AWS in 2024: focus on AI and the skills shortage

Amazon Web Services (AWS) is by far the largest cloud provider in the world. With a wide range of new services and improvements to existing offerings, AWS intends to further consolidate its position as market leader in the year that has just begun. The latest developments in the areas of artificial intelligence (AI), machine learning (ML), the Internet of Things (IoT) and serverless computing will influence AWS' future developments on several levels. The recent launch of Amazon CodeWhisperer, an AI-powered code generator that increases productivity through security checks and accelerated code deployment, is just the first step.

AI services such as AWS Sagemaker are also becoming increasingly important. Sagemaker supports companies in developing and improving their own machine learning models. In addition, AWS is increasingly focusing on predictive analytics in 2024 by providing improved or completely new tools and services. For example, Amazon Forecast, a fully managed service that uses machine learning to deliver highly accurate forecasts, enables businesses to get improved demand forecasts for their products, perform better financial planning and ultimately increase business efficiency.

Tools such as AWS CloudFormation, which can be used to automate the provisioning of cloud environments, make it much easier for companies to maintain and manage their cloud infrastructure. It also significantly reduces costs. Another increasingly important tool is the Amazon Q AI assistant, which can be integrated into IDEs and was announced in December 2023. The tool is not unlike ChatGPT and can be consulted on AWS practices and procedures, for example. Amazon Q can also be used to analyze and resolve any problems directly in the AWS console.    

Sustainability, safety and a shortage of skilled workers

Despite its successes, AWS faces some significant challenges. We live in a time where sustainability and security are key factors in cloud computing. AWS wants to demonstrate its commitment to a sustainable future by setting up CO2-neutral data centers and using environmentally friendly technologies. In addition, AWS is emphasizing its focus on security and compliance by introducing enhanced security features and continuously developing its compliance standards.

The aforementioned management of the complexity of its extensive range of services and ensuring security in a constantly changing threat environment are key aspects of this. In addition, AWS, like its customers, is facing a growing skills shortage, primarily due to its own rapid growth. It is therefore to be expected that AWS will increasingly invest in training programs and certifications in order to train specialists for itself.  

However, it is also becoming increasingly important for AWS to simplify the management of its increasingly complex platform, which now has over 200 services. AWS will and must increasingly face this challenge for the benefit of its customers in 2024 and beyond. The shortage of skilled workers not only affects AWS, but of course also the cloud provider's customers. The shortage of skilled workers is creating a growing skills gap among customers, which AWS cannot solve itself, but which it must address by simplifying the operation of its platform. This is probably the most important task facing AWS on the road to a successful future.

Competition and market dynamics

Increasing competition in the cloud market is forcing AWS to constantly evolve and tap into new markets. With new technologies such as AI, ML and IoT, AWS is expanding into new markets. However, the ability to adapt quickly to changing market conditions and, above all, to effectively counter the shortage of skilled workers on the part of AWS and its customers will be crucial for AWS to maintain its market leadership in 2024 and beyond.

Future-proof jobs with AWS Machine Learning & AI

With the courses on AWS Machine Learning & AI from Skill IT, you are well positioned for the future. For example, learn in the course Amazon SageMaker Studio for Data Scientistscourse to learn how you as a data scientist can create ML models with fully managed infrastructure, train them and reduce training time to minutes with optimized infrastructure. Or learn in the course Deep Learning on AWScourse to learn how to deploy deep learning models using services like AWS Lambda and develop intelligent systems on AWS.