Ever marveled at the fact that a staggering 77 percent of our daily devices seamlessly incorporate the marvels of AI technology? If that statistic doesn’t underscore the monumental impact of AI on our lives, then what will? Brace yourself for the next frontier in technological innovation as we step into the realm of artificial intelligence as a service (AIaaS). It’s not just a service; it’s a gateway to a future where the limitless potential of artificial intelligence is harnessed to reshape the way we interact, solve problems, and propel us into an era of unprecedented possibilities.
Let’s dig in to learn more about this technology.
An Introduction to Artificial Intelligence as a Service
The meaning of AI-as-a-service is pretty much described by itself. “Artificial intelligence as a service,” is a service that is outsourced by other companies or individuals to implement AI solutions without having to build those AI solutions. Businesses that do not wish to invest in developing their AI-based solutions can opt for AIaaS via a third-party AI service provider.
Artificial Intelligence, Machine Learning, Deep Learning, etc. are an inevitable part of digital transformation. Integrating AI-powered solutions to enhance your business can give you a competitive edge over others, but how does AIaaS come into the picture here?
It is simple, to embrace a digital change you need AI solutions to perform human-like tasks and solve problems. However, you may not have the required capital to invest in building your AI-powered solution. This is where AIaaS comes into the picture, with AIaaS you outsource a third-party AI-based solution provider and avail ready-to-use AI services.
Some of the prominent key players offering AIaaS services are MonkeyLearn, IBM Watson, Microsoft Azure, Google Cloud ML, and much more.
Benefits of Artificial Intelligence as a Service
Many parallel computers and quick GPUs are essential for effective AI and ML. Prior to AIaaS, businesses made unwise initial and continuing maintenance decisions. Moreover, AIaaS enables companies to use machine learning at a much reduced cost. This means you can continue to work on your main line of business. Additionally, it does away with the necessity for investment and training in areas that only partially aid in decision-making.
● Low Cost:
One of the major benefits of AIaaS is reduced costs. With artificial intelligence as a service, you only have to pay for the services used which means you do not have to pay for unnecessary development costs.
● Easy to Use:
By opting for AIaaS businesses need not hire experts or in-house software to build and implement AI solutions. With a third-party AI service provider, it becomes easier to access ready-to-use AI solutions and implement them in any business process.
These workings may include the algorithms that are applied, whether they are updated, and so on. This may also lead to misunderstandings or misperceptions about the stability of your data or output.
● Scalability:
With artificial intelligence as a service, you can begin with smaller projects. It aids in determining whether it would be a suitable fit for you. Also, it helps you comprehend your unique needs. As you gain expertise with your own data and project demands change, you may also fine-tune your solution and scale up or down.
● Enhanced productivity:
AI solutions can ease the workload of customer care representatives, which can increase output and improve customer satisfaction.
● Medical developments:
AI can provide quicker and more accurate diagnoses and enhance medical research, both of which can contribute to improving healthcare outcomes.
Machine learning platforms provided by AIaaS providers can make it simpler for companies to develop and use machine learning models without requiring technical knowledge or expertise.
Drawbacks of Artificial Intelligence as a Service
● Additional Costs
Though AI-as-a-service is a cost-efficient solution for a business in the long run you may have to incur extra costs to continue services from your AI service provider. As existing technologies keep updating and new technologies keep coming in to access them extra costs have to be incurred. On the flip side, even though you spend more on new AI advancements, it enhances your business’s profitability.
● Security concerns
When you avail of artificial intelligence as a service, you have to share valuable and confidential company data with your AIaaS provider. This can raise an alarm for security concerns and you have to ensure you have secure data storage and data access mediums.
● High Cost on Long Run
Any “as-a-service” solution, including AIaaS, has the potential to accrue fees. You might be seeking more complex options as you learn more about AI and machine learning. However, these services may cost more and necessitate hiring and training people with more specialized knowledge. Yet, like with anything, the price may also be a wise investment for your company.
● Less Transparency
With Artificial Intelligence as a Service, you only pay for the service—not the access. Some compare a “black box” to service offerings, particularly those in machine learning (ML). Both the input and the output are known to you. You are not aware of the inner workings, including the algorithms that are utilized, whether or not they are updated, and which editions are applicable to which data. This could also lead to misunderstandings or a lack of clarity regarding the reliability of your information or output.
● Increased Reliance
As a result of your collaboration with one or more third-party companies for AI as a service, you rely on them to provide the preferred data. This isn’t a problem by itself, but if any problems occur, it can result in lag or other problems which could result in increased reliance on other third parties eventually slowing down the process.
Leading AI as a Services Companies
Leading the charge in artificial intelligence as a service, here are key players harnessing the power of artificial intelligence to reshape the digital landscape:
Microsoft Azure:
- Cognitive Services: Empowers applications with APIs for content moderation, anomaly detection, and more.
- Cognitive Search: Integrates AI-powered cloud search seamlessly into mobile and web applications.
- Azure Machine Learning (AML): Allows the building, training, and deployment of ML models from cloud to edge, supporting both service models and custom AI development.
- Bot Services: Offers a serverless chatbot service designed to scale on demand.
Amazon Web Services (AWS):
- Sagemaker: A fully-managed service facilitating machine learning in the cloud, enabling model building, training, and deployment to a production-ready environment.
- Lex: Provides features for building chatbots and virtual agents, integrating seamlessly with new and existing applications, boasting natural language capabilities like speech recognition and NLP.
- Polly: Equipped with features for creating speech-enabled applications and products, converting text into spoken audio.
- Rekognition: Offers computer vision capabilities with pre-trained algorithms and the flexibility to use custom-trained algorithms on personalized datasets.
Google Cloud:
- AI Platform: Empowers the building, deployment, and management of ML models at scale.
- AI Hub: A hosted repository providing plug-and-play AI components, including out-of-the-box algorithms and end-to-end AI pipelines.
- Conversational AI services: Encompasses various services such as Text-to-Speech, Speech-to-Text, virtual agents, and the Dialogflow platform, facilitating the creation of conversational actions across applications and devices.
Future of AIaaS
In the rapidly expanding artificial intelligence as a service market, businesses are leveraging technologies like machine learning, deep learning, and natural language processing. With an increasing number of businesses adopting tech-driven solutions, the integration of AI into their operations is poised to become a standard practice. As the global business landscape progresses technologically, the adoption and implementation of artificial intelligence solutions will witness a more active embrace. AIaaS emerges as the enabling factor, granting businesses flexible access to a suite of AI tools.
