Artificial Intelligence (AI) is central to the Fourth Industrial Revolution. Companies rely on AI, data analytics, and Robotic Process Automation to fuel every business process–from content creation to customer service. AI makes everything simpler, quicker, and more manageable.  However, implementing AI across operations is complex and expensive. This is where AI as a Service (AIaaS) comes into play, offering a convenient solution that relieves businesses from the burden of in-house development, bringing a sense of relief and reducing stress. 

How does it compare to traditional outsourcing? Let’s explore when choosing AIaaS might be the better option. But first, let’s understand what AIaaS is.

What is AI as a Service (AIaaS)?

AIaaS is a cloud-based service that provides AI tools and frameworks. Businesses can use these services without investing in the infrastructure or expertise to build AI solutions from scratch. Major cloud providers like Amazon Web Services (AWS), Google Cloud, and Microsoft Azure offer AIaaS. These platforms provide various AI services, including machine learning models, natural language processing, and computer vision.

The four most common kinds of AI as a service are chatbots, machine learning, Application Programming Interfaces (APIs), and data labeling. Almost all companies today need these AIaaS elements.

How is AI as a Service (AIaaS) different from traditional outsourcing?

Traditional outsourcing is simply hiring third-party vendors to develop and manage AI solutions. This has been common in the tech industry for years. Companies outsource tasks to external teams that specialize in AI development. While this method is excellent and very effective, it has a few drawbacks.

Let’s compare traditional outsourcing with AIaaS.

1. Savings

In traditional outsourcing, companies must pay to develop, maintain, and manage AI solutions. These costs are very high, especially if the project is complex. Additionally, there may be hidden costs, such as fees for ongoing support or updates. AIaaS typically operates on a pay-as-you-go model. Businesses only pay for the services they use. This makes it more affordable, especially for small and medium-sized enterprises (SMEs). There are no significant upfront investments, and costs can be scaled according to usage. 

2. Speed of Implementation

Finding the right vendor, negotiating contracts, and developing your desired AI solution can take months. Most businesses must act quickly. On the other hand, cloud-based AI services are ready to use. They can be integrated into existing systems rapidly, emphasizing the urgency and importance of quick solutions in industries where time-to-market is a competitive factor.

3. Scalability

As a business grows, its AI solutions need to evolve. Traditional outsourcing can be rigid in this regard. Scaling up an outsourced AI solution means renegotiating contracts or starting from scratch. Since AIaaS is cloud-based, businesses can quickly scale up or down. Whether it’s increasing processing power, adding more users, or expanding capabilities, AIaaS can adapt rapidly. Businesses with fluctuating demands or on a growth trajectory can use this.

4. Customization

In traditional outsourcing, the vendor typically handles all aspects of the project, from design to implementation. This arrangement is quick and convenient but limits a company’s control over its project. AIaaS provides more control and customization. Businesses can choose the specific AI tools and services they need and configure these services to suit themselves.

5. Data Security and Privacy

Before outsourcing AI development, companies must trust that the vendor will handle their data securely. However, AIaaS providers invest heavily in security measures. Reputable cloud providers offer encryption, access controls, and regular audits. Businesses can also manage their data within their environment before using AIaaS tools, adding an extra layer of security.

6. Updated Technology and Skills

Vendors don’t always provide the most relevant solutions, particularly if they have existing contracts to fulfill, but reputed AIaaS providers update their services to include the latest AI advancements. Businesses using AIaaS can access state-of-the-art technology without new infrastructure or retraining staff. This internal development is an added benefit that traditional outsourcing does not provide.

7. Talent and Expertise

Outsourcing relies on external teams that may not fully understand the business’s goals or culture.  AIaaS reduces the need for in-house expertise. While some knowledge is required to integrate and manage AIaaS tools, it is far less than what is needed for full-scale AI development.

8. Flexibility in Use Cases

Traditional outsourcing is often project-specific. Vendors are hired to complete a particular task, and this approach usually limits the flexibility of AI applications within the business. AIaaS is much more flexible, providing the tools to experiment with and making the audience feel empowered and in control of their AI solutions. 

9. Integration with Existing Systems

Compatibility issues, data migration, and technical debt complicate the integration of AI into existing systems. AIaaS is designed for easy integration. Most cloud-based AI services offer APIs and other tools to integrate existing software and platforms seamlessly. This reduces the technical challenges and ensures the AI solution works smoothly with other business systems.

10. Support and Maintenance

In traditional outsourcing, the vendor usually provides ongoing support. However, the quality and availability of this support can vary (remember that the vendor is located in a different time zone and has multiple clients to manage). AIaaS experts provide 24/7 support. Additionally, since AIaaS is cloud-based, the provider handles maintenance and updates, reducing the business’s burden.

11. Global Accessibility

Accessibility is a concern for businesses with global operations, and AIaaS is accessible from anywhere with an internet connection. Global teams can collaborate and use AI tools regardless of their location. The global accessibility of AIaaS is particularly beneficial for businesses looking to expand or operate in multiple markets. 

12. Environmental Impact

Anything cloud-based is an environmentally friendly choice. Outsourcing might involve limited travel, the need for physical infrastructure, and energy consumption, all of which have environmental impacts. AIaaS reduces the need for this physical infrastructure and minimizes energy consumption. Many AIaaS providers are also committed to using renewable energy sources, making it a greener choice for businesses.

Wrapping Up: When to Choose AIaaS Over Traditional Outsourcing

This article isn’t meant to present AIaaS as a clear winner. 

There will always be situations in which traditional outsourcing will be the best solution, especially for big industries. AI as a Service is also dynamic, and we still aren’t aware of all its advantages over traditional outsourcing. A few of them are cost-effectiveness, speed, scalability, flexibility, and increased access to cutting-edge AI technologies without investing in infrastructure or expertise. While conventional outsourcing may still be appropriate for highly specialized or custom projects, AIaaS is often the better choice for businesses looking for a quick, flexible, and cost-effective way to integrate AI into their operations.