According to Technavio, the global artificial intelligence-as-a-service (AIaaS) market is expected to grow by $14.7 billion from 2021 to 2025. AI has proven itself to be vital to businesses for everything from customer experiences to automating redundant tasks. The use cases of AIaaS align closely with goals of digital transformation. Achieving growth for your organization requires not only the right talent, but future-focused technology as well.
In an era where data is accumulating faster than ever, implementing technology that can quickly process it to enable companies to act in a matter of minutes versus months will put them ahead of their competitors.
The Quickest, Cheapest Way to Implement AI: Third-Party Services
The quickest and most cost efficient way to deploy AIaaS is through third-party services. Building a team of AI experts internally is more expensive, and the recruiting process can be quite challenging. When finding the right experts, recruiters need to evaluate technical skills, creativity, business acumen and — because AI systems amplify any biases of its creators — an unwavering sense of ethical and moral responsibility.
Not only is the talent behind the technology expensive, but developing in-house AIaaS processes and frameworks is a long, complicated process and requires significant capital investment. Going through the process of implementing AI with current processes within a company results in significant cost and effort, often without a guaranteed return. Even when such talent is secured, teams are often bogged down by laborious tasks associated with data preparation, model selection, as well as operational tasks such as the deployment of models into a production environment.
To start, companies are well advised to seek out external experts who have experience working with a variety of clients and already possess the latest AI tools and unique intellectual assets. But, successful projects start with upfront acknowledgement that the organization will have to address more than just the technical aspects of AI — they will also be examining what AI really means to the organization and how the most value can be derived from it. There are many benefits to this approach, including a frictionless onboarding process, short time to prove value, and incremental return on investment through a focus on business outcomes, applied with experience and a knowledge of industry best practices. Without the ramp-up required in an otherwise new context, their services save time, effort, and money.
Continue reading: https://builtin.com/artificial-intelligence/AIaaS-ai-as-a-service-6-capabilities
In an era where data is accumulating faster than ever, implementing technology that can quickly process it to enable companies to act in a matter of minutes versus months will put them ahead of their competitors.
The Quickest, Cheapest Way to Implement AI: Third-Party Services
The quickest and most cost efficient way to deploy AIaaS is through third-party services. Building a team of AI experts internally is more expensive, and the recruiting process can be quite challenging. When finding the right experts, recruiters need to evaluate technical skills, creativity, business acumen and — because AI systems amplify any biases of its creators — an unwavering sense of ethical and moral responsibility.
Not only is the talent behind the technology expensive, but developing in-house AIaaS processes and frameworks is a long, complicated process and requires significant capital investment. Going through the process of implementing AI with current processes within a company results in significant cost and effort, often without a guaranteed return. Even when such talent is secured, teams are often bogged down by laborious tasks associated with data preparation, model selection, as well as operational tasks such as the deployment of models into a production environment.
To start, companies are well advised to seek out external experts who have experience working with a variety of clients and already possess the latest AI tools and unique intellectual assets. But, successful projects start with upfront acknowledgement that the organization will have to address more than just the technical aspects of AI — they will also be examining what AI really means to the organization and how the most value can be derived from it. There are many benefits to this approach, including a frictionless onboarding process, short time to prove value, and incremental return on investment through a focus on business outcomes, applied with experience and a knowledge of industry best practices. Without the ramp-up required in an otherwise new context, their services save time, effort, and money.
Continue reading: https://builtin.com/artificial-intelligence/AIaaS-ai-as-a-service-6-capabilities
