Cloud as a service is a business model that combines the cloud infrastructure delivered to customers as a subscription-based service, where the customer can access a cloud infrastructure without running it on-premise. Therefore, the whole premise of the cloud as a service business model is to offer a more agile cloud infrastructure at a fraction of the costs compared to on-premise software, and that can be scaled up according to the need of the business.
The new software paradigm: from proprietary to on-cloud premises
By the early 2000s software paradigms shifted. From on-premise, heavy software infrastructure to online-based, cloud infrastructure. Indeed, the web enabled companies to start building a cloud infrastructure that could host other servers.
This is part of the agile transformation. Where software infrastructure is hosted online, much lighter, and based on continuous updates so that it can be quickly iterated, and improved, based on users feedback loops.
This, in turn, brought also in the business world, to the phenomenon defined as continuous innovation, where business transformation is led by quick feedback loops between the company’s operations and its customers.
A further progression of this evolution is from a software-centered approach, where continuous innovation plays a key role, to a customer-centered approach; where continuous innovation coupled with continuous intelligence, dynamic technological stack, and continuous deployment and delivery become critical.
The cloud industry in a nutshell
With the advent of the Internet, and the fact the web scaled globally, cloud computing became the main paradigm.
Cloud computing expresses itself in three main business models: IaaS, PaaS, and SaaS.
These models ended up creating a new trillion-dollar industry, which is behind most of the digital and tech companies existing in today’s business panorama.
This paradigm proved much lighter and way more scalable than the previous, on-premise, software paradigm. However, it’s important to remark that while the cloud enabled many small businesses to run very heavy software operations by relying on massive cloud infrastructures.
These cloud infrastructures are managed centrally, by a few key players (like Amazon AWS, Microsoft Azure, IBM Cloud, Google Cloud, and a few others). Therefore, the whole cloud infrastructure, powering up an entrepreneurial ecosystem worth trillions of dollars is also centrally managed by a few key players. Thus, making the whole system fragile.
Every software company will be an AI copany
As new algorithms are integrated within software products, an important trend is sharing the software world. of the 2020-the the 2030s is the transformation of software into AI-based workflows, in what has been called Artificial Intelligence as a Service:
In this new model, cloud players (like Microsoft, Amazon, Google, and IBM) integrate AI features within their platforms, so that whoever is picking up their services will also be able to leverage on an AI platform. This, in turn, is leading to the transformation of the “as a service” industry toward a consumption-based one. Where customers, beyond a subscription plan, will have the option to pay as they go. Thus, paying the use of the infrastructure, based on the consumption of the platform.
Cloud As A Service business model case studies
As you can see from the visualizations above, cloud players are manufacturing models and algorithms, that becomes an integrated part of their cloud-based offering and platform. This is what attracts more AI developers and companies to become part of the ecosystem, thus, in turn, consuming more cloud infrastructure.
Beyond Cloud As A Service and into decentralized data storage
The main weakness of the current paradigm is the centralization of the whole cloud-based industry (which today represents pretty much most of the digital and tech landscape) in the hands of a few, centrally managed players.
Whether or not this will prove viable, it’s important to work toward cloud-based models which can have a higher degree of diffusion to prevent the collapse of the whole cloud ecosystem, as it’s placed in the hands of a few players.
- Shift to Cloud Infrastructure: In the early 2000s, there was a transition from on-premise software infrastructure to cloud-based solutions. The advent of the web enabled companies to build cloud infrastructure to host various servers, facilitating agility and scalability.
- Agile Transformation: Cloud-based software infrastructure allowed for continuous updates and quick iteration based on user feedback loops. This shift embraced agile methodologies, enabling companies to adapt and improve products rapidly.
- Continuous Innovation: Cloud adoption led to continuous innovation, where business transformation is driven by rapid feedback loops between a company’s operations and its customers. Products and services are designed around customers’ problems rather than just technical solutions.
- Customer-Centered Approach: The evolution continued from a software-centered approach to a customer-centered one. Continuous innovation, coupled with continuous intelligence, dynamic technological stack, and deployment, became critical for software operations.
- Cloud Computing Models: Cloud computing introduced three main business models: Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). These models allowed for offloading the complexity of on-premise hosting and provided more scalability and flexibility.
- Trillion-Dollar Cloud Industry: The shift to cloud infrastructure created a new trillion-dollar industry, with key players like Amazon AWS, Microsoft Azure, IBM Cloud, and Google Cloud managing massive cloud infrastructures.
- AI Integration: A trend emerged where software products incorporated AI algorithms, transforming software into AI-based workflows. This trend led to the rise of Artificial Intelligence as a Service (AlaaS), allowing organizations to integrate AI functionality without the expertise.
- Cloud Players and Consumption-Based Model: Cloud providers like Microsoft, Amazon, Google, and IBM integrated AI features into their platforms, leading to a transformation of the “as-a-service” industry toward a consumption-based model. Customers pay based on actual usage of the infrastructure.
- Cloud Service Case Studies:
- C3.ai: Offers cloud-based Enterprise AI SaaS with proprietary applications for digital transformation.
- Microsoft Azure: Part of the multi-billion dollar AI ecosystem, providing cloud infrastructure and AI services.
- Google Cloud: Offers models and algorithms integrated into its cloud-based offerings.
- Amazon AWS: Provides cloud services to enterprises and startups through a platform business model.
- IBM Cloud: Diverse technology company offering cloud services, including innovative products like Watson and Blockchain.
- Decentralized Data Storage: The centralization of the cloud industry in the hands of a few players is seen as a weakness. Blockchain-based business models, like Dfinity, aim to shift the paradigm from centralization to decentralization. Dfinity is working on a decentralized computer cloud for stable and cost-effective solutions.
Connected Business Model Types And Frameworks
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