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  • Why data security is now a top concern for IT leaders

    The ability to use artificial intelligence effectively is also a large concern for IT decision makers.

    T leaders face a range of challenges, but data security ranks as the no. 1 concern, according to a Tuesday survey from Adobe.

    Among the 1,000 US IT decision makers polled, 47% put data security at the top of their list of priorities. Respondents pointed to such challenges as making sure that data is secure, that customers can act upon it, and that it can easily flow through the myriad systems that organizations have in place.

    While organizations are focusing on data security, other data management issues remain. Grappling with the huge avalanche of data available in their organizations naturally seems like a top challenge. But another aspect of data management scored higher as a challenge among the IT leaders polled.

    “Surprisingly, having too much data is one of the least-cited challenges; actually using the data effectively is a much more important issue,” Ronell Hugh, head of product strategy and marketing for Adobe Experience Platform, said in a press release.

    A full 63% of those surveyed said they’ve been successful at integrating different data sources, 59% said they’ve been able to clean their data to reduce inaccuracies, and 59% said they’re able to use the data effectively to personalize it for their customers.

    Artificial intelligence (AI) and machine learning were next on the list. Almost 90% of those polled said they envision an increase in the use of AI and machine learning in their future. But 40% cited the ability to implement AI as a top concern. The survey revealed a disconnect in AI between IT teams and the business side at many organizations, with only around half of the IT leaders surveyed expressing positive feedback about the effectiveness of their current AI and machine learning solutions.

    Improving the customer experience

    AI and machine learning were cited by 41% of those polled as providing the most value in improving the customer experience. Other technologies seen as improving CX were the Internet of Things (IoT), voice, immersive technologies including virtual and augmented realities, and chatbot technology.

    Among many organizations, IT teams and the business side seem to be working together as true partners. Some 53% of the IT leaders surveyed said they collaborate with their customers on both the vision and implementation of technology. Of the rest, 27% said the business side envisions technology solutions and works with IT to implement them, while 18% said that IT decides on the right technologies with input from the business side.

    Overall, 95% of the IT leaders expressed optimism about their ability to positively affect their customers, and 69% said they believe they have the right tools and systems to create personalized experiences for their customers.

    “IT decision makers have a firm seat at the table,” Hugh said in the release. “They feel that they are a strategic partner to other lines of the business, and most often they feel their department is organized in a way that enables their teams to support improved customer experiences.”



  • Artificial Intelligence In Automotive Industry: Surprisingly Slow Uptake And Missed Opportunities

    The automotive industry is one of the most high-tech industries in the world – so a headline finding in a report published this week was, on the face of it, somewhat surprising.

    Capgemini’s report – Accelerating Automotive’s AI Transformation – found that during 2018, the number of companies in the industry deploying AI “at scale” grew only marginally by 3%.

    This reflected that just 10% of respondents surveyed said that their organizations were deploying AI-driven initiatives across the entirety of its operations “with full scope and scale,” during 2018, compared to 7% in 2017.

    The relatively slow pace of growth is evidence that “the industry has not made significant progress in AI-driven transformation since 2017”, the report concludes – a surprising finding given the scale of investment and enthusiasm shown by industry leaders.

    I spoke to one of the report’s authors, Capgemini’s Ingo Finck, who told me “To an extent, I did find this surprising, because from the discussions we’ve been having with these companies we see that the vast majority – more than 80% – mention AI in their core strategy.

    “It’s clearly a strategic factor for them, so yes … we were surprised by the relatively slow growth rate.”

    Before we start delving into the possible reasons for this slow uptake, it’s worth noting that there is a key geographic variation: In China, the number of automotive companies working at scale with AI almost doubled, from 5% to 9%.

    This is explained to some extent by the comparatively “open” approach taken by China’s AI giants, such as Baidu’s development of the open source Apollo platform. This has involved it partnering with over 130 other businesses and organizations.

    Finck explains that the slow growth demonstrated in other regions could be down to the fact that organizations are taking a more mature approach to AI deployment. This might mean they are moving away from “try everything and see what works” methodologies, towards focusing on proven use cases that can then be scaled.

    Another disparity is apparent when we consider the sizes of the businesses that are reporting growth in AI deployments.

    “We can see that the smaller companies are struggling more with AI – whereas with larger companies [with revenue of $10 billion plus] the adoption rate is higher.

    “The way we interpret this is that the complexities in small companies are almost the same as they are in large companies – many of the difficulties in applying AI are the same across small and large organizations.”

    In fact, there’s a clear correlation, as would be expected, between the amount of money invested and the scale of an organization’s AI deployments. This is clearly a limiting factor for smaller players in the industry.

    Of those that have successfully deployed at scale, 80% have done so by spending more than $200 million on AI. Of those that judge themselves not to have successfully deployed at scale, just 20% have spent that amount.

    While self-driving, autonomous cars are often talked about as the “headline” use case for AI in automotive, today’s reality is that cognitive learning algorithms are mainly being used to increase efficiency and add value to processes revolving around traditional, manually-driven vehicles.

    Significant AI deployments highlighted by the report, mostly at larger OEM organizations, include:

    • Prototyping – General Motors uses machine learning in their product design operations.
    • Modeling and simulation – as used by Continental to gather 5,000 miles of virtual vehicle test data per hour.
    • Sales and marketing – Volkswagen uses machine learning to predict sales of 250 car models across 120 countries, using economic, political and meteorological data.
    • Quality control – Audi uses computer vision-equipped cameras to detect tiny cracks in sheet metal used in its manufacturing processes, which would not be visible to human eyes.

    These companies fall into a category that Capgemini defines as “scale champions” – they have successfully deployed AI at scale, and all tend to display a number of characteristics – a focus on high benefit use cases, good AI governance, significant levels of investment and, importantly, show a willingness to “upskill” employees.

    “We’ve learned that AI is most effective when it comes as a human/machine combination,” Finck tells me.

    “In the same way that you improve your AI capabilities, you also have to upskill and educate your staff. That’s more than just training or hiring a few more data scientists. It’s about educating the rest of the organization – the casual user of AI.”

    All of these challenges go some way to explaining the slower than may have been expected adoption of AI across the industry. One thing Finck is certain of, and which is borne out by the report’s broader findings, is that AI has a key role to play in the industry’s future.

    He says “I think companies understand that it’s far more than just a ‘plug-in’ technology – it’s a core technology that they have to adopt – like the engine, or information technology. The challenge is embracing this technology across not just the product, but also the service, and the organization.”

    Capgemini’s full report, Accelerating Automotive’s AI



  • CFOs and CIOs must collaborate on digital transformation to remain competitive

    CFOs are shifting their priorities from cutting costs to rapidly investing in technology and data.

    Significant percentages of senior financial executives currently implement technologies such as advanced analytics (38 percent) and machine learning (30 percent), while many plan to dedicate additional resources to frontier technologies within two years, including:

    • Artificial intelligence, or AI (41 percent)
    • Drones and robots (30 percent)
    • Blockchain (40 percent)
    • Robotic process automation, or RPA (41 percent).

    In addition, financial leaders plan to speed up their efforts to implement several popular technologies within the next two years, including optical character recognition (45 percent) and broader distributed ledger technology (44 percent), according to Grant Thornton’s 2019 CFO Survey, conducted in partnership with CFO Research.

    Further, year-over-year comparisons show that CFOs are seeing dramatic changes in technology adoption at their companies:

    • Forty-two percent reported their finance functions regularly make use of advanced and automation technologies in corporate development and strategic planning, compared to 18 percent in Grant Thornton’s 2018 CFO Survey;
    • Forty percent reported their finance function already implements advanced technologies and automation technologies in risk management, compared to 20 percent in 2018;
    • Thirty percent use machine learning, compared to 8 percent in 2018; and
    • Twenty-five percent use AI, compared to 7 percent in 2018.

    “Financial leaders must embrace and adapt to new technologies to ensure their organizations operate efficiently,” said Srikant Sastry, national managing principal of Advisory Services at Grant Thornton.

    “The speed with which CFOs are investing in IT shows a clear vision of the digital transformation they want to see at their companies. But, advanced technologies like AI, RPA, drones, and robotics require CFOs to focus on specific use cases, workforce preparation, and measurements for these technologies to facilitate and maximize a timely return on investment.”

    CFO role continues to evolve

    CFOs reported that they are well-positioned to collaborate with IT and ensure that digital investments fit into their organization’s innovation strategies: Nearly 91 percent of respondents agree or strongly agree it is the CFO’s job to ensure their companies fully realize the benefits of technology investments.

    That said, almost the exact same amount of respondents (92 percent) believe the finance function of the future must do a better job of leveraging both technology and people.

    According to the “All systems go: CFOs lead the way to a digital world” survey, CFOs see themselves as part of a cross-functional, collaborative team.

    Of the nearly 400 financial leaders surveyed, 95 percent of respondents said their company’s CFO is a key stakeholder of enterprise transformation planning; while 94 percent reported their company’s CFO actively supports an innovation culture; and 90 percent agreed the company’s CFO actively shares insights about how to run a lean, efficient function with their peers in business units.

    Challenges ahead: Skill and collaboration

    As CFOs speed toward transformative technology, 60 percent believed the finance function must provide advanced analytical support. The most important skill sets senior financial executives want to develop in the finance function are:

    • Data analytics (55 percent),
    • Business strategy (40 percent),
    • Operations management (35 percent), and
    • Technology acquisition (33 percent).

    Moreover, the survey showed that financial leaders want to recruit and retain employees who possess traditional financial expertise, while also showing an eagerness to learn new technologies and process design.

    “Over the next two years, talent and skills will be one of the top three challenges the IT function faces as it seeks enterprise growth, along with system complexity and business integration,” says Chris Stephenson, Business Consulting principal at Grant Thornton.

    “As the finance function of the future takes shape, it will demand new skill sets. Leaders will need to move full speed ahead to invest in the right technology and people to transform their businesses and, ultimately, guide strategic decision making across their organizations.”

    Stephenson concludes that this transformation will not end with recruiting and developing employees to have the right set of skills – or merely implementing the latest technologies. “Working more closely with the IT organization can help the CFO rethink end-to-end finance processes. CFOs and CIOs must closely collaborate on digital transformation to remain competitive,” he says.



  • Digital Transformation: How to avoid the five common pitfalls

    Global competition, shifting customer demands and a surge in digitalisation are just some of the trends changing the face of modern manufacturing. To keep up with this change of pace, many manufacturers are now starting out on their own digital transformation journeys. While there is no magic formula, there are some common stumbling blocks, which can be avoided.

    Industry 4.0 is here to stay, and it is vital that manufacturers make the most of the opportunities it offers. However, there are traps for the unwary and unprepared, which often complicate the job of introducing IoT and digital transformation.

    Fortunately, by focusing on just five core principles, manufacturers can take a strategic approach to digital technologies, which perfectly complements their business.

    1. Too much too soon

    For many engineers and factory managers, it can sometimes seem as though Industry 4.0 needs to be applied everywhere immediately, and it’s easy to fall into the trap of believing that digitalisation demands a complete overhaul.

    In practice, however, that approach would be unreasonable for most manufacturers, requiring a considerable period of system shutdown and typically over-investment as existing machinery is replaced and the complexity of technology increases virtually overnight.

    Not only does this make it difficult to manage, but almost impossible to see where upgrades have contributed to ROI. In contrast, taking small and strategic steps to digitalisation can prove more beneficial for most manufacturers. Remember, this is evolution, not revolution.

    Upgrading to Industry 4.0 in manageable steps not only allows businesses enough time to make well-researched and considered decisions, but also gradually introduces employees to the new technology around them.

    This step-by-step approach also enables manufacturers to see precisely how digitalisation is adding value to their processes, and by reducing complexity, makes it possible to easily connect other machinery down the line – saving time and money.

    1. Getting off on the wrong foot

    Industry 4.0 is about flexibility – of manufacturing processes, machinery, facilities, people and outputs. With that in mind, selecting the correct standard at the start of your digital journey is essential, but it’s a step some machine manufacturers and end-users overlook.

    To be truly flexible, any upgrades need to be able to accommodate change. After all, Industry 4.0 is in constant motion, making change inevitable. For machines, that means connections which not only meet the standards of today but will also be easily modified in response to future changes.

    So, when making investment for the future, manufacturers need to be sure their machinery will provide the flexibility needed for change.

    1. A lack of planning

    In the digitalised factory, data sits at the heart to create an environment of connected manufacturing and continuous improvement. In harnessing that data, sensors are key.

    Attached to cells, machines or tooling equipment, these sensors measure variables such as temperature, pressure, vibration and power consumption to provide an inside view of the machinery that powers their facility.

    The problem, however, arises in how that data is evaluated and interpreted. When taking their first steps into the Industry 4.0 arena, manufacturers are often overwhelmed and can fall into the trap of using vast numbers of sensors to collect mass amounts of data.

    To overcome this, people need to be brought into this automated process. By visualising the data that is being collected, employees can share their expert insights and knowledge to help manufacturers understand what is important to measure – from machine performance through to functions such as logistics and purchasing.

    Only then can the true impact of digitalisation be seen.

    1. Overlooking security

    As the world around us becomes more digital, cyber-attacks become increasingly prevalent. So, while Industry 4.0 brings a host of benefits for manufacturers, it can also make them more susceptible to these attacks – if the correct precautions aren’t taken.

    Studies have shown that the vast majority of manufacturers feel underprepared when it comes to digital security, and only expect their vulnerability to grow. The good news is that preventative action can be taken; equipping manufacturers with the tools they need to protect their data from cyber-attacks.

    Proven IT security processes, for instance, can be quickly and seamlessly extended to production, such as network segmentation and firewalls. In addition to this, instruments which enable users to centrally manage all IoT devises and simultaneously install security updates at all locations around the world are also available, ensuring manufacturing operations remain protected.

    1. Re-inventing the wheel

    When setting out on the journey to Industry 4.0, some manufacturers set out to create their own solutions. The thinking is logical – creating a system, which is unique to them, will suit their specific needs. The reality, however, is quite different, requiring huge amounts of time and money.

    Simply writing the documentation for a proprietary solution can take a tremendous amount of time, not to mention the fact that standard solutions are more user friendly and can be moulded to a manufacturer’s precise requirements.

    By using a standard solution, manufacturers can be up and running within a matter of hours, with all IoT-connected machines centrally managed in their network. Using a standard solution also minimises unnecessary complexity, enabling easier connection between machines and control systems.

    This approach further helps manufacturers maximise the value of Industry 4.0 upgrades over the long term, reducing restrictions on upgrade options in the future. For this reason, it’s more beneficial for manufacturers to operate IoT functions on dedicated systems, concentrating on real-time communications between systems.

    Andrew Minturn, Business Development and Strategic Product Manager Bosch Rexroth


  • How Telecommunications Industry Can Use Blockchain For Innovation

    “If 4G and LTE heralded the era of location-based services, 5G is anticipated to propel presence-based services”

    Telecommunications industry (telcos), once considered as the pinnacle of innovation, is under tremendous pressure to innovate. Over-the-top (OTT) players like WhatsApp, Netflix and Facebook delivered a strong round of disruptive surprise and pushed the telcos into a downward spiral. With 5G around the bend and setting the stage for the next round of disruption, can telcos leverage on blockchain to offer innovative and cutting-edge services and products?

    Next-Generation of Telecommunications

    The fifth generation (or 5G) telecommunications network is all about higher data rates, lower latency and a massive mesh of interconnected devices. If 4G and LTE heralded the era of location-based services, 5G is anticipated to propel presence-based services. Imagine walking through an airport without ever having to open your passport or the boarding pass. That day might not be far away with an array of sensors, combined with technologies like facial-recognition, edge-computing, and AR & VR — tracking every individual’s movement within an airport.

    Plenty of use cases, combining broadband speeds on cellular devices and networked devices, will evolve as 5G rollouts pick up steam. Along with the use cases, new business models will emerge — new trust models, ways-of-working, partnerships and the sharing economy.

    As telcos prepare for the next wave, let’s look at the key blockchain use cases on the horizon to enhance their existing services/products and offer new ones.

    Network and Infrastructure

    Telcos inherently are complex and largest infrastructure projects requiring large-scale investments. Billions of dollars have gone into the transformation to current 4G/LTE networks. Many telcos are yet to monetize their investments into existing technologies. Despite no ROI, the pressure to invest heavily for 5G and remain competitive is growing.

    As a viable alternative, telcos are turning to infrastructure sharing with other players in the market, instead of doing it all alone. A sharing economy, among the service providers in a region, will bring its own challenges of transparency, timely coordination and intervention, and adherence to the contractual T&Cs.

    With its core features of decentralization, transparency and immutability, blockchain has the potential to deliver a level playing field for telcos irrespective of their size, eliminate complex middlemen and distribute value proportionately among the participants. In addition, features like smart contracts, will help create new business models like on/off rentals and pay-as-you-go. Clearly, the era of macro-sharing will give way to micro-sharing and a blockchain backbone will help the telcos get there.

    Business/Operations Support Systems (B/OSS)

    B/OSS is the heart keeping the telco network ticking. From delivering services on demand to realizing revenues from the delivered services, B/OSS applications play a vital role. The current technologies in use are heavily siloed, inflexible and firewalled, resulting in poor customer experience, losses due to fraud and leakages and gross inefficiencies in the overall delivery mechanism.

    From quote to cash, the services rendered by telcos can be viewed as a complex supply chain ecosystem, requiring many interdependent teams, both internal and external. Naturally, blockchain enabled use cases relating to eliminating middlemen in the inter-carrier settlement, preventing roaming fraud and efficient mobile number portability are already underway.

    In addition, telcos should start exploring blockchain for efficient supply chain management, building a participatory marketplace involving partners and consumers and data fraud protection.

    Emerging opportunities

    We are moving into an anything-as-a-service economy and telcos will be no stranger to it. There are two waves of opportunities for telcos to consider: repurposing existing services/products; and building new offerings for the market.

    While a lot has improved in the past years, telcos still have much ground to cover to meet the rising expectations from the customers. Inflexible pricing bundles will have to give way to flexible options. If mobile money can be transferred freely across networks and customers, why not other items of value like airtime and access to the network? Fungible services and networks will deliver better bang for the customers’ buck.

    We are at the cusp of a new technological era and new technologies bring new opportunities. Given their market share, deep insights on customer behavior and implicit trust consumers place on the brand, telcos must fully utilize this opportunity. New avenues for growth and revenue — like Identity-as-a-service, data & device security, content ©right management, and even blockchain-as-a-service — are opening for the telcos.

    Whether telcos are relegated as a dumb pipe or regarded as a value stream, the choice is entirely up to them.



  • How digital transformation is driving cyber security evolution

    In a news environment dominated by political and economic shifts, the devastating effects of cyber crime and data breaches go largely unreported. Yet, for small to medium-sized businesses (SMEs) in South Africa, which arguably form the backbone of a teetering economy, cyber crime and data theft are undermining growth and sustainability.

    While reliable statistics are nearly impossible to obtain, it is clear that SMEs are falling victim to hackers on a weekly basis. Why? Business leaders have clearly not stayed abreast of a cyber risk landscape that has changed dramatically over the past decade. Not only have the nature and scope of the risks evolved, but so too have the tools and strategies required to mitigate them.

    For SMEs, it is critical to understand this evolution and to bring the organisation in line with current (and future) trends, says Colin Thornton, MD of Turrito Networks.

    A simple question of software

    When looking back 10 to 15 years ago, cyber security for SMEs generally equated to a decision around which anti-virus software to choose. As long as the anti-virus was reputable, and kept up to date, business leaders could tick the cyber security box. In most cases, this box was probably located towards the very bottom of the business agenda… and budget.

    As businesses began to embrace more seamless and accessible Internet connectivity, the cyber threat level began to rise. Employees gained access to social media platforms, and started to harness these platforms for business as well as personal communications. The use of e-mail within organisations became paramount to productivity, along with other emerging connectivity tools such as Skype.

    New barriers needed

    With employees becoming increasingly ‘plugged in’, hackers and fraudsters soon identified newbie Internet users as soft targets for online scams and phishing. Along with the unwanted tides of advertising and ‘junk’ mail, these scams prompted businesses to install spam filters along with the trusted anti-virus software.

    In addition to targeted attacks, business leaders very soon had to contend with the peril of dodgy Web sites. As employees delighted in newfound connectivity and Web surfing freedom, they blundered their way onto infected sites and unsecured environments. This forced businesses to invest in firewalls as well as more sophisticated anti-virus software.

    Mobility, endpoint security emerges

    Over the past several years, smartphones, laptops and other mobile devices have become integral to modern working environments. Particularly for SMEs and start-ups, being able to work and communicate remotely has proven critical to survival. Yet, with the proliferation of mobile devices that connect into sensitive business platforms and environments, the cyber risk naturally intensifies. Another way of thinking about it is that as ‘entry points’ to business information and systems multiply, so too do the risks.

    To combat this heightened risk environment and the emergence of mobile working solutions, businesses embraced the concept of ‘endpoint security’. In techie terms, endpoint security is simply a security approach that focuses on ‘locking down’ endpoints (think individual computers, phones, tablets and other network-enabled devices) in order to keep networks (businesses) safe.

    Along with the focus on endpoint security, the heightened risk environment also sparked off interest in penetration testing and vulnerability assessments. Penetration tests are designed and intended to exploit weaknesses within IT networks and thus to determine the degree to which hackers can gain unauthorised access to business information and assets. These tests can be manual or automated and are performed by IT security professionals. Even as recently as five years ago, regular tests such as these were considered a nice-to-have but were fairly far down the IT task list. Nowadays, they should be near the top.

    The devil is in the data…

    While the reality of hyper connectivity has deepened the complexity of cyber risks, this connectivity is also fuelling the creation of data. As we have seen in recent years, data has been likened to the new ‘oil’ of the global economy, and as such, it has become an asset that needs vigilant and well-structured protection. Notably, in the World Economic Forum’s Global Risks Report 2019, “massive data fraud” was ranked the number four global risk facing organisations of all kinds.

    For SMEs, which are just as likely to fall victim to data breaches as their larger counterparts, data security now demands a full strategy of its own. To begin with, SMEs have to harness tools such as SharePoint to implement secure document management. Such tools ensure that employees not only store data in a safe and organised way, but that they can also collaborate on files and safely share information with outside parties. Moreover, with legislation such as the Protection of Personal Information Act 4 of 2013 (POPI) and the General Data Protection Regulation (GDPR) coming into effect, businesses of all sizes will have to enforce strict data governance frameworks, or else risk falling afoul of the law.

    Moving beyond silos

    When assessing the current cyber risk environment for SMEs, perhaps the most significant element of the digital evolution is that cyber security has become everyone’s responsibility: it does not simply fall to the business owner, the tech guy, the manager, etc… every employee has become a target, and similarly, everyone has a role to play. This means education and internal training has to be the first and most fundamental part of any cyber security strategy. Today, businesses are still allowing staff to save sensitive data on their own laptops, memory sticks and consumer cloud platforms like Dropbox, for example, which immediately places the business at risk of a data breach.

    As the risks continue to change and evolve, so too do business owners and employees have to elevate their own awareness and online behaviours. Digital transformation continues to propel business and innovation forward, but the dark side of cyber security is casting a formidable shadow.



    About the author

    Colin Thornton founded Dial a Nerd in 1998 as a consumer IT support company, and in 2002, the business-focused division was founded. Supporting SMEs is now its primary focus. In 2015, his company merged with Turrito Networks, which provides niche Internet services outside of the local network. These two companies have created an end-to-end IT and communication solution for SMEs, from supplying a laptop right through to designing and delivering a fibre-connected geo-redundant hybrid-cloud solution. This type of end-to-end service was typically only possible for enterprise customers, but now SMEs, mid-market organisations, homes and schools can benefit too, for a fraction of the cost. Thornton has subsequently become the Managing Director of Turrito.

  • What is AI’s biggest asset in government digital transformation?

    In this article, Sascha Giese examines how Hybrid IT and cloud computing will be AI’s biggest asset as the government embraces digital transformation

    The term artificial intelligence (AI) is familiar to most of us. Looking beyond the realms of science fiction, however, AI has the potential to have a positive impact in a government context, because the take-up of AI will more than likely be the result of the adoption of hybrid and cloud computing.

    AI is highly effective but historically has had a long adoption timeframe, similar to other excellent technologies waiting for the perfect use case within day-to-day IT environments. But many believe that’s about to change. Public sector investment in AI is expected to rise rapidly in the coming years. According to the SolarWinds U.K. Public Sector IT Trends Report 2018, over half of the surveyed public sector IT pros predict that AI will be among the biggest technology priorities in three to five years.

    Here in the U.K.,

    emerging technologies are already being used to improve services. In a recent article, Oliver Dowden, minister for implementation in the Cabinet Office, shared the example of Her Majesty’s Revenue and Customs (HMRC), which has used Robotic Process Automation (RPA) technology.

    According to Dowden, in the example of employer registration end-to-end processing, up to 85% of applications are automatically processed, thanks to the deployment of 12,500 robots and the automation of 56 processes across multiple lines of business. The technology validates data from online applications and provides a unique reference number to new employers to enable them to begin employing staff.

    Signs point to hybrid IT and cloud adoption as primary factors in the rise of AI adoption. In fact, the two can have a synergistic relationship, as AI will enhance the capabilities provided through a hybrid IT or cloud environment.

    One of the great advantages of the cloud is its ability to serve as a platform for public sector IT pros to acquire and use technologies as a service, versus buying them outright. Applications, storage, infrastructure—all of these are now available as a service.

    AI is no different. Each major cloud provider offers its own machine learning services (MLaaS) platform, which allows third-party AI application developers to build their smart applications on each of these cloud platforms. With the availability of AI platforms, comes the opportunity to “let someone else” handle the intricacies of creating AI applications, which may lead to a wide variety of new AI-based applications.

    Two further advantages of cloud that present an environment ripe for AI are worth mentioning:

    1. Abundant computing and storage capacity to access vast amounts of data

    Abundant capacity means applications have the room to use as much computing power as necessary to accomplish highly complex computing algorithms, and storage to access vast amounts of data so applications have the information necessary to use those complex algorithms to deliver far more “intelligent” information.

    The network making its transition to “Software Defined Everything” can allow AI to use additional resources when necessary and return that capacity when it’s finished with complex issues. Templates, policies, and dynamic scaling are designed to make this more than possible. It even becomes simple.

    2. AI’s role in managing this highly intelligent environment

    Take the Internet of Things (IoT), for example.

    AI has the potential to allow for a dramatically enhanced ability to manage elements that, to date, have been difficult to manage or even track. Taking that scenario even further, the intelligence and data analytics behind AI may also provide the ability to implement far more broad-reaching automation.

    With the automation of hybrid IT and cloud, comes greater efficiency and more opportunity for innovation. I’d call that a win-win.



  • How Microsoft plans to connect more farmers to AI

    While some farmers are using IOT to save time and money, it’s not always a straightforward process.

    Lack of data and power connectivity on farms is an obvious challenge. Another hurdle is the need to buy and install multiple IOT solutions for similar tasks, says Srini Chandrasekar, Director, Azure Global Engineering at Microsoft.

    “A specific IOT provider may give you hardware with sensors for measuring soil moisture, a solution in the cloud and a mobile app,” Chandrasekar says.

    “But if you want to measure nitrogen and PH levels, you go to a different provider, they give you their own sensors and application and the data sits on their site.”

    “It’s very hard for farmers, even if they work with a system integrator, to build solutions that are customised for their needs.”

    In Chandrasekar’s view, the problem is the result of hardware and software vendors forming one-on-one partnerships to offer bundled solutions.

    Those bundles solutions may not be interoperable with other solutions, and might not provide access to advanced AI and data analytics services.

    A common platform

    To solve this problem, Microsoft is encouraging hardware and software vendors to enable their products to work with its IOT platform. That platform includes Microsoft Azure and a range of Azure services, including the Project FarmBeats initiative.

    A common platform should improve interoperability, allowing ISVs and system integrators to build IOT solutions faster and more affordably, says Chandrasekar.

    Hardware and software vendors will also benefit by leaving the task of maintaining the cloud stack and AI services to Microsoft.

    “There are a lot of solutions out there that don’t use the Azure IOT Hub functionality for management, so they try and write their own management stack,” says Chandrasekar. “These are complex systems. Maintaining and investing in them gets to be hard for small companies over time.”

    Microsoft is also creating templates, which it calls solution accelerators, to make it easier for end-user organisations to build IOT solutions.

    Plenty of companies have demonstrated the benefits of using Microsoft’s IOT stack. They include Australian agtech provider The Yield, which worked with Microsoft, Intel and Bosch several years ago to build a system the oyster farming industry uses to monitor water quality.

    Building an ecosystem

    Microsoft is also hoping hardware and software vendors see that building on its platform will expose them to a wide array of complimentary products.

    That includes a marketplace of AI models and additional data – for example, Microsoft will encourage providers of weather and geospatial information to offer that data via Azure.

    “Our goal is to make it easy to aggregate all this data from the field, and weather and geospatial data, and use AI models and other technology to analyse it,” Chandrasekar explains.

    Chandrasekar wants to enable an ecosystem of Project FarmBeats-enabled products that farmers can buy off the shelf and connect to solve problems.

    “We are not an agtech solution provider. We are trying to enable agtech solution providers to be successful,” Chandrasekar says.

    “You will see a lot more public information and partnerships with Project FarmBeats towards the later part of this year.”



  • Is Your Business Ready for the Internet of Things?

    Aviva Leebow Wolmer – CEO of Pacesetter

    Ten years ago, it would have been strange to stand alone in a room and tell that someone named “Alexa” to order pizza — but today, most of us take in stride the virtual assistance that AI provides. With the Internet of Things (IOT), consumers can now take on impossible tasks with ease. Answering the front door from a beach hundreds of miles away is easy; feeding the dog during a long night at the office requires only a few quick taps on a smartphone.

    With all of the feats it makes possible, IOT tech has developed a reputation for redefining how ordinary consumers enjoy their at-home experience. However, smart home devices constitute only a small tip of the overall IOT iceberg. Advances in technology stand to revolutionize the business world as much as if not more as they have our personal lives. That said, while the commercial opportunities in IOT are well-hyped in the media, many corporate executives have so far been cautious, remaining on the sidelines of this developing field.

    Today the question remains: Is it finally time for company leaders to take part in the technological revolution and integrate the Internet of Things into business life? Or is the commercial world still too wary of IOT’s strange potential to take advantage of it?

    What is the Internet of Things, exactly?

    Understanding what IOT can do for business starts with understanding IOT itself. Most laypeople know what these devices can do in their daily lives; however, providing a technical definition is often an entirely different challenge.

    Analysts describe the Internet of Things as “the interconnection of machines and devices through the internet, enabling the creation of data that yields analytical insights and supports new operations.” IOT solutions use these connections to cross-utilize wireless communications, networks, the cloud, and data storage. In doing so, they offer considerable opportunities for handling and analyzing massive amounts of data across geographically disparate locations. 

    What can it do for business?

    The primary benefit IOT provides business lies in its capacity for boosting day-to-day efficiency. These solutions use data collected from social networks, traditional media, and internal and external networks to provide actionable intelligence that empowers machines and people to optimize their behaviors. Well-integrated IOT technologies can offer company leadership valuable feedback into how a company might improve their product functionality and better their user experience, as well as streamline production processes and supply chain management.

    Because these solutions can process more real-time data in a set period than a human could ever hope to, they also play a crucial part in developing financial decisions by providing real-time insights into the state of the business as a whole. The actionable intelligence sourced from IOT solutions complements that from a company’s accounting systems and enterprise resource planning (ERP) and, when taken together, can provide executives with a bird’s-eye view of the venture’s state and provide insights into potentially lucrative financial strategies.

    The benefits that IOT solutions provide are invaluable — however, some researchers have managed to put a number on the potential financial gain. According to a 2015 McKinsey study, IOT stands to save global businesses up to $11 trillion annually by 2025. Other experts in the field project that the technology will boost corporate profits by as much as 21 percent by 2022.

    Statistics like these command interest; a survey found that 45 percent of executives said that IOT-enabled manufacturing was a high or very high priority for their ventures. Interestingly, only 21 percent of those involved in the study worked directly in the manufacturing sector — a detail which implies that the interest for IOT goes far beyond its surface capabilities. 

    Why is IOT so underutilized?

    Unfortunately, interest doesn’t always equate to usage. Many executives have opted to observe the IOT field as it develops rather than actively integrate the potentially valuable technology into the day-to-day workings of their business. According to a study conducted by Capgemini, fewer than “four out of 10 organizations are deploying IOT in operations at full scale.” Moreover, those that do implement IOT technology center in a few choice industries; leaders include industrial manufacturing (62 percent), retail (46 percent), and telecommunications (38 percent).

    Their hesitancy is understandable, even if it does hold ventures back from potential gain. According to a study put forth by Hitachi, 32 percent of surveyed companies were unable to present a compelling return on investment for integrating IOT, another 32 percent struggled to keep potential solutions secure, 31 percent saw problems with cross-departmental cooperation, and 30 percent were unable to process the influx of data effectively.

    For all of its promise, the Internet of Things doesn’t readily or immediately lend itself to daily use. Integration demands strategy, troubleshooting, and countless hours of work; executives will undoubtedly face growing pains. The sheer amount of work and consideration that goes into applying IOT solutions stands as a strong deterrent to those who might otherwise leap on the chance to take advantage of the technology’s potential.

    Does this mean businesses shouldn’t use IOT?

    Every step towards progress demands some heavy lifting. Businesses should not steer clear of IOT solutions because they are imperfect or because they require company leaders to overcome logistical hurdles; the potential payoff is far too high. Moreover, IOT solutions will likely become a norm in business, making integration less of a tech-forward decision and more of a necessity for keeping up with the competition. Integrating IOT technology can and should be a priority; however, companies will need to have advanced analytics and development platforms in place to handle the influx of IOT data, as well as cyber security solutions that address any vulnerabilities that IOT technology creates in a company’s day-to-day systems.

    As the CEO of a tech-forward steel manufacturer, I have seen the value that IOT solutions can provide to modern businesses firsthand. At Pacesetter, we’ve already taken basic steps to integrate IOT into our operations. To date, we have integrated sensors in our production lines that connect to our networks and create live dashboards for our operators. This update allowed us to optimize our reaction time and boost our understanding of our day-to-day efficiency. By analyzing data trends, we were able to determine what proactive steps we could take to improve our processes.

    Pacesetter is in the midst of exploring more ways to integrate technology and further optimize our operations — and it certainly isn’t alone in doing so. Staying on the cutting edge of technology has become inarguably vital to remaining competitive in nearly every industry. One point is for certain for all: the advances we see today are only a hint of what could benefit businesses in the future.



  • Will You Be a Digital Winner or a Digital Loser?

    The Internet is a transformative force in business, enabling amazing new business models and dramatically more efficient means to deliver services and manage a business. It also brings about a level of speed and change unlike anything we’ve previously encountered. It creates new winners and losers. Some of those losers are once-proud businesses succumbing to their newer, more nimble competition.

    The next wave of the internet is the Internet of Things (IoT), or the connection of tangible products and assets to the internet. IoT will be no different from other markets disrupted by the internet, except that the change will be across a far broader set of companies. After all, the Internet of Things involves the digitization of physical assets, and that includes pretty much every company. And just like other markets, some of the largest market participants will assume that they have plenty of time to respond, or that they are too big and too entrenched for the change to significantly impact their businesses. But they will be wrong.

    But how can you tell if you are going to be a digital winner? What are some of the signs that you are falling behind and possibly falling into the loser category?

    Characteristics of Digital Winners:

    • Speed, speed, speed: They’re fast to learn, fast to change, fast to implement and able to change the features of their product to meet customer demands in days and weeks. Winners launch new products at an accelerated monthly schedule.
    • Think like data companies: Decisions on product features are based on data, such as customer engagement. Winners can quickly modify products based on knowledge of usage, failure rates.
    • Differentiate via software: Hardware is slow to change; software is rapid when architected correctly. Winning companies leverage “Software-Defined Products” and assets to drive faster change in business.
    • Higher asset-utilization rates: Winners know where assets are, how to service them more efficiently, have much better control of uptime and therefore higher revenue.
    • Manage products and assets remotely: Digital twins mean companies no longer need to send unnecessary truck rolls to monitor and maintain their products and assets, with huge resulting savings to support their products and to run their business.
    • Know where their products are and how they are being used: Winners have an understanding of engagement with products and customers.

    Characteristics of Digital Losers:

    • Slow product introductions: They aren’t able to do firmware updates to fix bugs in the field and enhance capabilities, especially relative to their new, nimble competitors.
    • Slow to respond to market changes: These companies note the changes slower, and respond slower. Every month, they are losing the data battle to understand the market.
    • Features = what’s in the hardware: They don’t take advantage of software as a differentiator, relying on their old hardware advantages.
    • Lots of decisions based on a hunch and conventional wisdom, not data: Product feature decisions are based on older approaches rather than data. They barely leverage data created by their products and assets.  They’re essentially flying blind compared to their newer competition.
    • Lower asset utilization: They don’t know where their assets are and how they’re being used. And they have less ability to know how and when they’re failing. They respond with too many truck rolls or not enough to maintain similar uptime and customer satisfaction.

    Don’t Get Stuck on the Wrong Side of IoT Digital Transformation

    The first step is to figure out how to embrace these changes and how to roll them into your business. It may seem scary from your vantage point, but it doesn’t have to be a massive shift. After all, digital winners understand the concept of agile development and making small, incremental changes.

    You can do the same with the right strategy, the right tools and the right partners to help guide you through the process.


    Written by David Friedman, Executive Chairman and Chief Strategist at Ayla Networks in Santa Clara, Calif.