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	<title>digital twins Archives - CDInsights</title>
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		<title>Cognitive Digital Twins are a Leap Forward</title>
		<link>https://www.clouddatainsights.com/cognitive-digital-twins-are-a-leap-forward/</link>
					<comments>https://www.clouddatainsights.com/cognitive-digital-twins-are-a-leap-forward/#respond</comments>
		
		<dc:creator><![CDATA[Elizabeth Wallace]]></dc:creator>
		<pubDate>Sat, 30 Mar 2024 16:04:30 +0000</pubDate>
				<category><![CDATA[AI/ML]]></category>
		<category><![CDATA[cognitive digital twins]]></category>
		<category><![CDATA[digital twins]]></category>
		<guid isPermaLink="false">https://www.clouddatainsights.com/?p=5078</guid>

					<description><![CDATA[Find out why cognitive digital twins represent a logical next step for many companies in pursuit of digital transformation.]]></description>
										<content:encoded><![CDATA[<div class="wp-block-image">
<figure class="aligncenter size-full"><img fetchpriority="high" decoding="async" width="1000" height="500" src="https://www.clouddatainsights.com/wp-content/uploads/2024/03/Depositphotos_510402080_S.jpg" alt="" class="wp-image-5079" srcset="https://www.clouddatainsights.com/wp-content/uploads/2024/03/Depositphotos_510402080_S.jpg 1000w, https://www.clouddatainsights.com/wp-content/uploads/2024/03/Depositphotos_510402080_S-300x150.jpg 300w, https://www.clouddatainsights.com/wp-content/uploads/2024/03/Depositphotos_510402080_S-768x384.jpg 768w" sizes="(max-width: 1000px) 100vw, 1000px" /><figcaption class="wp-element-caption"><em>Find out why cognitive digital twins represent a logical next step for many companies in pursuit of digital transformation.</em></figcaption></figure></div>


<p>The concept of digital twins has been a game-changer in digital transformation. They&#8217;ve provided a virtual mirror to physical assets, processes, or systems and enabling unprecedented levels of analysis, monitoring, and prediction. But as technology evolves, so does our capacity to imbue these digital replicas with a previously unimaginable layer of intelligence. Enter the era of cognitive digital twins—where the line between the digital and physical world blurs even further. These advanced models do not just simulate reality. They learn from it, adapt to it, and potentially even anticipate future changes. If you thought digital twins were a leap forward, cognitive digital twins are set to redefine what&#8217;s possible. They&#8217;re offering insights and efficiencies that could transform industries.</p>



<p>But first, some background.</p>



<h3 class="wp-block-heading">What are cognitive digital twins?</h3>



<p>Cognitive digital twins are advanced digital models replicating physical objects, systems, or processes in a digital environment while incorporating cognitive computing capabilities. These capabilities enable the digital twins to learn, adapt, and optimize themselves based on data and interactions. In fact, it&#8217;s a lot like human mental processes. Here&#8217;s a breakdown of their key features and applications:</p>



<h4 class="wp-block-heading">Key Features</h4>



<ul class="wp-block-list">
<li><strong>Data Integration</strong>: They integrate data from various sources, including real-time data from IoT (Internet of Things) devices, historical data, environmental data, and more. This combination create a comprehensive digital representation.</li>



<li><strong>Cognitive Computing</strong>: Incorporating AI (Artificial Intelligence), machine learning, and sometimes natural language processing, cognitive digital twins can analyze data, learn from it, and make predictions or decisions.</li>



<li><strong>Adaptive Learning</strong>: They continuously learn and adapt based on new data and outcomes, improving accuracy and effectiveness.</li>



<li><strong>Interactivity</strong>: These models can interact with users, providing insights, answering queries, and even receiving feedback to refine their operations.</li>
</ul>



<h4 class="wp-block-heading">Applications</h4>



<ul class="wp-block-list">
<li><strong>Manufacturing</strong>: In manufacturing, cognitive digital twins optimize production processes, predict maintenance needs, and improve product design through simulations.</li>



<li><strong>Healthcare</strong>: They can model human organs or systems to simulate medical treatments and predict outcomes, helping in personalized medicine and surgical planning.</li>



<li><strong>Smart Cities</strong>: For smart cities, they help optimize traffic flow, energy consumption, and infrastructure management by analyzing vast amounts of urban data.</li>



<li><strong>Energy</strong>: In the energy sector, they optimize the operation of renewable energy sources, predict demand, and improve grid management.</li>
</ul>



<h4 class="wp-block-heading">Advantages</h4>



<ul class="nv-cv-m wp-block-list">
<li><strong>Efficiency Improvements</strong>: Predicting maintenance and optimizing operations reduces downtime and saves costs.</li>



<li><strong>Enhanced Decision Making</strong>: The ability to simulate scenarios and predict outcomes aids in making more informed decisions.</li>



<li><strong>Personalization</strong>: Especially in healthcare and consumer products, they enable highly personalized solutions based on <a href="https://www.rtinsights.com/another-avenue-for-digital-twins-behavioral-modeling-for-banks/">individual data</a>.</li>
</ul>



<h4 class="wp-block-heading">Challenges</h4>



<ul class="nv-cv-m wp-block-list">
<li><strong>Data Privacy and Security</strong>: Handling sensitive data securely is a significant concern, especially with regulations like GDPR.</li>



<li><strong>Integration Complexity</strong>: Integrating with existing systems and managing vast data streams can be complex.</li>



<li><strong>Computational Demands</strong>: The advanced AI and simulations require significant computational resources.</li>
</ul>



<p>Cognitive digital twins represent a significant leap in digital modeling, offering dynamic, intelligent representations that can drive innovation and efficiency across various sectors.</p>



<h3 class="wp-block-heading">Expanding the reach of digital twins</h3>



<p>Cognitive digital twins could profoundly impact strategic decision-making and innovation cycles. While many businesses adopt cognitive digital twins for operational efficiency and predictive maintenance, their potential extends beyond these applications. Here are some possibilities:</p>



<h4 class="wp-block-heading">Accelerated Innovation</h4>



<p>Cognitive digital twins can significantly shorten product and service design and development cycles. By simulating real-world conditions and user interactions in a virtual environment, businesses can rapidly prototype, test, and iterate on new ideas without the time and cost associated with physical prototypes. This can lead to faster innovation cycles, allowing companies to stay ahead in competitive markets.</p>



<h4 class="wp-block-heading">Strategic Decision-Making</h4>



<p>The predictive analytics and scenario simulation capabilities of cognitive digital twins provide businesses with a powerful tool for strategic planning. Companies can use these models to forecast future trends, evaluate the potential impact of different strategies, and make informed decisions that align with long-term objectives. This strategic foresight is often underappreciated but can significantly affect a company&#8217;s ability to navigate complex market dynamics and emerging challenges.</p>



<h4 class="wp-block-heading">Cross-functional Collaboration</h4>



<p>Cognitive digital twins can foster enhanced collaboration across different departments within a company, breaking down silos that traditionally hinder information flow and decision-making. By providing a unified, interactive model of products, processes, or services, design, engineering, operations, and marketing teams can collaborate more effectively, ensuring a cohesive approach to problem-solving and innovation.</p>



<h4 class="wp-block-heading">Ethical and Privacy Considerations</h4>



<p>As businesses leverage more data and advanced AI within cognitive digital twins, they must navigate the complex landscape of data privacy, security, and ethical use of AI. Companies might not fully appreciate the need for robust governance frameworks to meet ethical considerations, which could lead to reputational damage and legal issues.</p>



<p>See also: <a href="https://www.clouddatainsights.com/digital-twins-the-iot-powered-sandboxes-behind-smart-manufacturing/">Digital Twins: IoT-Powered Sandboxes Behind Smart Manufacturing</a></p>



<h3 class="wp-block-heading">Real-time Customer Insights</h3>



<p>Cognitive digital twins can offer real-time insights into customer behavior and preferences by integrating data from various touchpoints. This aspect is particularly valuable for businesses looking to enhance customer experience and develop more personalized offerings. However, the potential of these insights for driving business strategy and customer engagement may not be immediately evident to all businesses.</p>



<p>However, some of the real surprises could lie in customization and personalization. Unlike traditional digital twins, which primarily focus on optimizing manufacturing processes, predictive maintenance, and operational efficiency, cognitive digital twins can dive much deeper. They leverage AI and machine learning to not only understand and simulate complex systems but also predict the behaviors, preferences, and needs of individual users in real time.</p>



<p>Here&#8217;s why this is significant:&nbsp;</p>



<ul class="nv-cv-d nv-cv-m wp-block-list">
<li><strong>Personalized Customer Experiences</strong>: Cognitive digital twins enable businesses to offer highly customized experiences by dynamically modeling individual customer interactions and preferences.</li>



<li><strong>Real-time Adaptation</strong>: They adapt in real time. They enable continuous updating based on new data to improve their understanding of customer needs and system performance. Even further, they can predict changes before they happen.</li>



<li><strong>Innovation in Product Design</strong>: By simulating real-world product use and incorporating behavioral insights, cognitive digital twins can lead to innovative designs more aligned with user needs.</li>



<li><strong>Transformative Business Models</strong>: They enable new, as-a-service business models that continuously optimize products through software, enhancing customer satisfaction and loyalty.</li>



<li><strong>Surprising Insights from Data</strong>: The analysis and learning from a vast array of data can reveal unexpected opportunities for optimization, innovation, and customer engagement.</li>
</ul>



<h3 class="wp-block-heading">Why companies should care about the next stage of digital twins</h3>



<p>The transition from traditional digital twins to cognitive digital twins marks a significant evolution in how businesses utilize technology for data analysis, artificial intelligence, and machine learning. Cognitive digital twins stand out for their dynamic nature. They learn from data and adapting in real time, representing a major leap from the static simulations of their predecessors. This adaptability is key to their predictive capabilities. It also allows them to forecast future scenarios with impressive accuracy, anticipate risks, and optimize operations to meet future demands.</p>



<p>The strategic decision-making enabled by cognitive digital twins offers companies a significant competitive advantage, providing deep, actionable insights that support informed and strategic decisions across all organizational levels. This capability for differentiation in crowded markets underscores the transformative potential of cognitive digital twins. They&#8217;re not just mirroring physical and digital realities. They&#8217;re using anticipation and learning to shape the future of industries. For many organizations, this path is unveiling a new dimension of digital interaction and operational intelligence.</p>
<div class="saboxplugin-wrap" itemtype="http://schema.org/Person" itemscope itemprop="author"><div class="saboxplugin-tab"><div class="saboxplugin-gravatar"><img decoding="async" src="https://www.clouddatainsights.com/wp-content/uploads/2022/05/Elizabeth-Wallace-RTInsights-141x150-1.jpg" width="100"  height="100" alt="" itemprop="image"></div><div class="saboxplugin-authorname"><a href="https://www.clouddatainsights.com/author/elizabeth-wallace/" class="vcard author" rel="author"><span class="fn">Elizabeth Wallace</span></a></div><div class="saboxplugin-desc"><div itemprop="description"><p>Elizabeth Wallace is a Nashville-based freelance writer with a soft spot for data science and AI and a background in linguistics. She spent 13 years teaching language in higher ed and now helps startups and other organizations explain &#8211; clearly &#8211; what it is they do.</p>
</div></div><div class="clearfix"></div></div></div>]]></content:encoded>
					
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		<post-id xmlns="com-wordpress:feed-additions:1">5078</post-id>	</item>
		<item>
		<title>Digital Twins: The IoT-Powered Sandboxes Behind Smart Manufacturing</title>
		<link>https://www.clouddatainsights.com/digital-twins-the-iot-powered-sandboxes-behind-smart-manufacturing/</link>
					<comments>https://www.clouddatainsights.com/digital-twins-the-iot-powered-sandboxes-behind-smart-manufacturing/#respond</comments>
		
		<dc:creator><![CDATA[Jason Hehman]]></dc:creator>
		<pubDate>Thu, 14 Dec 2023 20:50:07 +0000</pubDate>
				<category><![CDATA[AI/ML]]></category>
		<category><![CDATA[digital twins]]></category>
		<category><![CDATA[IoT]]></category>
		<category><![CDATA[smart manufacturing]]></category>
		<guid isPermaLink="false">https://www.clouddatainsights.com/?p=4726</guid>

					<description><![CDATA[Digital twins technology is a core enabler for better development and cost optimization in smart manufacturing and industry 4.0.]]></description>
										<content:encoded><![CDATA[<div class="wp-block-image">
<figure class="aligncenter size-full"><img decoding="async" width="1000" height="667" src="https://www.clouddatainsights.com/wp-content/uploads/2023/11/Depositphotos_664846762_S.jpg" alt="" class="wp-image-4737" srcset="https://www.clouddatainsights.com/wp-content/uploads/2023/11/Depositphotos_664846762_S.jpg 1000w, https://www.clouddatainsights.com/wp-content/uploads/2023/11/Depositphotos_664846762_S-300x200.jpg 300w, https://www.clouddatainsights.com/wp-content/uploads/2023/11/Depositphotos_664846762_S-768x512.jpg 768w, https://www.clouddatainsights.com/wp-content/uploads/2023/11/Depositphotos_664846762_S-930x620.jpg 930w" sizes="(max-width: 1000px) 100vw, 1000px" /><figcaption class="wp-element-caption"><em>Digital twins technology is a core enabler for better development and cost optimization in smart manufacturing and industry 4.0.</em></figcaption></figure></div>


<p>Industry 4.0 – the emerging future of manufacturing – combines software and IoT devices to support faster, smoother, and more cost-effective operations. Getting there, though, depends on tools that provide accurate, real-time insights about floor-level machinery. Also critical: a low-risk way to continually optimize performance and equipment health.</p>



<p>Enter digital twins. They use IoT data to replicate physical machinery (like a robot or conveyor belt) in a virtual environment. And they’re the key to <a href="https://www.rtinsights.com/2024-automotive-smart-manufacturing-trends/">smart manufacturing</a>.</p>



<p>Here, I’ll explain how digital twins work and how manufacturers can use them to improve efficiency and protect the bottom line.</p>



<h3 class="wp-block-heading">How Real-Time IoT Data Powers Digital Twins</h3>



<p>True <a href="https://www.rtinsights.com/manufacturers-embrace-digital-twins-for-enhanced-production/">digital twins</a> are more than static 3D simulations. They rely on real-time data that continuously flows between IoT-monitored equipment and engineers. Here’s what the process looks like:</p>



<ul class="nv-cv-d nv-cv-m wp-block-list">
<li><strong>IoT sensors collect real-time data about equipment</strong>. This could include data about a machine’s position, electrical currents, rotational speed, noise emission, temperature, etc.</li>



<li><strong>The data feeds into the manufacturer’s cloud storage system</strong>. Depending on the sensor hardware, data transmission can occur via WiFi, Bluetooth, cellular, or wide access network (WAN).</li>



<li><strong>Engineers use cloud data to virtually replicate the monitored equipment</strong>. From here, engineers can manipulate this digital twin without actually being on the facility floor. If any changes need to occur to the physical equipment, they can remotely communicate that to nearby workers.&nbsp;</li>
</ul>



<p>As IoT sensors continue to improve their connectivity with cutting-edge technology (like 5G), they’ll be able to relay larger volumes of data at higher speeds than ever. That means manufacturers can maximize the accuracy and relevancy of every digital twin.</p>



<p>It’s worth noting that although digital twins are often used to simulate equipment or machinery, they can also replicate whole manufacturing environments. For example, if a manufacturer is using connected data loggers to monitor a climate-controlled warehouse, workers can create a digital twin to simulate how sensitive products react to sudden fluctuations in temperature, pressure, or humidity.</p>



<p>In the following sections, we’ll take a look at a few specific ways manufacturers can use digital twins to transform their facility operations.</p>



<p><strong>See also:</strong> <a href="https://www.clouddatainsights.com/surging-growth-in-the-global-cloud-database-and-dbaas-market/">Surging Growth in the Global Cloud Database and DBaaS Market</a></p>



<h3 class="wp-block-heading">Digital Twins Enable Smarter Decision Making</h3>



<p>One of the biggest advantages to a digital twin is the ability to remotely track a machine’s operation in real time. And with the right software, AI can recommend adjustments that could extend a machine’s lifetime or improve its performance.&nbsp;</p>



<p>Those two use cases –&nbsp;predictive maintenance and performance optimization – can pave the way for smart manufacturing that protects the bottom line. To illustrate, I’ll walk you through a scenario for each.</p>



<h4 class="wp-block-heading">Use Case #1: Predictive Maintenance</h4>



<p>Imagine an auto manufacturer that’s struggling to keep its automated conveyor belts from breaking down without warning. Engineers can use a series of digital twins to monitor the full conveyor belt system. Thanks to real-time data, they can pinpoint the moment a foreign object gets caught in a machine or a motor starts slowing down –&nbsp;and alert a worker on the floor before the system comes to a halt.</p>



<p>What’s more, AI can use equipment data to, say, notify engineers when a motor has worn down past a certain threshold. It can even suggest an optimal maintenance schedule by comparing real-time and historical data.</p>



<p>The bottom line: with the help of digital twins, manufacturers can slash equipment downtime and keep revenue flowing.</p>



<h4 class="wp-block-heading">Use Case #2: Performance Optimization</h4>



<p>Picture a food and beverage manufacturer that wants to improve the efficiency of its packaging robots. With digital twins, engineers can track each robot’s performance and identify specific components that could be slowing them down.&nbsp;</p>



<p>Then, they can virtually test individual tweaks (like a motor upgrade) and simulate their effectiveness in custom production scenarios. They can even adjust environmental factors, like heat or humidity, to gauge the upgraded robot’s structural resilience. Once the engineers have identified the right changes, they can relay next steps to the right team.</p>



<p>The benefit: digital twins let manufacturers explore ways to create new efficiencies without disrupting equipment on the floor.</p>



<h3 class="wp-block-heading">Digital Twins Can Be a Product Development Sandbox</h3>



<p>So far, we’ve looked at ways digital twins can help manufacturers optimize equipment within their facilities. But they’re also powerful tools for intelligently improving devices in production.&nbsp;</p>



<p>Think of digital twins here as a product development sandbox: engineers can model a near-infinite number of product changes and operational scenarios in a matter of seconds. Most importantly, these changes happen without the need for costly physical rework.</p>



<p>The simulation and testing process is similar to the ones we’ve already explored. The main difference: each model relies on a recent snapshot of IoT data about prototypes versus a true real-time stream. Even so, engineers get a highly accurate prototype simulation that they can virtually manipulate to boost its performance. It’s a low-risk way to test, fail, learn, and create better products.</p>



<h3 class="wp-block-heading">Don’t Wait to Invest in Digital Twins</h3>



<p>Digital twins are a core enabler for Industry 4.0. But the truth is that many firms are already watching this space. The proof: digital twin investments <a href="https://www.mckinsey.com/industries/industrials-and-electronics/our-insights/digital-twins-the-key-to-smart-product-development">are set to reach $73.5 billion by 2027</a>.</p>



<p>It’s clear that manufacturers using digital twins will gain a leg up in this next phase of industrial innovation. Invest now or risk falling behind. </p>
<div class="saboxplugin-wrap" itemtype="http://schema.org/Person" itemscope itemprop="author"><div class="saboxplugin-tab"><div class="saboxplugin-gravatar"><img alt='Jason Hehman' src='https://secure.gravatar.com/avatar/8260f2dda367a977ff4db8d5054f256d?s=100&#038;d=mm&#038;r=g' srcset='https://secure.gravatar.com/avatar/8260f2dda367a977ff4db8d5054f256d?s=200&#038;d=mm&#038;r=g 2x' class='avatar avatar-100 photo' height='100' width='100' itemprop="image"/></div><div class="saboxplugin-authorname"><a href="https://www.clouddatainsights.com/author/jason-hehman/" class="vcard author" rel="author"><span class="fn">Jason Hehman</span></a></div><div class="saboxplugin-desc"><div itemprop="description"><p><em>Jason Hehman is a Client Partner at </em><strong><em><a href="https://txidigital.com/">TXI</a></em></strong><em> and the Vertical Lead for Industrial Innovation and Industry 4.0 at TXI. He helps clients come up with innovative solutions to their most difficult challenges by building integrated teams of their own, transforming company cultures, and supporting new products and services that optimize the ways they and their customers do business.</em></p>
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		<post-id xmlns="com-wordpress:feed-additions:1">4726</post-id>	</item>
		<item>
		<title>Accenture, Microsoft Complete Unilever Cloud Migration</title>
		<link>https://www.clouddatainsights.com/accenture-microsoft-complete-unilever-cloud-migration/</link>
					<comments>https://www.clouddatainsights.com/accenture-microsoft-complete-unilever-cloud-migration/#respond</comments>
		
		<dc:creator><![CDATA[David Curry]]></dc:creator>
		<pubDate>Mon, 08 May 2023 13:03:01 +0000</pubDate>
				<category><![CDATA[Migration]]></category>
		<category><![CDATA[cloud migration]]></category>
		<category><![CDATA[customer experience]]></category>
		<category><![CDATA[digital twins]]></category>
		<guid isPermaLink="false">https://www.clouddatainsights.com/?p=2961</guid>

					<description><![CDATA[One of the main upgrades with the migration is an "industrial metaverse" that uses real-time data from simulated digital twin factories to inform physical factory improvements.]]></description>
										<content:encoded><![CDATA[<div class="wp-block-image">
<figure class="aligncenter size-full is-resized"><img loading="lazy" decoding="async" src="https://www.clouddatainsights.com/wp-content/uploads/2023/05/cloud-migration-Depositphotos_277655514_S.jpg" alt="" class="wp-image-2963" width="750" height="563" srcset="https://www.clouddatainsights.com/wp-content/uploads/2023/05/cloud-migration-Depositphotos_277655514_S.jpg 1000w, https://www.clouddatainsights.com/wp-content/uploads/2023/05/cloud-migration-Depositphotos_277655514_S-300x225.jpg 300w, https://www.clouddatainsights.com/wp-content/uploads/2023/05/cloud-migration-Depositphotos_277655514_S-768x576.jpg 768w" sizes="(max-width: 750px) 100vw, 750px" /><figcaption class="wp-element-caption"><em>One of the main upgrades with the migration is an &#8220;industrial metaverse&#8221; that uses real-time data from simulated digital twin factories to inform physical factory improvements.</em></figcaption></figure></div>


<p>Accenture and Microsoft recently <a href="https://newsroom.accenture.com/news/unilever-goes-cloud-only-accenture-and-microsoft-complete-one-of-the-largest-cloud-migrations-in-consumer-goods-industry.htm">announced</a> the completion of one of the “largest and most complex” cloud migrations in history, moving multinational consumer goods giant Unilever and its 400 brands to cloud-only operations. </p>



<p>The key aims of the 18-month project were to accelerate product launches, enhance the customer service experience, improve operational efficiency, and meet the sustainability commitments set by Unilever by reducing carbon emissions.</p>



<p>Unilever is the fifth largest consumer goods company by revenue, according to <a href="https://consumergoods.com/top-100-consumer-goods-companies-2022">CGT</a>, with $62 billion in revenue and a long list of top brands, including Dove, Knorr, Axe, Ben &amp; Jerry&#8217;s, Hellmann&#8217;s, and Magnum.&nbsp;</p>



<p>One of the main upgrades Accenture and Microsoft have built for Unilever is an &#8220;industrial metaverse&#8221; that uses real-time data from simulated digital twins factories to inform physical factory improvements. Unilever already has two factories, in Tianjin, China and Indaiatuba, Brazil, which have <a href="https://www.unilever.com/news/news-search/2023/unilever-sites-join-network-of-worlds-most-digitally-advanced-factories/">been awarded</a> Lighthouse status as two of the world&#8217;s most digital advanced factories. It aims to have more of these through the use of the industrial metaverse platform.&nbsp;</p>



<p>“We’re using advanced analytics to make better-informed decisions quicker than ever before,” said said Steve McCrystal, chief enterprise and technology officer at Unilever.&nbsp;</p>



<p>This includes the use of artificial intelligence to identify trends and make quicker decisions on new product launches, with forecasting services to better understand consumer needs and market changes. Research and development teams will be empowered with high-quality analytics to create items that consumers are asking for at a quicker rate, while also getting a better understanding of why a certain product is not performing as well as expected.&nbsp;</p>



<p>“The path to business resilience now and in the future is through total enterprise reinvention—which involves the transformation of every part of the business—with cloud at the core,&#8221; said Nicole van Det, senior managing director at Accenture. &#8220;With access to the full continuum of cloud capabilities, including generative AI, Unilever has the elasticity to drive innovation faster, accelerate growth and continue to set the pace as a digital powerhouse and leader in its industry.”</p>



<p><strong>See also:</strong> <a href="https://www.clouddatainsights.com/youve-migrated-to-the-cloud-now-what-4-critical-cost-saving-practices/" target="_blank" rel="noreferrer noopener">You’ve Migrated to the Cloud, Now What? 4 Critical Cost-Saving Practices</a></p>



<h2 class="wp-block-heading">Embracing new technologies with the migration  </h2>



<p>Generative AI is a subject on every organization’s mind, and Unilever is taking advantage of Microsoft’s close partnership with OpenAI, by applying Azure OpenAI Service across Unilever’s many brands and departments to enable better customer experiences. What this means on the day-to-day is not clear, but Azure OpenAI Service offers the ability for brands to create campaigns, adverts, and other promotions utilizing data collected on consumer interests and feedback.&nbsp;</p>



<p>“With Microsoft Azure as its cloud foundation, Unilever’s end-to-end digitization will enable rapid innovation across its entire business,” said Judson Althoff, executive vice president and chief commercial officer at Microsoft.&nbsp;</p>



<p>Microsoft has several ways for organizations on Azure to lower their carbon footprint, with its Green Cloud Advisor tool, Unilever is able to transition its cloud operations to be more sustainable and eco-friendly.&nbsp;</p>
<div class="saboxplugin-wrap" itemtype="http://schema.org/Person" itemscope itemprop="author"><div class="saboxplugin-tab"><div class="saboxplugin-gravatar"><img loading="lazy" decoding="async" src="https://www.clouddatainsights.com/wp-content/uploads/2022/05/curry-150x150-1.webp" width="100"  height="100" alt="" itemprop="image"></div><div class="saboxplugin-authorname"><a href="https://www.clouddatainsights.com/author/david-curry/" class="vcard author" rel="author"><span class="fn">David Curry</span></a></div><div class="saboxplugin-desc"><div itemprop="description"><div class="author-info">
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<p>David is a technology writer with several years experience covering all aspects of IoT, from technology to networks to security.</p>
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