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A Small Business’ Guide to Building AI Infrastructure

Posted by Devika Hastak

April 28, 2024

Prepare your business for the AI revolution with this guide to building effective and scalable AI infrastructure.

The artificial intelligence (AI) revolution is well and truly underway, and individuals and businesses must do their part to keep up. Many companies already utilize AI in finance, customer service, recruitment, supply chain operations, etc. With a growing list of what AI can be used for, it’s vital that businesses, especially small businesses, have a solid foundation in place to efficiently and sustainably incorporate AI into their day-to-day operations. This solid foundation, AI infrastructure, is not just a necessity, but a powerful tool that can empower small business owners to navigate the AI landscape with confidence and capability.

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The AI infrastructure market is set to grow from $23.5 billion in 2021 to $309.4 billion in 2031. This is no wonder since reliable and effective AI infrastructure is the key to the success of all your AI-powered tasks and applications. Suppose you are the key decision-maker at a small business or firm. In that case, you know all too well that embracing innovation is crucial to powering through tough times of change. Let’s dive deeper into how AI infrastructure can help your small business and the steps you need to take to be AI-ready.

What is AI Infrastructure?

Just as we have IT infrastructure such as servers, CPUs, networks, computers, and data centers to operate and manage a company’s IT services and environments, we now also have AI infrastructure. 

AI infrastructure, also known as an AI technology stack, refers to the hardware and software needed to create, train, and utilize AI-powered solutions and applications in a reliable and scalable way. It is made up of the following key components: 

  • A powerful graphic processing unit (GPU) or tensor processing unit (TPU)
  • Reliable data storage and management
  • Data processing frameworks
  • Machine learning frameworks and libraries
  • Machine learning operations

The components of AI infrastructure work together to ensure that their machine learning capabilities can process large amounts of data efficiently to carry out AI-powered tasks and applications. 

Benefits of Solid AI Infrastructure

AI already has far-reaching influences on every aspect of our society and is a regular feature in almost every discussion. It is proving especially irreplaceable in the ever-changing business landscape, where growth and optimization are the main priorities, even during these turbulent times. For example, several companies are already leveraging AI in finance to amplify predictive analytics, slash operational costs, boost revenue growth, bolster cybersecurity, and enhance the customer experience. We will continue to find more valuable applications for AI, and there are countless benefits to ensuring that your business has solid AI infrastructure to prepare for this. 

The proper AI infrastructure will make your business more scalable, flexible, and resilient in the face of change and uncertainty. It will help you adapt to today’s evolving business landscape, where technological advancement, economic uncertainty, and socio-cultural influences are front and center. This also supports the innovation-valuation relationship, which states that your business’ value is directly linked to your ability to innovate, adapt, and thrive in an ever-changing world. By investing in AI infrastructure, you are not just preparing for the future, but also paving the way for a more optimistic and hopeful future for your business.

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A solid operating foundation will help you benefit most from your AI-powered tasks. We already know that AI can optimize business processes such as decision-making, SaaS financial reporting, data aggregation, and customer relationship management. With AI infrastructure that supports these processes as your business grows, you can ensure your operations are sustainable, productive, and impactful.

Although your initial investment may seem high, building reliable AI infrastructure early on is more cost-effective than conducting AI-powered tasks on regular IT infrastructure. In the long run, you may need to consider the costs of upgrading your existing infrastructure to keep up with AI-related demands and remain compliant with changing regulations. However, starting with the right resources and capabilities will help you make the most of your AI projects at lower financial and legal costs.

How to Build Your AI Infrastructure

Now that we’ve told you how AI infrastructure can support your small business, let’s explore how you can build the boat that will help you navigate the choppy seas of the AI world.

1. Develop Your AI-Ready Strategy

Before you decide what components will make up your AI infrastructure, you must first clarify the goals you hope to achieve. Highlight the processes you plan to power with AI: SaaS financial reporting, cybersecurity, data aggregation and analysis, operations, or customer service. This will encourage you to take a forward-thinking approach to your AI-powered tasks and help you build a scalable infrastructure to keep up with growing computational demands and AI workloads.

Budgeting is also a crucial part of your strategy. Examine the costs associated with sourcing hardware and software and the training and consulting required to get set up. This will help you make informed decisions when choosing the components for your AI infrastructure.

2. Assess and Update Your Existing Infrastructure

Once you have built your strategy and identified a budget, the next step is to work with SaaS asset management specialists to assess your existing infrastructure. This involves a thorough evaluation of your hardware, software, and storage capabilities to determine whether they can meet the needs of AI-powered tasks. Based on this assessment, you can then proceed to upgrade or procure each component per your strategy, budget, and future goals. For example, cloud services offer a low investment solution so your small business can build scalable AI infrastructure easily adapted to future growth and demand. 

Since AI and machine learning work best with rich, high-quality data, this stage also includes assessing and centralizing your existing data. Ensure your data is relevant, accurate, and addresses the problems you hope to solve. 

3. Foster an AI-Ready Culture

Ensuring your employees are part of this journey is crucial to building your AI infrastructure. Establishing new infrastructure and processes, especially for AI, is a significant change that will likely be met with apprehension and resistance. As with any change management exercise, make your employees feel supported and explain how AI will benefit them and their jobs. Express your gratitude for the value they bring, as well as their expertise and human skills. Lastly, upskill your current employees and hire those with the skills to work with AI infrastructure. 

Final Thoughts

Artificial intelligence is here to stay and will continue to impact how we work significantly. As we continue to uncover more AI capabilities, we must prepare ourselves to adapt to this new information and use it to our advantage. Reliable AI infrastructure can enhance key business processes such as SaaS asset management, financial reporting, customer relationship management, and sales. This invaluable support with day-to-day operations will help small businesses remain resilient in today’s dynamic landscape.

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Want to know more about getting your business AI-ready? Escalon has helped over 5,000 companies across a range of industries improve their compliance regarding internal controls and streamline processes. Talk to an expert today.


Devika Hastak
Devika Hastak

Devika Hastak is a dynamic content writer who is passionate about using the power of the written word to promote knowledge sharing and drive business success. She is adept at crafting compelling content tailored to client objectives and successfully executing SEO strategies that significantly impact brand awareness and lead generation. When she’s not wielding her digital pen, you can find her conducting culinary experiments in the kitchen or enjoying a good laugh with her family and friends.

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