Microsoft’s Azure Cloud Services (MS Azure) solutions are amongst the most widely-used and robust on the global market. Whether it’s Microsoft 365 suite or Xbox gaming products, using these MS Azure and MS products leads to digital transformation. Therefore this A3logics blog article reviews exactly how the AI portfolio in MS Azure cloud products drives dynamic outcomes.
So now let’s proceed with our comprehensive discussion about peak performance using MS Azure’s AI technologies portfolio in 2024.
Why Microsoft Azure Cloud suite is one of the essential Public Cloud Services
Primarily, we’ll review the MS Azure Cloud products and services available to customers as a monolithic public cloud provider.
Why MS Azure is one of the leading Public Cloud Services
To begin, let’s review the multi-billion dollar global public cloud market. According to Gartner in late 2022, the worldwide market spending is forecast to reach nearly USD$600 billion in 2023. Altogether, global cloud spending continues its upwards trajectory due to widespread services onboarding as businesses pursue dynamic digital transformation.
Overall, the top three public cloud providers making up the current top 65% — and likely into 2024 — are familiar faces:
- Amazon Web Services (AWS) has 32% of the market share
- MS Azure has 22% of the market share
- Google Cloud Platform (GCP) has 11% of the market share
The remaining public cloud market leaders hold less than 5% of the market each.
MS Azure’s number-two place, Lionel Sujay Vailshery analyzes for Statista, is “owed to Microsoft’s legacy in enterprise IT”. Moreover, Vailshery explains that MS Azure is designed for countless global customers with extensive operating systems and programming languages. “Accordingly, the Azure platform is a popular choice for businesses to leverage technology to achieve their goals,” he says.
Features and functionalities of MS Azure Cloud Services
- Launched in October 2008
- Exceeds 200 cloud services and products
- Available for customers as Infrastructure-as-a-Service, Platform-as-a-Service (PaaS), and Software-as-a-Service (SaaS)
- Over 55% of organizations worldwide use MS Azure
- Seamless hybrid cloud operations for on-premises, multiple clouds, and edge computing
- Highly secure local and global data centers, multilayered security, and intelligent threat protection
- Integratable with existing MS products like Office 365 and third-party integration like Salesforce with MS Teams
- Free and paid subscription services
- Scalable and agile with customizable configurations that meet customer needs
- Extensive data insights with secure enterprise-scale analytics including dashboards and visualizations
- Simplified migration from existing services
- Suitable for widespread industries
- Development and data scientist insights and building products
- Hundreds of certifications in learning mode
Experience the Magic of MS Azure Cloud. The Cloud Computimg Future is Here
The MS Azure Cloud Services AI and ML product range for developers and data scientists
Undeniably MS Azure is an extraordinarily robust cloud offering. With the integration of AI across the MS Azure cloud products, the AI and machine learning (ML) advances business performance. Due to how businesses are empowered to use cutting-edge technologies and leverage intelligent systems, they can transform and advance. Following this they can sustain innovation, growth, and build in their chosen directions through analysis, tools, and overcoming latency. When it comes to MS Azure’s place in the global public cloud services market, their AI technology is fortifying expansion. For CNBC, Jordan Novet reports that in 2023 AI is likely contributing to MS Azure’s 22% market growth. Novet says, “While AWS still leads the pack in terms of overall market share, one reason Microsoft may be picking up business is that companies want to run their artificial intelligence models on Azure.”
AI and ML in Azure Cloud Services
Undoubtedly, MS Azure’s AI and ML technologies are keeping Microsoft at the front of the pack. Microsoft asserts that MS Azure is designed for businesses to use AI while also building their own AI and ML solutions. Moreover, the Azure AI Infrastructure provides businesses with, “A purpose-built AI supercomputing infrastructure for accelerating innovation”.
Not only do these tools equip businesses to enrich their operations with AI, Microsoft puts forward that Azure for AI:
- Helps businesses build their teams
- Leads to businesses deploying mission-critical AI solutions
- Supports responsible AI application
Here we’ll provide an overview of the key AI and ML technology across the Azure Cloud Services range:
-
Azure AI infrastructure
Firstly, across the entire MS Azure product range, AI technologies (AI and ML) are thoroughly integrated. In detail, they also offer the Azure AI portfolio (thorough explanation following this section) that incorporates a range of products. Overall what’s most important about this is that it’s largely designed for users without specialized ML or data science knowledge. Moreover, this AI technologies integration makes functionalities accessible which helps enterprise customers leverage everything from analytics to automation.
-
Machine Learning (ML)
Secondly, MS Azure equips developers and data scientists to use and build ML models that transform businesses. In particular, their Azure Machine Learning product, from the Azure AI Solutions, offers ML operations (MLOps). Furthermore this end-to-end ML lifecycle product works in tandem with MS Azure products and third-party applications. Therefore the ML solutions built are built according to business needs while adhering to responsible AI principles. Simultaneously in the Azure AI Services, ML technologies are part of the wider MS Azure range. Both building and using ML is available to MS Azure enterprise customers.
-
Large Language Models (LLMs)
Thirdly, MS Azure uses LLMs across their Azure AI products. Essentially, the LLMs available provide enterprise users the chance to evaluate, customize, and deploy AI capabilities such as GPT-4. Sarah Bird explains for Microsoft, “Embedding Llama 2 and other pre-trained large language models (LLMs) into applications with Azure enables customers to innovate faster, by tapping into Azure’s end-to-end machine learning capabilities, unmatched scalability, and built-in security.” Further to this, MLOps can be leveraged for LLMOps. Above all, the innovative LLMOps advancements lie with the fact that advanced ML capabilities are in place throughout LLM lifecycle.
-
Generative AI (GenAI)
Fourthly, Microsoft is an ongoing force in AI and its research pipeline goes a long way back. Even so, their major strides in Generative AI (GenAI) go hand-in-hand with their investment in OpenAI. Since 2019 — well before the epoch-defining ChatGPT model GenAI chatbot launch — Microsoft has been an OpenAI partner. Subsequently, MS Azure and ChatGPT have inextricable links with OpenAI running their cloud operations exclusively on Microsoft cloud services. Jordan Novet illuminates that OpenAI’s GenAI is integrated in products including GitHub coding tools and the Microsoft 365 productivity bundle. Specifically, “Startups and multinational companies, including Microsoft, are rushing to integrate their products with OpenAI, which means massive workloads running on Microsoft’s cloud servers.”
Accordingly MS Azure offers GenAI in multiple functionalities across cloud products and solutions. Currently the ChatGPT model and Microsoft’s Bing Chat share some foundational technology though they’re not the exact same GenAI. Nevertheless, the leading takeaway for businesses is how these tools can be integrated across MS Azure products.
-
Conversational AI
Lastly, this MS Azure AI technology equips customers to utilize and deliver world-class, enterprise-grade analysis and data retrieval. In particular, the Azure AI Bot Service is a flagship product for swift bot-building, safe scaling, and computer vision.
How MS Azure Cloud Services solutions range uses AI and Machine Learning (ML)
Now that we’ve reviewed the current leading AI in MS Azure Cloud Services, we’ll delve into the AI Solutions range.
Microsoft cloud services AI and ML Solutions range characteristics and functionalities
They key fact for businesses to know is that the majority of AI technologies are developed in partnership with OpenAI. Microsoft CEO Satya Nadella specifies this AI portfolio is a strategic step for Azure’s parent company. “As you know, AI projects are not just about AI meters,” Nadella says, “They have lots of other cloud meters as well.”
In addition to this, Microsoft’s AI technologies are maturing and being integrated across their wider product range. On the one hand, there’s the Bing search engine Copilot integrating ChatGPT meaning the interactive model has live data sources. On the other hand, there’s Microsoft Teams integrating AI to automatically detect voice and audio issues on conference calls. Crucially, CNBC notes Microsoft infrastructure is, “the underlying computing power for the popular ChatGPT chatbot and other products from OpenAI”. Basically then enterprise customers can see extensive AI functionalities and product options with MS Azure AI and ML solutions.
Significantly MS Azure products are for:
- Accessing high-quality vision, speech, language, and decision-making AI models
- Integrating AI through simple API calls, and creating ML models using an AI supercomputing infrastructure
- Leading tools like Jupyter Notebooks and Visual Studio Code
- Programmer open-source frameworks like TensorFlow and PyTorch
- Using technologies backed in Microsoft’s responsible AI principles
- Flexibility, customization, personalization, and intelligent, empowered operations
- Robust cybersecurity with live insights, threat analysis, and parsing of billions of data points
- Cost-effective access to the newest AI and ML
- Multilingual prompts including translation services for more than 100 languages and dialects.
Leading MS Azure AI and ML products are:
- Automated ML
- ML designer
- Responsible AI
- MLOps
- Knowledge mining
- Conversational AI
- Document process automation
- Machine translation
- Speech transcription
- Vision
- Bot Service
- Azure OpenAI
- Azure Cognitive Search
Industries already using Microsoft cloud services AI Solutions include
- Financial services
- Manufacturing
- Retail
- Health
- Transport
- Pharmaceutical
- Sport
- Entertainment
- Tourism
- Media
MS Azure Consulting Partners and MS Azure AI credentials for MS Azure Cloud Services
Concurrently to their AI Solutions range, Azure AI and ML certifications are also available for developers and data scientists. Because industry professionals can complete qualifications in the MS Azure that are AI and for ML, this adds product value. Both Azure Consulting Partners and enterprise customers benefit from these credentials as it contributes to building AI products and configuration.
What MS Azure Cloud Services certifications exist for AI and ML
Broadly speaking, the leading certifications for Azure AI and ML are:
- Azure AI Fundamentals
- Azure AI Engineer Associate
Why this benefits data scientists and developers using MS Azure
Once developers and data scientists hold these certifications, they can apply their training to Azure AI Solutions. Alternatively they can work as an AI engineer or an AI Edge Engineer for MS Azure and software development companies. These certifications can be applied in both cloud and hybrid environments for cognitive services, ML, and knowledge mining.
Why businesses should hire MS Azure Consulting Partners with Azure AI certifications
There are two key reasons for why Azure AI certifications are invaluable in the MS Azure enterprise ecosystem.
In the first place, MS Azure Consulting Partners are software development and industry organizations who are official Azure Experts. These partners, “Bring aboard high-quality consulting and delivery services plus a depth of expertise addressing specific, complex solution areas within Azure,” Microsoft says. It’s important to note that these partners have expertise and are official providers that can invent and deliver unique solutions. Therefore enterprise customers can inarguably derive more value from their MS Azure service with Consulting Partners than without them.
In the second place, MS Azure Consulting Partners are typically platform-certified expert teams of developers, data scientists, and architects. Their certified qualifications add to their platform knowledge with product insights refined through training and experience.
All in all, in this pivotal era of AI advancements and rapid developments — combine with digital transformation objectives — expert matters. Consequently certified MS Azure Consulting Partners are the best call when enterprise customers are seeking pursuing maximum cloud computing value. They have access to solution functionalities exclusive to Consulting Partners and they apply qualified technical skills to MS Azure.
Looking to Elevate Your Enterprise with Microsoft Azure Cloud Services?
How MS Azure Cloud Services AI portfolio supports businesses
Following on from our explanation of MS Azure AI certifications, we can discuss five strategic objectives AI and ML facilitates:
1. Advanced user experience (UX)
With AI functionalities, businesses have the most intelligent workflows, customer experience (CX), and advanced systems of all time. Redesigning user experience (UX) in business applications using MS Azure AI technologies is a smart tactic because it’s highly cohesive. In fact, businesses can work on improving their staff UX with in-built Azure bots that provide better customer engagement. As an all-in-one UX solution, this can be used as a 360-degree approach to transforming stakeholder outcomes.
2. Streamlined operations
In like manner, an outcome that’s equally beneficial is businesses using AI and ML technologies for streamlining their operations. Whether to revise resource management based on AI analyzing workloads or finding automation opportunities, these technologies simplify streamlining efforts. Overall strategic streamlining of common operations are a valuable Azure AI and ML functionality. For example, using ML to standardize customer communications as per brand voice or leveraging ChatGPT to check developer code. Both of these options increase accuracy without any extra effort from team members or allocation of additional resources.
3. Remote processes
Recently more businesses than not are offering completely remote operations. When they have hybrid teams or multiple office locations, they’re likely powered using MS Azure Cloud Services. Though using Azure cloud solution is assumed, all businesses benefit from AI integration to fortify remote processes. Especially for business building, the human resources and productivity benefits are countless. For example, teams from all over the world can seamlessly use the same systems with Azure AI translation services. Simultaneously new team members can onboard easily with the Azure Virtual Desktop with swift setup regardless of their location. Also if employees are on different timezones, they can always turn to company-trained virtual assistants for accurate, immediate support.
4. Intelligent data insights
Emphatically, a leading attraction for every AI and ML technology user is data insights. Neither the elimination of cumbersome data processing nor time freed when businesses use ML data tools can be underestimated. Accordingly there are extensive specialized MS Azure tools for GenAI and multimodal data insights. Across the board, business data becomes an asset for internal use or even as a unique value proposition for customers. Whether it’s Azure SQL, building apps with AI-powered Azure Cognitive Search, or Azure AI Services — knowledge mining delivers value.
5. Cybersecurity standards
Chiefly MS Azure Cloud Services are among the most secure public cloud providers. Because they spend $1 billion annually on research and development, Azure’s development and testing AI security lifecycle capability is verified. Their cybersecurity standards lead to products like Microsoft Sentinel that provides intelligent security analytics and Azure AI Content Safety. Since businesses all over the world — irrespective of enterprise size and industry — are likely to experience cyberattacks or data breaches, intelligent cybersecurity is yet another factor in peak performance.
Forecasting AI developments for MS Azure Cloud Services in 2024
Prior to reviewing U.S. MS Azure AI case studies, we’ll review AI forecasting for 2024. After all 2023 was one of the most momentous and historic years for AI and technological developments in history. Given that, many experts and enterprises alike are wondering what the next 12 months of AI products and updates holds.
-
Continued growth in MS Azure Cloud Services tied to AI products
It’s definitely very likely that growth in the MS Azure AI Solutions group will continue. Whether that’s adding new products or further technological AI and ML integrations across the cloud solutions. Undeniably we’re seeing unprecedented advancements in AI technology across the board. Therefore we can expect that even if growth slows, MS Azure will remain on-track in its upwards market trajectory.
-
Multimodal AI realized in MS Azure Cloud Services
Though rumblings early in 2023 suggested that OpenAI’s ChatGPT would be multimodal, Microsoft got there first with their Visual ChatGPT. Since then, GenAI has continued its training updates and now products are on the precipice of managing simultaneous multimodal prompts. Where this goes next is certainly a “watch this space” however this advances virtual — metaverse — reality aspirations and product potential.
-
Ongoing Microsoft partnerships for AI
Together with OpenAI, Salesforce, and Meta, Microsoft’s partnerships are a force to be reckoned with. When it comes to how this affects AI solutions and Azure Cloud Services, we can look to their extensive integrations. From Salesforce Customer Relationship Management (CRM) integrations for business customers to being a preferred partner for Meta AI’s Llama 2, their partnerships demonstrate both research and application reach. As AI and ML technology keeps progressing in the year ahead and beyond, we expect these partnerships to continue evolving in practically demonstrable ways that drive performance and innovation.
Three MS Azure Cloud Services customer case studies of AI technology use
Finally, we’ll review three U.S. customer case studies of Azure Cloud Services solutions. These three businesses use Azure AI products and worked with MS Azure Consulting Partners for their custom cloud solution.
1. Twitter / X
The social media company Twitter, now renamed to X, makes its platform more accessible and user-friendly with MS Azure. In reality, they use MS Azure Cognitive Services for speech-to-text that helps the platform uphold their inclusivity values. With over 100 languages and variants available, this handles real-time transcription that includes and keeps all users in the conversation.
2. Walgreens Boots Alliance
Another business user of MS Azure Cognitive Services, pharmacy and healthcare retailer Walgreens Boots Alliance (WBA) use AI for communications. During the Covid-19 pandemic, they utilized the Azure AI technology to inform customers and support them with remote health. To list, this included seamless integration of question-and-answer bots, telehealth access, and even third-party healthcare provider connections.
3. CarMax
For three decades, CarMax has been a U.S. disruptor in the used car market. Accordingly they were early AI adopters and used the MS Azure OpenAI service to streamline their website content administration. Auto-generated AI content helps them accurately list cars on their business site which includes text summaries about products. Subsequently they CarMax now view themselves as an omnichannel retailer thus proving the digital transformation power of Azure cloud services.
Unleash The Full Potential of Cloud With Microsoft Azure Services
Conclusion
Evidently the MS Azure Cloud Services AI portfolio has enough variety to be a robust next-generation business solution. In conclusion, enterprise customers can confidently invest in MS Azure and benefit from comprehensive AI for a range of needs. Nevertheless MS Azure Consulting Partners like A3logics have an essential role to play in long-term solutions. Though Azure’s AI products don’t require developers or data scientists for use, expertise is a game changer. Despite the highly user-friendly product suite, certified and experienced partners have the platform knowledge to configure for performance objectives. uently businesses should begin with a planning consultation for their MS Azure AI strategy, they can discuss needs with professionals. Afterwards they can proceed with an informed outlook for their investment and decide their course of action for MS Azure.
Frequently Asked Questions (FAQs)
Do all Microsoft Azure Cloud Services have AI technologies?
Currently Microsoft have integrated their AI technologies across their entire Microsoft Azure (MS Azure) Cloud Services products range. This includes technology like their Bing Chat tool and their partner OpenAI’s generative AI (GenAI) ChatGPT model. Right now, these AI technologies along with Large Language Models (LLMs), machine learning (ML), and conversational AI are widely available. Additionally customers can also purchase AI Solutions to build out their own Azure Cloud Solutions. When they do this, enterprise customers gain additional functionalities like Azure Cognitive Search that uses AI for smarter data retrieval.
What benefits are there for hiring MS Azure Cloud Consulting Services?
There are significant benefits to hiring MS Azure Consulting Partners like A3logics for two key reasons:
- MS Azure Cloud Services expertise and experience
- Developers, data scientists, consultants, and architects certifications
Generally speaking these two key points work together as MS Azure Consulting Partners typically have extensive industry experience with MS Azure. Equally they are recognized members of the Microsoft global network of service providers. They have certain access to cloud services functionalities and scalability that non-partner subscribers don’t. When combined with the official Azure certifications, their teams are highly trained in the cloud solutions and will have specialist expertise. This is based in their qualifications completed through Microsoft. With their credentialled certifications, these team members have an in-depth platform understanding and are capable of highly advanced configurations. Altogether then, working with MS Azure Consulting Partners can deliver far more subscription value in line with enterprise customer needs.
Is it worth hiring MS Azure Cloud Consulting Services for AI and Machine Learning (ML) products?
Overall AI and ML are newer technologies that benefit from expert insights. Whether for planning a roadmap strategy for future integration or needing to start using AI technologies immediately, expertise helps.
Accordingly it’s immeasurably valuable for businesses to gain accurate input on the full MS Azure Cloud Services range. When businesses hire consultants for this, consultation is lengthy, needs assessment happens, and then MS Azure products are specifically considered. This informed decision-making process is helpful for designing an AI/ML usage plan and choosing from AI/ML technologies. Consequently businesses will actually receive expert advice on the AI tech they need, configuring it, and then using it.
Can businesses use the OpenAI ChatGPT product without MS Azure Cloud Services?
Businesses can definitely use OpenAI’s ChatGPT model without an MS Azure Cloud Services subscription. Currently they can access this for free via OpenAI though its performance may not be to an enterprise-standard. Further to this, businesses can purchase Plus and Enterprise subscriptions for more robust performance ChatGPT that can handle more prompts.
Despite this, if businesses wish to use MS Azure Cloud Services with ChatGPT then this is an advanced, enterprise product. Not only does this have the high-level capabilities of Plus and Enterprise but also it uses MS Azure technologies. The MS Azure OpenAI Service equips enterprises to build, apply, and leverage advanced language models for highly sophisticated AI outcomes.