-1.6 C
New York
Thursday, February 2, 2023

AI as a Service (AIaaS): Unlocking greater productivity and profitability from AI implementations – TechRepublic

Register for your free TechRepublic membership or if you are already a member, sign in using your preferred method below.
We recently updated our Terms and Conditions for TechRepublic Premium. By clicking continue, you agree to these updated terms.
Invalid email/username and password combination supplied.
An email has been sent to you with instructions on how to reset your password.
By registering, you agree to the Terms of Use and acknowledge the data practices outlined in the Privacy Policy.
You will also receive a complimentary subscription to TechRepublic’s News and Special Offers newsletter and the Top Story of the Day newsletter. You may unsubscribe from these newsletters at any time.
Username must be unique. Password must be a minimum of 6 characters and have any 3 of the 4 items: a number (0 through 9), a special character (such as !, $, #, %), an uppercase character (A through Z) or a lowercase (a through z) character (no spaces).
AI as a Service (AIaaS): Unlocking greater productivity and profitability from AI implementations
Your email has been sent
Learn why enterprises should adopt AI-as-a-Service solutions.
For every application available on-premises, it’s almost certain it will also eventually be available as a cloud-based service, delivered on demand, by a cloud service provider. A somewhat recent addition to the growing field of cloud-based services is AI as a Service (AIaaS). With AIaaS, companies can enjoy the benefits of AI without having to make upfront investments in hardware and software. And in the case of AI, the savings can be significant.
After decades as fodder for science fiction movies, the use of artificial intelligence in business has exploded. Companies use AI for everything from customer service and marketing to process automation, security, and business and sales forecasting. In fact, a study by strategic advisors NewVantage found nine out of 10 top businesses have an ongoing investment in AI. A 2019 study by IT researcher Gartner found 37% of organizations in 2019 actually used AI in the workplace.
SEE: Artificial Intelligence Ethics Policy (TechRepublic Premium)
However, for small and medium companies, the same Gartner report, only 29% said they have adopted AI. This is at least somewhat influenced by the knowledge that specialized AI hardware is required and is often cost prohibitive. This is because a generic off-the-shelf server could be used, but because of the massive processing power required, it is not ideal and would bring productivity to a grinding halt.
And that’s just the investment for hardware. Then there’s the software, programming and training of models, which require specially trained data scientists, who command significant salaries. With AIaaS, companies of any size can enjoy the benefits of AI research, machine learning and analytics on demand and via the cloud.
Like every other technology, AI has been adopted slowly and incrementally. Businesses dip their toe in the water before diving in headfirst to try it out and see if it delivers on its promise. So, the initial rollout of early AI projects is generally measured and modest. Smaller companies are especially risk averse.
AIaaS is especially valuable for companies that don’t expect to do much AI work from the start. AI breaks down into a two-step process: Training and inference. The training part is the compute-intensive part, but the inference has much lower power requirements and can be handled with a much less powerful, non-specialized processor.
Now let’s say you only plan to deploy about two or three AI projects and you’ve chosen to invest in specialized hardware. Because you can’t repurpose an AI training server as a general-purpose database server, it will sit unused.
Conversely, if you’re doing multiple AI projects each year, then you may consider taking a hybrid approach and investing in an on-premises system. This is because cloud services employ a pay-as-you-go model for all the compute power needed to ingest and process data as well as all associated applications for storage, databases, networking and analytics. Ambitious AI projects generate massive amounts of data. Known as “data gravity” AIaaS projects can multiply the requirements for additional capacity and services, which drives up cost. This can easily blow up the cloud service provider (CSP) bill, and eventually it becomes more economically feasible to bring these workloads on premises.
There are a variety of programming languages for AI, from the common and ubiquitous (Python, C++) to the esoteric (R, Rust). This can prove challenging for a non-data scientist, who may not have any coding ability or understanding of data science beyond the basics. And all too often, non-data scientists are being tasked with owning AI projects because there are simply not enough skilled programmers and data scientists to meet the ever-growing demands for their skills.
Fortunately, CSPs that offer AIaaS services also offer no-code infrastructures for non-programmers. No-code tools and services are those that allow people to build applications without having to program them in the traditional way of writing, testing and debugging source code. Instead, the core functionality is created through visual tools much like a flowchart, where actions are taken based on preset conditions. If you ever use Microsoft Visio, you have an idea of how this works.
No-code is empowering business users to do the job of programmers, but the downside is that the applications tend to be simplistic. If you want fine-grained, precise control and action of complex AI models, you still need to program the application.
But no code is still very good for getting started writing simple AI apps, easing the burden on data scientists who have much more demanding tasks ahead of them and perhaps writing a simple chat bot.
Finally, the pros and cons of whether an AIaaS approach or an on-premises/hybrid approach to AI should be carefully considered and take into account costs, time and workforce specialization. For those just starting out or doing a limited number of AI projects each year, the benefits of AIaaS may far outweigh alternatives.
Phil Brotherton is the vice president of solutions and alliances at NetApp.
Learn the latest news and best practices about data science, big data analytics, and artificial intelligence.
AI as a Service (AIaaS): Unlocking greater productivity and profitability from AI implementations
Your email has been sent
Your message has been sent
TechRepublic Premium content helps you solve your toughest IT issues and jump-start your career or next project.
These 11 cloud-to-cloud solutions back up your organization’s data so you’ll be covered in the event of deletions, malware or outages. Compare the best online cloud backup services now.
You can use a mobile device to speak with another person directly through the Teams app. Lance Whitney shows you how to use this handy feature.
A phishing technique called Browser in the Browser (BITB) has emerged, and it’s already aiming at government entities, including Ukraine. Find out how to protect against this new threat.
With so many project management software options to choose from, it can seem daunting to find the right one for your projects or company. We’ve narrowed them down to these nine.
Start-ups, DARPA and Accenture Ventures announce research partnerships, new hardware and strategic investments.
IIoT software assists manufacturers and other industrial operations with configuring, managing and monitoring connected devices. A good IoT solution requires capabilities ranging from designing and delivering connected products to collecting and analyzing system data once in the field. Each IIoT use case has its own diverse set of requirements, but there are key capabilities and …
Recruiting an Operations Research Analyst with the right combination of technical expertise and experience will require a comprehensive screening process. This Hiring Kit provides an adjustable framework your business can use to find, recruit and ultimately hire the right person for the job.This hiring kit from TechRepublic Premium includes a job description, sample interview questions …
The digital transformation required by implementing the industrial Internet of Things (IIoT) is a radical change from business as usual. This quick glossary of 30 terms and concepts relating to IIoT will help you get a handle on what IIoT is and what it can do for your business.. From the glossary’s introduction: While the …
Procuring software packages for an organization is a complicated process that involves more than just technological knowledge. There are financial and support aspects to consider, proof of concepts to evaluate and vendor negotiations to handle. Navigating through the details of an RFP alone can be challenging, so use TechRepublic Premium’s Software Procurement Policy to establish …


Related Articles


Please enter your comment!
Please enter your name here

Latest Articles