Amazon Web Services commonly shortened to AWS is the world’s leader in public cloud services. Not only is global cloud services’ market revenue around half a trillion USD but also AWS has 32% market share. Moreover the other two leading providers, Microsoft Azure and Google Cloud Platform trail with 22% and 11% respective shares. It’s no surprise that Statista writer Felix Richter asserts Amazon was an “early leader in the market for cloud infrastructure”. When we evaluate the current market, AWS cloud services continue to be central to 21st century businesses and digital transformation.
Nevertheless, how is AWS faring in this “golden age of Artificial Intelligence (AI)”? After all, this current unprecedented technological advancement we’re seeing speaks to nonstop record-breaking development. Currently AI products are changing the world within days and 2023 alone was a year of extraordinary digital transformation. Basically AWS is the global leader in cloud services, serving thousands of businesses, and their AI technology affects entire industries. Every business should be aware of what’s on offer, how it’s shifting AWS cloud portfolio, and AI services awaiting us.
With these points, we’ll review key facts, statistics, and examples to ensure businesses gain a comprehensive insight into AWS AI.
To begin, let’s unpack why Amazon Cloud Services are a choice for countless businesses all over the world. Considering the top three public cloud providers — AWS, Microsoft Azure, and GCP — have 65% of the total public cloud market. Significantly though, AWS holds almost half — 32% — of this almost two-thirds market share.
Overall, Lionel Sujay Vailshery describes for Statista, “Accordingly, AWS offers a wide range of cloud-based products, including databases, analytics, management tools, security, IoT, enterprise applications, and developer tools.”
Now that we’ve reviewed the foremost AWS value propositions, we’ll progress to a 2023 overview of the AWS cloud products.
Amazon maintains its top spot in cloud services as a reliable cloud solution with proprietary products and extensive native features. In particular, AWS has deep security tools with more than 300 security, compliance, and governance services and functionalities. Additionally AWS supports 143 security standards and compliance certifications.
Overall, Lionel Sujay Vailshery describes for Statista, “The company continuously expands its repertoire of services to meet its customers’ changing needs and thereby advances industry standards and practices.” The AWS ecosystem facilitates seamlessness across all products that supports businesses to scale and adopt new technologies as they’re released. In essence, this makes AWS a logical choice for customers seeking solutions that are agile, encouraging innovation, and cost-effectiveness. Mark Haranas at CRN effuses, “From new generative AI tools to supply chain and cybersecurity services, the innovation engine at Amazon Web Services in 2023 has been roaring.”
Hence AWS is a robust product suite that suits everyone from developers and retail businesses to data scientists and analysts. Because AI is in tandem with digital transformation and AWS is the world’s number one public cloud product, technology matters. On this front, Amazon CEO Andy Jassy said in 2023 that AWS’ future in GenAI in particular is bright. Jassy says, “Let’s just say that LLMs [large language models] and generative AI are going to be a big deal for customers, our shareholders and Amazon.”
So what does this look like as we approach 2024? Emphatically Mark Haranas at CRN effuses, “AWS’ focus in 2023 has been on launching new product offerings around generative AI, data security, serverless, Internet of Things, unified software development and cloud cost optimization.” We’ll now explain AWS’ key AI and ML releases and updates in 2023 and what’s coming in 2024.
Before we review these, we’ll note that AWS presents their AI products and solutions under the ML banner. Specifically Amazon says, “AWS helps you at every stage of your ML adoption journey with the most comprehensive set of artificial intelligence (AI) and ML services, infrastructure, and implementation resources.” Currently AWS has over 100,000 customers using their AI/ML products with hundreds of algorithms and models in AWS marketplace. Evidently AWS’ strategic objective with these solutions is to equip customers to seamlessly build, automate, personalize, and streamline their operations.
The AWS deep learning models help make AI technology in the cloud suite much more accessible to enterprise customers. Moreover developers can actually use LLMs like Meta AI’s Llama in AWS for code generation in Amazon CodeWhisperer. Equally Amazon SageMaker can be used to start building models that can then be integrated with other AWS cloud products.
AWS taps into the GenAI vertical with a range of models available across the cloud suite. Whether using their own Amazon models or A121 Labs through to Meta and Stability AI, customers can customize in Amazon Bedrock. Accordingly Amazon is committed to responsible generative AI practice while still offering customers access to cost-effective GenAI infrastructure.
This AI technology in AWS is through natural language processing (NLP), natural language understanding (NLU), and natural language generation (NLG). Thus businesses can deliver personalized, automated, intelligent, and consistent customer service and stakeholder engagement. Currently Amazon’s Conversational AI (CAI) is available across multiple products: Amazon Kendra, Amazon Polly, and contact center product Amazon Connect. Additionally businesses can use third-party CAI integration to build custom interactive interfaces or build scalable experiences using Amazon Lex. While not strictly an AWS product, the Alexa Internet of Things (IoT) is likely to have further CAI advancements soon.
Though not entirely realized, the promise of multimodal AI represents the next frontier of AI. Because AWS already offers a range of ML models that can handle voice, text, and image prompts, multimodal awaits customers. For instance, Amazon has a partnership with Stable AI whose Stable Diffusion GenAI model responds to text and image prompts. Amazon Bedrock and Amazon SageMaker use Stable Diffusion as a foundation model for a range of tasks and creative output. When it comes to forthcoming Amazon technology — both cloud solutions and hardware — multimodal AI is highly important for innovative activities.
Now that we have a clear picture of the leading AI technologies in AWS, let’s review twelve exciting usage opportunities. The following examples are for enterprise customers across all industries so that they can understand the dynamism of AWS’ AI.
Undeniably one of the most exciting aspects of AI technology is how it empowers users to create from prompts. With the Amazon and Stable AI partnership, AWS customers can use generative multimodal AI for images from text and voice. Whether for mock-ups or first impressions of ideas, this AI completely transforms the creative process.
AWS Amazon Aurora databases at an astonishing rate with the addition of ML to applications. Thus the AI can make ML-based predictions using SQL programming language. Both the simplicity and security of this integration helps businesses gain even more from their data. At the same time, data backups can be automated and continuous without compromising database performance.
Recently AWS announced that their Amazon Bedrock product would soon become more powerful. Beyond its building and scaling capabilities for GenAI applications, the Amazon Titan LLM may well become generative as it matures. Coupled with foundation models (FM) built into Amazon Bedrock, the AWS generative capabilities will likely advance thus fortifying the cloud.
Altogether how customers from differing industries use AWS will likely continue to shift in the years ahead. For instance, current industries leveraging AWS AI technology include healthcare bodies and customer relationship management companies. In time, many businesses from varying industries will find innovative and customized ways to use AWS AI. Indeed this may be for advanced compliance or better employee care; either way there is significant untapped potential for everyone.
Since AI will be a core pillar of all software development and business solutions sooner rather than later, credentials matter. Hence AWS will expand their AI-specific credentials so software development companies will have deeper technical knowledge. From here customers will then be able to work closely with AWS Consulting Partners to gain the maximum AI efficacy.
Evidently cybersecurity is another fundamental component of 21st century business. Not only because threats are increasing but also due to widespread digital transformation. With mass onboarding to cloud services, AWS is already working to build smarter data centres and deepen security analysis functionalities. Undoubtedly the AWS approach of building security into AI training and implementation ensures better use. For example, AWS is using GenAI for comprehensive security — both on the side of the AI and in the cloud.
While GenAI is revolutionizing everything from user experience (UX) to analytics, a colossal opportunity for advanced chatbots exists. As GenAI becomes multimodal, chatbots and digital assistants will advance in capability, accuracy, and responsiveness. Whether for customer service or worker productivity, the fact that these tools will respond to multimodal prompts promises dynamic value. The advanced range of functionalities in these AI tools will improve workflows, stakeholder experiences, refine personalization, and maintain compliance.
Following on from chatbots is the related advancements of AI integration in hardware: IoT. Though this relates to Amazon’s products branch, as hardware and AI integration improves this expand tool options for AWS customers. In fact, AWS reports that Alexa Voice Service (AVS) is now integrated as a feature of AWS IoT Core. Seeing that Alexa is a highly recognizable Amazon product, this offers new pathways for AWS integration for some businesses. What’s more, AWS reports that “The Alexa Voice Service (AVS) Integration is a new feature of AWS IoT Core that enables device makers to make any connected device an Alexa Built-in device.” The immediate diversification of IoT tools being integrated with AWS processes is an invaluable value proposition for AWS enterprise customers.
Without doubt, the continual advances in AI are definitively making core global business activities more effective. The multi-billion dollar national and international networks for supply chains have been under significant pressure since the pandemic. Now AI helps the AWS Supply Chain tool have enhanced accuracy leading to more sustainable, more efficient, and seamless logistics. Furthermore AI analytics deliver live insights, predictions, and reporting so that end-to-end network of processes has greater resilience.
Enhanced and more nuanced system load balancing makes an incomparable difference to the AWS UX. Though a lesser-known benefit of AI technology, load balancing is a crucial component of AWS cloud products. Because their global network of servers and Points of Presence is relied on by millions of customers, maintaining strength matters. AI enhances this by identifying issues more quickly and improving the speed of data despite high traffic. Additionally AI and ML can actually predict traffic in advance and schedule load balancing for dynamic scaling. As businesses continue their digital transformation, this is even more important and success depends on seamless infrastructure.
Despite AWS databases becoming more robust with AI technology, there is major potential for Amazon S3 in particular. The Amazon S3 (shortened from Simple Storage Service) is the robust engine behind high volume data storage. “Customers of all sizes and industries can use Amazon S3 to store and protect any amount of data,” explains AWS.
The extensively varied storage includes:
Obviously the scope of AI in this case is massive and one core product, Amazon Lookout for Metrics, uses ML. When businesses connect this AWS product to the S3 data store, ML automatically work to review, detect, and diagnose anomalies.
Following on from is ML in S3 is how data analysis is advanced in the Amazon Athena product. The serverless product uses standard structured query language (SQL) to “process logs, perform data analytics, and run interactive queries”. ML technology helps simplify SQL queries without compromising complex query results. Therefore AWS users can run inference to detect anomalies, analyze their customer base, and even make sales predictions. Additionally ML models deployed on Amazon SageMaker can be run simply for any team member with basic SQL experience. Hence AWS customers extrapolate even more valuable insights about their data that can help them identify opportunities and negative trends.
Finally to round out this AWS AI technology discussion, we’ll review three case studies of leading U.S. companies. From three varying industries — Entertainment and Media, Finance, and Transport — these case studies demonstrate the dynamism of AWS AI applications.
The world’s leading internet television network Netflix is a titan of online streaming. Both for hosting media and now producing original TV shows, movies, and documentaries, Netflix is a true industry disruptor. Currently Netflix uses AWS for the majority of all computing and storage needs. Specifically this includes databases, analytics, recommendation engines, and video transcoding — more than 100,000 AWS server instance. In order to consistently deliver on load balancing requirements, Netflix opted for AWS cutting-edge technology that delivers streaming quality. The AI and ML features are crucial to maintaining robust systems for viewers and content creators alike.
When U.S. financial services Capital One Financial Corporation took a huge company leap and went “all-in” on the cloud, they chose AWS. Prior to 2020, they still used legacy, on-premises data centers. Nevertheless they pursued immeasurably significant digital transformation migrating to AWS Lambda. Despite strict parameters for “code patches, machine refreshes, and bug remediation”, they successfully made a cost-effective transition with AWS. Since then their engineers — the majority of their staff — have been able to focus on building applications using AI tools. Overall they have greater efficiency and are continuing their journey to modernize systems and products with AWS.
For almost a century, United Airlines (UA) has been a heritage U.S. brand serving domestic and international guests. Because of their expansive route network across 193 countries and thousands of daily flights, their operational systems must be robust. Therefore when they sought to advance their digital products and customer service tools, their choice was AWS. Now their intelligent systems offer everything from end-to-end data analytics and insights to “personalization at scale”. In particular, their partnership with Formation.ai helped them leverage ML through AWS to deliver their gamified miles redemption program. All in all, UA is able to be more meaningfully, consistently, and demonstrably customer-centric leading to better business outcomes.
Partner With AWS consultants at A3logics
In conclusion, AWS AI technologies are progressing incredibly quickly. Although a major product launch — as of October 2023 — is yet to be confirmed, their research department is certainly active. While many experts speculate that Azure and GCP may close in on AWS’ market share, Amazon retains a strong foothold. Accordingly we can argue that their commitment to sustained innovation and now AI technology indicates they’ll continually be cloud leaders.
Even so, businesses should always understand that it’s not solely the quality of the product that’s important but the usage. Hence undertaking a comprehensive AWS roadmap strategy that’s devised according to business needs and leverage AI cloud technology is crucial. Then businesses can be ready for new product launches as AWS AI advances without disruption to existing operations and priorities.
Starting with a preliminary consultation, A3logics dedicated AWS cloud solution teams will analyze precisely what your business needs. Their expertise incorporates extensive market insights for U.S. and global operations across wide-reaching industries. For over 20 years A3logics has been delivering software solutions designed, deployed, maintained, and scaled for each client’s business needs. Every development begins with the certified AWS consultant team meeting to assess the right cloud products and execute precise solutions. When it comes to AWS, A3logics expert AWS Premier Consulting Partner team is dedicated to transformative cloud solutions.
AWS is available as all three “as-a-Service” options: Infrastructure, Platform, and Software. Altogether the mix of these options for the cloud platforms supports businesses to find the dynamic products suitable for them. Accordingly AWS has devised a range of products that also mean businesses can opt for hybrid cloud or multi-cloud. Further to this businesses are in a position to continually scale their cloud systems and immediately harness new AWS features.
The AWS Consulting Partner paths are designed to help their cloud customers accelerate how they use their solution. When a software development company is an AWS Consulting Partner, enterprise customers will benefit from their deep expertise. In fact, this means businesses have access to additional features that the Consulting Partners can unlock while delivering custom solutions. Then over time this ensures simplification and acceleration of scaling and solution updates plus expert guidance to using AWS. Before formally hiring AWS Consulting Partners, businesses should have an initial consultation with experienced cloud solutions specialists. With over 20 years of development experience, A3logics dedicated AWS cloud solution teams bring AWS certification and proven optimization capabilities.
Since AWS is integrating robust deep AI models and technologies across their hundreds of products, customers can definitively maximize AI. Even so understanding what the technology does, what their objectives are, and how to leverage these advanced functionalities requires planning. Accordingly, working with a software development cloud solutions team helps with needs evaluation and understanding AI technology usage potential. Consequently businesses benefit from working with a development team who will ensure implementation of an AI digital transformation strategy. Furthermore, working with an AWS Consulting Partner to identify AI use in the short-term and long-term helps scaling. Because the developers will know their needs and how they’re progressing with AWS AI technology, they’ll advise them about new models they can use to achieve key goals.
At present, AWS has Generative AI (GenAI) across products including Amazon Kendra, Amazon Polly, and customer service product Amazon Connect. Businesses can choose from a range of GenAI models to support their needs. For example, Stable Diffusion for natural language processing (NLP), natural language understanding (NLU), and natural language generation (NLG). Additionally AWS products can be integrated with third-party GenAI as well as developer tools for building custom solutions.
