duplicative capabilities already offered centrally. Furthermore, XaaS contracting is still immature and often offers weak service levels.

For this reason, CIOs must educate agency leaders about the risks associated with this type of contracting and need to take an active role in negotiating these contracts wherever possible. Without the support and experience of their IT organization, a XaaS solution can create significant risks to the government organization and the citizens it serves.

Chatbots Deliver Lasting Benefits for Financial Services

Ever since the advent of computer use by established banking and insurance organizations in the early 1950s, financial services has been a sector that generates an enormous amount of customer transaction data.

That's why they've adopted analytics tools for big data use cases, and it's why they've been one of the first sectors to pilot the deployment and applications of artificial intelligence (AI) systems.

AI Chatbot Market Development

According to the latest worldwide market study by Juniper Research, the operational cost savings from using chatbots within banking will reach $7.3 billion globally by 2023 -- that's up from an estimated $209 million savings in 2019.

This tremendous productivity improvement represents 862 million hours potentially saved for banking business operations by 2023 -- that's equivalent to nearly half a million working years.

According to the new research, chatbots can now reduce excessive operational costs in financial services organizations, by resolving customer support requests in a fully automated way.

As Natural Language Processing (NLP) capabilities evolve and domain expertise is added to AI systems, chatbots are demonstrating a proven record of end-to-end service delivery, which will drive adoption by even the most skeptical legacy financial institutions.

This anticipated productivity advancement is reflected within the forecast growth of nearly 3,150 percent in successful banking chatbot interactions conducted between 2019 and 2023.

According to the Juniper assessment, chatbot integration in mobile banking software apps will be the dominant channel for chatbot-driven customer communications, accounting for 79 percent of successful interactions during 2023.

This dominance is due to several reasons, primarily an increase in user preference for app-based banking, as well as the strong performance of early banking chatbot deployments -- such as Bank of America’s 'Erica' chatbot.

"Chatbots in banking allow heavily automated customer service, in a highly scalable way. This type of deployment can be crucial in digital transformation, allowing established banks to better compete with challenger banks," said Nick Maynard, senior analyst at Juniper Research.

Outlook for Chatbot Automation Apps

The market study also uncovered that AI, including chatbots, will have a highly disruptive impact on insurance claims management, leading to cost savings of almost $1.3 billion by 2023 -- applied across automobile, life, property and health insurance, that's up from $300 million savings in 2019.

Chatbots can automate post-incident data collection, with AI used to analyze the details or images provided using computer vision. These methods will not only save money for insurers, but they will also reduce time to claim settlement, and potentially improve customer loyalty.

How IoT Technology Drives Smart Building Innovation

Commercial buildings are getting smarter. They now include a growing variety of technologies that are part of the Internet of Things (IoT) phenomena. Across the globe, new buildings are being constructed with both wired and wireless IoT infrastructure that enables innovation.

According to the latest worldwide market study by Berg Insight, the installed base of sensors, actuators, modules, gateways and other 'connected devices' deployed as part of IoT-based automation in smart commercial buildings was an estimated 151 million units worldwide at the end of 2018.

Commercial Building Automation Market Development

Growing at a compound annual growth rate (CAGR) of 33 percent, the installed base will reach 483 million units in 2022.

About 4.5 million of these devices were connected via cellular communication networks in 2018. The number of cellular connections in the building automation market will grow at a CAGR of 44 percent to reach 19.4 million in 2022.

In terms of revenues, Berg Insight estimates that connected devices into the global building IoT market generated revenues of more than $1.2 billion in 2018. This figure will grow at a CAGR of 21 percent to almost $2.7 billion in 2022.

Berg Insight analyses the market for building automation in smart buildings along multiple verticals ranging from well-known ones such as heating, ventilation and air conditioning (HVAC), indoor lighting, fire & safety, access & security, to less known ones such as electric vehicle charging, irrigation systems and pool monitoring.

The most successful building automation solutions to date, in terms of sold units, include access and security, fire and safety, HVAC systems and elevators and escalators management.

These solutions are marketed by product OEMs such as Assa Abloy, Avigilon, AMAG Technology, HID Global, Comark, Tyco, Albireo Energy, Cimetrics, Delta Controls, ENGIE Insight, Silvair, KONE, Otis, Schindler and ThyssenKrupp.

The automatic control may be done through a centralized system such as a Building Management System (BMS). Examples of BMS solution providers include ABB, Honeywell, Johnson Controls, Schneider Electric, Siemens and United Technologies.

Building automation has been around for many decades, but there is a new urgency due to factors such as energy conservation as well as mandates for green construction, according to findings from the Berg assessment.

The latest smart building solutions leverage new technologies such as IoT, big data, cloud computing, data analytics, deep learning and artificial intelligence for the benefits of saving energy, reducing operational expenditures, increasing occupancy comfort, and meeting increasingly stringent global regulations and sustainability standards

"A major change is starting to happen now especially in new construction, where the primary driver is changing from cost reduction to features that enhance the user experience and change how users and buildings interact. Instead of there being a single killer-app, we are starting to see a combination of use-cases," said Alan Varghese, senior IoT analyst at Berg Insight.

Outlook for Smart Building Application Growth

These use-cases leverage the Internet of Things, sensors and connectivity to enable customization of spaces in offices and conference rooms based on occupancy levels and occupant preferences, efficient mobility throughout the building, and they help occupants with location and wayfinding – all controllable by mobile communication platforms.

Most important, they are capable of predictive awareness of individual needs.

'AI at the Edge' Creates New Semiconductor Demand

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.

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).

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:

• 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.