Preparing Your Company for AI

Artificial Intelligence (AI) is big news, bringing the promise and peril of transformational change.

Companies need to look at the potential changes AI can bring to their industry and how they need to transform their businesses.

While technology like AI affects everyone, it is especially true for small and medium-sized enterprises (SMEs) as they have limited budgets to work with. In this blog, I will explore how analytics can be a stepping stone to preparing your company for using AI.

Both analytics and AI rely on a solid data foundation.

If you are still getting ready to get into AI, an analytics program is the way to build the data foundation that will help you well when you do.

Sections

Introduction to Artificial Intelligence (AI) in Small and Medium-Sized Enterprises (SMEs)
The Benefits of Analytics for SMEs
Using Analytics as a Stepping Stone to Artificial Intelligence
From Business Insights to AI Strategy

The Benefits of Analytics for SMEs

Analytics involves examining data to uncover insights, patterns, and trends.

It has long been invaluable for large corporations and is equally essential for small and medium-sized businesses.

Here are some key benefits that analytics can bring to small and medium-sized businesses:

By using analytics, you can gain valuable information about customer behaviour, market trends, and business performance. You can use it to make intelligent decisions about developing new products and creating effective marketing strategies.
Analytics can help your business find inefficiency in its operations and processes. You can use it to guide the changes you need to make and save money.
Your company can benefit by making decisions grounded in data. You can gain an advantage in staying ahead and adjusting to market changes more effectively.

Analytics as a Stepping Stone to Artificial Intelligence

Analytics is a good starting point to prepare for AI because it requires the same solid data practices to be in place.

Many of the steps to prepare data for an analytical model are the same as those for an artificial intelligence model.

By adopting good data management and integration processes, your company lays a sound foundation for AI technology in the future.

Both analytics and AI are complex and expensive programs to adopt.

Most companies can’t find ways to go all-in, everywhere, all at once. So, you need to focus your program on problems important to your business where you have enough relevant data.

This focus choice is much the same for both analytics and AI.

Your Organization’s Data Quality and Structure

Before diving into AI technology, companies can focus on analytics to ensure the quality and structure of their data.

Analytics projects require organizations to cleanse, organize, and structure their data.This is a necessary first step for any effective AI system.

For many SMEs, this may involve adopting basic data management practices, which are crucial for advanced data processing in AI.

Business Process Optimization and Automation

Analytics can make business processes more efficient.

By using analytics tools, businesses can find and fix problems in their operations and improve processes to work better.

Over time, you can find those areas where you can automate routine tasks and implement AI to save time and resources for your businesses.

Your Organization’s Skill Development and Data Literacy

Investing in analytics helps your employees to become more data literate.

Through constant exposure to using data to help make everyday decisions, analytics grow awareness of how data can improve your business processes.

Training employees in data analysis tools and techniques is also necessary for preparing the company for AI technologies.

To learn more about how to build a data analytics team, click here.

Building Analytical Tools and Infrastructure

The tools and practices you use for data collection, integration, and preparation for your analytics project are the same types you will use for AI.

When developing data sets for analytics, you also produce them for future AI projects.

By considering where your organisation can use AI, you can create a well-prepared dataset today for your AI future. Thus, you prepare your company for AI.

From Business Insights to Your AI Strategy

Companies can figure out what insights they can get now from analytics, allowing you to understand your operations better and determine which parts of your business would benefit most from AI technology.

For example, you can identify repetitive or time-consuming tasks to automate using AI.

Your decisions can become more fact-based and data-driven. Over time, analytics help build trust in the data and tools used for AI. This change is vital for getting ready for the AI future.

The journey to AI should be a step-by-step process. The first important step is analytics.

This approach helps build a solid foundation, getting the most out of the benefits and minimizing the risks of preparing to adopt AI.

Analytics is an investment that gives you the tools, skills, and insights you need to transition to AI successfully.

When your business goes on this journey, you create a robust data framework, promote a culture that values data, and slowly incorporate AI into your business processes to ensure a seamless and effective digital transformation.