TEKNOLOGI
Four Cutting-Edge Technologies That Enhance User Experience

The Future of UX Design: Four Cutting-Edge Technologies That Enhance User Experience
At the dawn of the computer age, PCs did not have a graphical user interface.
Only employees of scientific institutions could work with them. With the help of special commands, they accessed an operating system through a console. In the 1970s, Xerox PARC managed to make technology clear for people by developing a GUI. The era of personal computers began. Nowadays, it is hard to amaze users who have already seen iOS, Android, MacBook, and Apple Watch with previous computer achievements. User experience does not stand still, and innovations that challenge UX design constantly appear. Let’s take a look at four promising UX design techniques.
1. Voice User Interface
In his book The Design of Everyday Things (the “bible” of usability), Professor Don Norman states the main goal of UX/UI designers. They need to provide users with pleasant and simple product experience. Designers should always put themselves in the client’s shoes and solve their problems most conveniently.
At present, an average user needs a keyboard, mouse, or touch screen to work with an application interface. However, the future of devices is often seen as interfaceless. Golden Krishna has written a book on this topic called The Best Interface Is No Interface: The Simple Path to Brilliant Technology. But is it possible to work without an interface? Yes, you can easily do it with the help of voice and virtual assistants like Amazon Alexa, Google Home, Siri, and others.
In 2019, there were 2.45 billion voice assistants. By 2023, their number will equal the number of people in the world and will be approximately 8 billion. VUI is a hot trend in design, and IT professionals need to learn how to build efficient voice interfaces.
A voice interface does not have a visual representation. Therefore, the main task of designers implementing a VUI solution is to research the target audience, its goals and pains, develop interaction scenarios with a voice device, and prepare a text message from the user and device responses.
Designers need to analyze how clients will interact with a device and determine what they may need a VUI for. They need to collect terms and phrases that customers use more often. This data will be useful to build conversations between a person and a device.
Then they should consider scenarios for using the VUI and make sure that the voice assistant solves the problem most simply and efficiently. For example, if a person asks an assistant for a route from Chicago to New York, the device must understand the request and provide the necessary information in the correct context. Voice interaction should be constantly improved in each design iteration so that smart assistants recognize speech and its meaning correctly.
After working with dialogs, designers need to develop a voice interface, test it and continue to improve it. If everything is carried out correctly, a business will gain a competitive advantage over companies that have not embedded voice assistants into their applications.
2. Touchless Gesture Control
Previously, people needed styluses and touch screens to work with smartphones. But in the future, users won’t need to touch their phones at all to turn on music, answer a phone call, or increase the volume. In 2015, Google presented its Soli technology by introducing a miniature radar reading every human movement.
Since then, designers have been talking about touchless gesture control, a new way of human interaction with devices and applications. Examples of this are the Google Pixel 4 smartphone and the Airtouch dashboard from BMW. The latter allows drivers to change the volume of music or receive calls without taking their eyes off the road.
What does this innovation mean for designers? UX/UI professionals need to think about navigation, action, and transformation gestures that will allow them to control the content of devices. The movements must correspond to the ergonomics of the human body, be simple and not require great physical effort. The design community hasn’t yet developed common gestures for UX, so you can create your own. You can base it on real-life experience and make it as simple as possible to reproduce.
Users must be provided with textual or visual hints allowing them to learn a sign language. Also, do not forget about people with disabilities who may have problems with fine motor skills. Therefore, designers should also implement an alternative interface, with the possibility to connect joysticks or electronic devices.
Touchless gesture control opens up a new accessible user experience for customers, building unique ways of interacting with an application.
3. Artificial Intelligence
AI is widely used to create voice assistants. A smart algorithm can also optimize the work of UX designers.
Personalization is the queen of UX. McKinsey estimates that 71% of consumers expect firms to have a personalized experience, and companies that succeed in it increase revenue by an average of 40%. To provide a personalized experience, IT professionals need to analyze a huge amount of user data, then segment it and provide customers with relevant content only. AI is extremely helpful in analytics. Using archive data, the algorithm predicts a user action or request and suggests the best UX option to a designer. Thus, AI in UX allows you to optimize interface modules, present an improved experience and increase the value of a product for a wide audience.
AI in UX will automate repetitive simple designer tasks. For example, it can perform color correction and photo resizing, while a UX specialist solves more important tasks. Of course, AI developers have impressive ideas. They want to teach a smart algorithm to understand sketches and turn them into user interfaces. By the way, this feature has already been implemented in a designer assistant, an application based on AI Uizard.
Content generators for design layouts are built on AI. A designer usually needs a lot of time to fill in text and photos to create content that is close to reality. Generative adversarial networks use a smart algorithm to automatically fill layouts with real content. There are similar solutions on the market. Take, for example, the This Person Does Not Exist platform which generates photos of non-existent persons based on images of real people. Such software already frees UX designers from certain tasks and responsibilities, allowing them to devote all their attention to perfecting layouts.
4. Virtual Reality
As science advances, VR/AR/MR in UX are actively penetrating healthcare, education, eCommerce, and other industries. According to researchers, in 2021, these technologies cost $28 billion. By 2028, they are predicted to grow to $250 billion. This is a powerful trend that UX designers cannot disregard.
Designers follow the same pattern when implementing VR solutions. They research the customer and the target audience to create UX. The difference is that in VR applications, the client is not a bystander but an active participant. To plan digital interactions for these applications, specialists should use the storyboard technique and get their ideas down on paper first.
It is also important to consider the duration of a VR session. As a rule, it does not exceed 20-30 minutes because people get tired and lose concentration. If a session in a VR application lasts longer, designers should consider the option of saving the progress and returning to it afterward. A UX designer needs to correctly calculate the scale of the VR space so that users do not get lost in an environment that is too large or does not experience discomfort in a small area.
It is important to consider the VR space issues that prevent the most common problem – motion sickness. To do this, you can create fixed points in space or a static horizon that remain motionless while a user moves. Thus, the person can focus on something so as not to feel dizzy. Designers should also take care that the user keeps the same speed, there are no sharp drops, and there are “staging posts” for rest. Sound accompaniment corresponding to the actions taking place in virtual space will also help a person avoid disorientation and motion sickness.
For a convenient adaptation of users to VR, specialists need to consider a system of hints that guide customers along the way. They should avoid using too much text: in a virtual environment, excessive reading provokes eyestrain. It is better to add audio instructions, visual effects, and simple sentences to convey important information. Users will be grateful for such care.
Slutsats
UX design technologies improve the customer experience by providing users with new opportunities and more convenient interactions with applications. UX designers have to adapt to new trends to offer clients an easier and more inspiring way to solve problems. As you can see from the examples above, VUI, touchless gesture control, AI, and VR do a good job of UX tasks. For a professional designer, knowledge of these technologies is a must. For a business, they mean an opportunity to increase revenue through an improved CX.
TEKNOLOGI
Shopify och Google Cloud AI-integration ökar e-handelsmöjligheterna

Shopify and Google Cloud have unveiled an integration that enables retailers using Commerce Components – Shopify’s enterprise retail solution – to leverage Google-quality search capabilities and AI innovations.
Enterprise brands on Shopify can today access Google Cloud’s Discovery Al solutions directly through Commerce Components, Shopify’s modern, composable stack for enterprise retail. This integration, which can now be used by Shopify merchants globally and is available in most languages, increases access to Google’s advanced search and browsing technologies so that retailers can create more fluid and fruitful shopping experiences for their customers.
Shopify and Google Cloud’s new integration equips enterprise brands with artificial intelligence (AI)-driven product discovery capabilities that address real-world business challenges, including:
- Google Cloud Retail Search, which providesadvanced query understanding that can produce better results from even broad queries, including non-product and semantic searches, to effectively match product attributes with website content for fast, relevant product discovery.
- An AI-powered browse feature that uses machine learning to select the optimal ordering of products on a retailer’s ecommerce site once shoppers choose a category, like “women’s jackets” or “kitchenware.” Over time, the AI learns the preferred product ordering for each page on an ecommerce site using historical data, optimizing how and what products are shown for accuracy, relevance, and likelihood of making a sale.
- An AI-driven personalization capability that customizes the results customers get when they search and browse retailers’ websites. The AI underpinning the personalization capability uses a customer’s behavior on an ecommerce site, such as their clicks, cart, purchases, and other information, to determine shopper taste and preferences.
- A Google Cloud Recommendations AI solution thathelps retailers deliver personalized recommendations at scale. Recent upgrades to Recommendations AI can make a retailer’s ecommerce properties even more personalized, dynamic and helpful for individual customers.
- Advanced security and privacy practices that help ensure retailer data is isolated with strong access controls and is only used to deliver relevant search results on their own properties.
Harley Finkelstein, president of Shopify, said: “We’re thrilled to continue our long-standing partnership with Google Cloud.
“We’re bringing together the best in commerce with the best in search to solve a complex and costly problem for enterprise retailers – world-class search and discovery for the online store.”
Thomas Kurian, CEO of Google Cloud, said: “Shopify integrating Google Cloud’s Discovery AI technology into its enterprise retail solution puts the power of AI directly into the hands of merchants and brands to solve everyday problems.
“Now, retailers will be able to enhance their digital properties with better product discovery experiences, creating more fulfilling shopping experiences for their customers.”
Rainbow Shops builds a better customer experience with Google Cloud search technology
Rainbow Shops, a Shopify merchant and popular retail apparel chain with more than 1,000 stores, recently integrated Google Cloud’s Discovery AI for Retail technology directly into its own digital domains. After experiencing limitations with other search and product discovery solutions, Rainbow Shops approached Shopify about the possibility of using Google Cloud’s search and browse capabilities.
When compared to other specialty search services, Rainbow Shops’ internal testing found that Google Cloud’s solution could deliver helpful results to an assortment of test queries 100% of the time. In addition to accuracy, Rainbow Shops saw an immediate reduction in the amount of time and effort its teams previously spent on manually refining search results, creating redirects, and pulling up to 50 other levers to get useful results.
Rainbow Shops is now using Google Cloud’s Retail Search technology, and importantly, it took less than a week for Google Cloud’s AI tools to be successfully integrated into Rainbow Shops’ online store and mobile app—all right before last year’s peak shopping moment for the retailer, Cyber Week.
David Cost, VP of e-commerce and marketing, Rainbow Shops, said: “Now our search bar can handle almost anything our shoppers throw at it, surfacing helpful product results for nuanced queries like ‘lbd’ (little black dress) and extremely general searches like ‘Mardi Gras.’ We’ve also significantly advanced our ability to produce relevant results when a shopper has a typo in their query, which is commonly seen among our many customers now shopping on mobile devices.
“Rainbow Shops is using Google Cloud’s AI tools to create an undeniably better shopping experience for our customers. In just three months we’ve already seen search volume increase 48% and our bounce rate on visits has decreased three-fold.”
Consistency lacking in retailer search experiences, resulting in search abandonment
Despite the continued rise in online shopping, many shoppers report hurdles in the product discovery experience on retailers’ ecommerce properties. New research from a Google Cloud-commissioned Harris Poll survey found that search abandonment—when a shopper searches for a product on a retailer’s website or mobile app, but doesn’t find what they are looking for—costs retailers more than $2 trillion annually globally, and more than $234 billion in the U.S. alone.
Shoppers themselves say they depend on the search function or search box when shopping; it’s the most common way U.S. consumers search for products on retail websites (69%), followed closely by general website browsing (63%). The problem is that retailers’ search experiences lack consistency, as only one in 10 U.S. shoppers say they get exact results for their queries (12%) or good alternatives (11%) every time they use the search function on a retailer’s site. In fact, more than three in four U.S. consumers (76%) say that in the past month they have used the search function or search box on a retail website and it did not provide the item they were looking for.
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TEKNOLOGI
Hur data och människor driver innovation

The role of CIO is fast becoming the ‘chameleon’ of the C-Suite, necessitating the capacity to constantly evolve and take on additional responsibilities – moving beyond driving efficiency, to driving innovation and growth – shaping and creating digital transformation.
This includes leading modernization strategy, moving legacy technology and frameworks to the cloud, and spearheading data migrations. And it extends to onboarding, managing and retaining talent that may not be physically proximate with the rise of hybrid working, alongside responding to changing employee, consumer and ecosystem partner behaviours and expectations. In part one of this two-part special, we explore the vectors of change, and key issues and opportunities such as addressing the data paradox, moving from data management to data centricity and value, and democratizing the capacity to create and build. In part two, we move on to unpack human centred leadership, the power of the ecosystem, and skills-based organisation with final thoughts to reflect and integrate key themes and insights together.
The world is rapidly changing with key trends impacting the path, progress and potential of digital transformation. These include a major shift to digital first and both customer and employee engagement personalisation. For consumers, this means heightened expectations around the level of differentiated, relevant and tailored experiences they will receive and across all touch points within that journey, whether onboarded within-stream on social media, or via a web form referral, or via a call-centre and beyond – all touchpoints must not only connect to your customer but equally connect to one another too. This is the essential foundation of an opti-channel approach which seeks to be friction-free and continually learning from previous interactions. Perhaps then, it is no wonder that 81% of organizations in a recent study cite CX as a leading competitive differentiator. And for employees this also matters greatly too, with focus areas notably growing in relation to skills development, for example the personalisation of learning journeys.
Additional trends include the centricity of gaining and retaining digital trust, the demands of hyper-competition, the rise in consciousness around ESG and accelerating talent gaps coupled with high employee agency. This is also reflected in work trends around burnout, middle management squeeze, ‘quiet quitting’, the ‘great resignation’ and proximity to churn. And it extends to the transition to ‘As A Service’, the application of digital platforms for agile business, a shift in platform users, notably citizen developers and scientists and the advance of ‘composable thinking, composable business architecture and composable technology’ as the ‘three pillars of composable digital business’ (Gartner®) which is unpacked further in the definition below:
‘A composable digital business applies the core principles of composability (modularity, autonomy, orchestration and discovery) to the foundations of its business architecture (the business model, enterprise operations and strategy) in order to master the risk of change and reach untapped business value’ Gartner®*
Beyond this, ecosystem partnerships are also a key innovation strategy. This is discussed in the excellent blog by Greg Sarafin, EY Global Alliance and Ecosystem Leader and includes a 5-part suggested strategy to support CIO’s in addressing key challenges in order to build the ‘digital foundation’ that underpins ecosystem success. And of course, there are other vectors of change and uncertainty, especially geopolitical (WEF 2023), which have impacted upon already accelerating challenges such as cybersecurity with threats escalating in scope, sophistication and scale. The list of influences just goes on!
So how does today’s CIO meet these growing, interrelated and complex needs? This piece explores data centricity, human-centred leadership and skills-based organization as the key catalysts to bring to every decision, innovation and experience for shared value impact. It is supported by insights from EY’s bi-annual Tech Horizon research, part of the CIO Imperativethought leadership series, alongside other salient studies, including my own original research.
Addressing the Data Paradox
Data that is secure, trusted and available – to the right role or system, and at the right time – has rapidly emerged to be the strategic currency of the digital age, alongside trust. But today’s data landscape reveals a paradox when it comes to achieving that value. Considering the 4’s V’s of Data: Volume, Velocity, Variability and Volatility, these have all clearly accelerated, most notably volatility and volume with the scale of cross sector disruption and evolved behaviours in the last two years. This has exacerbated a ‘DataParadox’ intention/action gap in three core areas, as revealed by the Dell research which I was directly involved in:
1 – Businesses believe they are data-driven but they don’t prioritize the use of data across the organization.
2 – Businesses need more data, but they have more data than they can handle right now.
3 – Many businesses believe in ‘As A Service’ benefits, but only a few have made the transition to such a model.
Overall, data overload and the inability to extract meaningful insights from data emerges as the third highest barrier to digital transformation in the Dell study. This also aligns with findings from EY’s bi-annual Tech Horizon research, which reveals that 53% of senior executives identify data and analytics to be their leading investment priority for the next 2 years – reflecting the heightened significance, this represents a 50% increase since 2020.
So it becomes clear that whilst timely data-driven decisions are at a premium there are still barriers to address, including data being too distributed or siloed or wrangling disparate sources via a central ETL pipeline, right through to tool, cloud and vendor sprawl, disruption in migrations, and taking too long to either move data or analyse it (WANdisco 2022). Additional examples include broken data pipelines after operational database changes, lack of integration and holistic visibility, growing talent gaps challenges (IDC Research*) which describes ‘a worrying shortage of talent that could throttle innovation and even lead to some businesses failing altogether…’. Additionally, as discussed during a recent keynote session Q&A, the team demands of building and maintaining a cloud data warehouse or equivalent, alongside concerns around security, measurement and levels of cloud waste (Flexera 2022, Eaves 2022).
This is reflected in EY’s study findings, where the second greatest challenge reported was that of building complex security and privacy requirements, cited by some 27% of respondents -an area that is only likely to grow given geographical differences across governance and compliance which can add to the complexity of management. And given the rising prominence of ESG and increasing demand for better cohesion across measurement, reporting, transparency and accountability of disclosures, needs in this specific area are poised to rise further still. I believe that ESG is the now the next frontier in privacy and data governance which will necessitate moving beyond pure regulatory compliance to holistically identifying areas throughout the data cycle that create risks.
Putting this all together, there is a fundamental need for interoperable, robust data capabilities across all areas of organisations from SME to Enterprise alike, across all verticals.
From Data Management to Data Centricity – And Value!
The time is now to move beyond disparate technology stacks, restricted facts and siloed decision-making capabilities, necessitating a migration in approach from data management to data centricity – this evolution describes the application of data as a shared asset to enable active intelligence and insights for customers, stakeholders and ecosystem partners, and to help continuously improve decisions, processes, products, and services. But with EY’s Tech Horizon research finding only 16% of organizations reporting that they are data-centric today, (although increasing), there is clearly still work to be done.
Underpinned by the vision, clarity and communication of a data centricity framework, this should include areas such as business goals and data strategy, data-science and architecture, data governance, reporting and visualisation. And this can be greatly supported by the use of a data fabric and data mesh architecture integrated across the enterprise. Indeed, data fabric plays a pivotal role in helping organizations achieve resiliency and sustainable growth, underpinned by right-size governance and data consistency, accuracy and accessibility via a single common platform. And the advances extend to self-service analytics too!
This approach affords a single data view, moving beyond the fragmented perspective that can result from data previously housed in disparate data lakes and warehouses. Or in other words, a fabric approach decouples consumption from diverse data repositories and works across siloes to pull in data that can be scaled and analysed. It is particularly relevant for more traditional (non digital-native) IT companies, looking to leapfrog the limitations of legacy IT.
Putting this into context and reflecting the range of application, this is something institutions like the military are already actively committing to. A recent announcement by the UK Army on ‘Demystifying data’ highlighted just how the UK is pushing ahead with data mesh solutions that add a layer to a data fabric to provide mission-critical products for commanders. Secure access to timely, relevant, high quality data always has been, and always will be the differentiator for success, whether for business decision making, or battle readiness!
And going further still, with the creation of a semantic layer to the data fabric, organisations can apply AI at scale alongside analysis tools to gain active intelligence around rapidly evolving trends and providing the agility to transform go-to-market strategies in days, not weeks – driving efficiency and innovation at the same time. By enabling organisations to run AI on the enterprise edge, this negates the need to build multiple algorithms to link AI into core processes. Further, AI systems, combined with ML, are able to transform data so that it will learn, cleanse itself, and pull in additional data as customers and market conditions change.
Embodying the ethos of ‘build for agility’ and ‘data as a product’, employing a data mesh as a flexible and scalable data platform version of microservices, enables leveraging of a self-serve and domain-oriented design which matches the language and structure of your code to its aligned business domain, with each handling its own data pipelines. This is an example of a data architecture to support an overall implementation of a data fabric, which puts ownership back to the domains, whilst retaining centralised governance. In this way, data expertise will expand from the IT department into business groups, internal operations, and customer relationships too, with security and control embedded by design, and whilst also helping to establish a shared vision around high quality, integrated data for all, no matter where that data resides – elements that all support the evolving role requirements of the CIO.
Democratizing the Capacity to Create and Build
Given the expanded user base of data, its democratization becomes an imperative for data strategists – making it more user-friendly, intuitive and accessible through an array of devices and/or through citizen developers. An excellent example of this in practice is the launch of SAP Build, a new unified low-code solution built on the SAP Business Technology Platform (SAP BTP) and which democratises the capacity to create and co-create, allowing everyone to build and augment enterprise applications, automate processes, and design business sites with intuitive visual drag-and-drop simplicity.
And you can learn more about the benefits across empowering citizen developers, community and education, addressing developer bottleneck constraints and accelerating that all important time to value in this new 4 part video series här – I loved putting this together! And most recently still, you can explore the launch of SAP DataSphere which represents the next generation of its cloud data warehouse service with new data cataloguing, simplified data replication and enhanced data modelling capabilities to enable easy access to business-ready data across the entire data landscape. Accompanying this launch, a new data education series can be freely accessed här.
Supporting all of this, agility and adaptiveness are key, making technology elasticity an important consideration, and necessitating configuration that utilises a tailored combination of core and custom features and modules, with ‘just enough’ customization to meet needs. This is especially important in applications such as Supply Chain, as explored by EY här. The right change management method is critical too, with approaches like Continuous Improvement, Continuous Deployment (CI/CD) enabling introduction of smaller, more regular changes that afford agility and make fault isolations easier to detect – so reducing risk too.
All feedback and follow-on questions most welcome.
Research Notes and Additional Info
Gartner, Becoming Composable: A Gartner Trend Insight Report, Yefim Natis, Janelle Hill, Partha Iyengar, Gene Alvarez, Jennifer Loveland and Chris Howard, 12 January 2023
GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved
IDC Research, How to be a Digital Leader in 2022, Develop Your Digital Quotient To Be Successful on Your Cloud Journey. Europe and North America Info-Briefs, Francesca Ciarletta, Carla Arend, Archana Venkatraman and Frank Della Rossa.
IDC RESEARCH is a registered trademark and service mark of International Data Group Inc and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved
About the Author
Prof. Sally Eaves is a highly experienced chief technology officer, professor in advanced technologies, and a Global Strategic Advisor on digital transformation specializing in the application of emergent technologies, notably AI, 5G, cloud, security, and IoT disciplines, for business and IT transformation, alongside social impact at scale, especially from sustainability and DEI perspectives. An international keynote speaker and author, Sally was an inaugural recipient of the Frontier Technology and Social Impact award, presented at the United Nations, and has been described as the “torchbearer for ethical tech”, founding Aspirational Futures to enhance inclusion, diversity, and belonging in the technology space and beyond. Sally is also the chair for the Global Cyber Trust at GFCYBER.
TEKNOLOGI
Encryption demand soars as 60% of business data kept on the cloud

Duncan is an award-winning editor with more than 20 years experience in journalism. Having launched his tech journalism career as editor of Arabian Computer News in Dubai, he has since edited an array of tech and digital marketing publications, including Computer Business Review, TechWeekEurope, Figaro Digital, Digit and Marketing Gazette.
The demand for cloud encryption is estimated to increase at a CAGR of 30.9% from 2022-2032. The market valuation is projected to increase by US$ 2.4 Bn by 2022 & US$ 34.8 Bn by 2032.
This is according to Future Markets Insight (FMI), which says organisations are investing in the modernisation of data storage strategy with the adoption of cloud technologies for digital transformation. This is expected to drive growth in the cloud encryption market.
The growing need to store data in public and private cloud-based storage is spurring demand in the market. Also, the pandemic forced organisations to adopt remote work, which increased the use of digital technologies and online data sharing. This has resulted in an exponential rise in cyber breaches like ransomware, malware attacks, and phishing.
As a result, enterprises are adopting cloud encryption to safeguard their sensitive data from data breaches and cyberattacks. Cloud encryption encodes the data by converting the plain text data into cipher text, which is unreadable by malicious users, thereby preventing data breaches. It provides enterprises with automated security, reduced complexity, and risk reduction by offering built-in security controls and continuous protection.
Increasing data volumes have driven the adoption of big data analytics across companies, which is capable of processing and analyzing results of big data and providing descriptive, predictive, and prescriptive results. However, one of the biggest issues is how to gain perfect security for big data.
Cloud computing and cloud data stores have aided the growth of big data. Businesses can obtain superior insights from their enormous amount of structured and unstructured data by adopting Big Data analytics in the cloud. Companies handle large amounts of data and leverage the cloud to perform analytics and keep it confidential.
With an increase in data saved in the cloud storage server, hackers try to access confidential data using organisational cloud servers with the help of different decoding techniques. Hence, the use of advanced cloud encryption software by organisations has increased for achieving semantic security.
“As cybersecurity and data security are equally important, enterprises should focus on high capital investment in cloud security by adopting cloud encryption. Encryption is recognised as a top tool required to meet new privacy requirements and should be widely adopted”, said an FMI analyst.
Key Takeaways:
- By component, the solution segment is anticipated to expand at a 32% CAGR through 2032.
- By service model, the infrastructure as a service (IaaS) segment is estimated to grow by 17.8X during the forecast period.
- Based on enterprise size, the SME segment is estimated to grow by 16.8X during the assessment period.
- In terms of industry, sales in the IT & telecom segment are anticipated to increase at a CAGR of 36.5% between 2022 & 2032.
- The U.S. is projected to hold 71.5% of the North American cloud encryption market share by 2032.
- Indonesia will emerge as a lucrative pocket, with sales growing at a 43.2% CAGR through 2032.
Vill du lära dig mer om cybersäkerhet och molnet från branschledare? Kolla upp Cybersäkerhet & Cloud Expo äger rum i Amsterdam, Kalifornien och London. Utforska andra kommande teknologievenemang och webbseminarier för företag som drivs av TechForge här.
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