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Bernard Marr

Bernard Marr is a world-renowned futurist, influencer and thought leader in the fields of business and technology, with a passion for using technology for the good of humanity. He is a best-selling author of 20 books, writes a regular column for Forbes and advises and coaches many of the world’s best-known organisations. He has over 2 million social media followers, 1 million newsletter subscribers and was ranked by LinkedIn as one of the top 5 business influencers in the world and the No 1 influencer in the UK.

Bernard’s latest book is ‘Business Trends in Practice: The 25+ Trends That Are Redefining Organisations’

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What Is Artificial Intelligence As A Service (AIaaS)?

14 October 2021

Up until recently, implementing artificial intelligence was cost-prohibitive for many companies – but now companies can use third-party artificial intelligence as a service (AIaaS) solutions to get the benefits of AI without the high price and large time investment of custom in-house development.

According to ResearchandMarkets.com, the global market for AIaaS solutions is expected to reach around $11.6 billion by 2024.

What Is Artificial Intelligence As A Service (AIaaS)? | Bernard Marr

What Is AIaaS?

Artificial intelligence as a service combines the power of computer systems that can perform human-like tasks (like problem-solving, pattern recognition, and learning) with the flexibility and affordability of third-party service solutions.

With AIaaS, AI technology can be accessible to any company. Even small organizations or departments with limited budgets can implement AI solutions to improve their products, services, and processes using low- or no-code software and APIs.

And the time it takes to implement AI is vastly compressed when companies use AIaaS solutions, often shortening implementation time to just a few days or weeks (vs. the months or years it can take with custom solutions).

Many companies also don’t need to hire in-house AI developers or experts, because they’re essentially outsourcing AI to a third party and buying that vendor’s expertise.

AIaaS is also customizable, scalable, and transparent – companies can create a system that meets their AI needs, scale up as needed, and pay only for what they need every month.

Examples of AIaaS

There are an increasing amount of ‘as a service’ AI solutions out there, and many more are in development for specific industries and use cases.

Using pre-trained models, companies can use out-of-the-box machine learning algorithms to find patterns in big data and make predictions. Businesses can customize these predictions to continually improve products, services, and processes. For example, Amazon makes the recommendation AI it is using on its own retail site available as a service to other retailers.

There are also many pre-trained AIs available for machine vision and natural language processing. That means, if you want to start analyzing large volumes of text, images, or video streams, you can simply start with these tools, which are delivered via the cloud. That means all you need to do if upload or stream your data to the cloud and switch on the AI to get started.

To enabler data integration with the cloud, AIaaS vendors offer Application Programming Interfaces (APIs) enable communication between two pieces of software. AIaaS allows users to upload and stream data, run cutting-edge models, and analyze data using a cloud platform.

Another example of AIaaS is chatbots, which are now offered as a simple plug-and-play tools. Using NLP and machine learning, chatbots use AI to simulate human conversation through online interfaces. Chatbots are trained to process user queries and respond with relevant responses, and they have been shown to improve customer satisfaction and save customer service agents time so they can focus on other tasks that require human brainpower. Chatbots also provide 24/7 support and handle multiple customer queries simultaneously at far lower costs.

Choosing the Right AIaaS

When deciding on an AI service, always start with your business goals. What are you trying to accomplish for your company, what data do you have access to, and what KPIs will you use to measure your progress?

Then consider your business size and your available budget. Assess the current tech capabilities of your team and the sources and amount of data you will be processing. Choose the right AI service to meet your needs right now, keeping in mind that you can pay only for the tools you need right now, and upgrade to a larger plan later as you scale.

Data Strategy Book | Bernard Marr

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