4 Things Every Company Needs To Do To Prepare For AI

Just a few short years ago, artificial intelligence was seen as something of a fantasy more suited to sci-fi novels than everyday life. Looking around at the digital landscape today and AI has infiltrated many areas of our lives. Anyone who talks to Siri, asks a question of a chatbot or views adverts on Amazon has been touched by AI. But for all the progress of artificial intelligence, we’ve only seen a fraction of the opportunities it will provide.

A 2017 survey by Forbes found that CEOs felt AI/Machine Learning was more important than virtual reality, advanced robotics and nanotechnology. If you’re a business manager, you can’t afford to ignore all the change that AI is set to bring about.

Artificial intelligence will soon have quite a few practical applications for business. These practical AI applications can manifest in all sorts of ways, depending on your organizational needs and the business intelligence insights derived from the data you collect. But it won’t be something you can decide on one day and implement the next. Your business must make specific preparations now to ensure you aren’t left behind

In this article, we highlight 4 things that your business needs to be doing to ensure you’re ready to take advantage of AI, even if the AI-based applications you end up using are still a couple of years off.

Learn what AI can do and what you want it to do

The first step is to take the time to become familiar with what modern AI can do. You, as a business owner, cannot afford not to understand the capabilities of AI. To do so could end up costing you a lot of great opportunities. Take advantage of the wealth of online information and resources available to familiarize yourself with the basic concepts of AI. Online courses are also available through institutions as prestigious as Stanford University and the Columbia Business School.

Once you’ve brushed up on what AI can do, you need to determine what you need AI to do. Start by thinking about how you can add AI capabilities to your existing products and services, with a particular focus on your current processes. Hold discussion groups within the company to find out which processes you can save time and money on by automating. Many of these processes may be time-consuming and laborious so it would be worth automating these tasks, allowing your employees to focus on higher-value responsibilities.

Sort out your data

The output that AI can provide for your company is limited to the quality and quantity of data you put into it. It simply isn’t possible to progress with AI until your data issues are fixed, and all companies have data issues that need fixing.

To give you a better understanding of how suitable your data is, ask yourself a few questions.

Is your data contextually relevant?

Most AI systems are good at determining correlations, but they don’t understand the surrounding data. To avoid any misinterpretation, you should give the AI both the data and the context. This will help it understand the facts surrounding the data and ensure the solutions it presents are relevant.

Is it structured?

However your company implements AI, you’ll need data that is consistently formatted and labeled. Start putting the right structure in place now so don’t have a huge mess to clean up later. Data management tools are great for connecting, collecting and unifying business data, leaving you with clean, easy to digest data that your AI can use. As Garth Laird, CEO of ZAP says,

“It is vital that corporations first invest in solutions that align their data to achieve a trusted data store.”

The more clean, classified and meaningful data you can gather now, the more you’ll get out of AI in the future

Is it enough?

Making predictions based on a small set of data will likely yield poor results. If you’re not collecting enough data, even the best AI technology won’t be of much use to use to you.

Plug your skills gaps

Using AI doesn’t have to require a major investment in systems and people. Most businesses are likely to have a good enough data infrastructure and people scattered across the organization who have the skills to leverage it. But it’s important that you encourage learning wherever possible through further training and education.

As well as increasing the chances of successful adoption of the new technology, investing in training helps your company stay competitive in the short-term and cultivate talented employees to become forward-thinking leaders in the future.

There’s a large number of online courses you could subsidize, as well as university classes or advanced degree programs. There are also on-site training sessions and workshops available. Make sure that all training and learning sessions are tailored to the needs of your company. You’ll need to consider your industry, company size, and data needs. Consulting with an educational expert about choosing a course may also prove beneficial.

Start small

When your employees are ready and your infrastructure is in place, it’s time to start building and integrating. If your goal is to build an all-knowing AI system that is able to solve your every business problem, you’re almost certainly going to fail. So it’s important to be realistic. Start small with AI applications with specific, discrete functions and keep in mind what your company is capable of doing at that time. Targeting low hanging fruit is a good place to start. For example, look for ways to automate laborious processes in order to free up time for your employees. You can refer back to the research you did at the start of this process.

Once you’ve got the hang of this, look for problems you can scale. Build on the data science techniques that others have used and see how you can modify these to suit your own needs. As you tackle these problems, you’ll be building the institutional knowledge required to solve similar issues in the future.

IBM, in conjunction with the TSA, built on simple object recognition technology with the aim of applying it to object detection for baggage screening. This new ‘visual’ recognition could then be taken further to answer more sophisticated questions about behaviour. For example, “What does preparation for a terrorist attack look like?” All that started from an AI that could tell the difference between an apple and orange. Automation will change your company, and by utilizing these four steps you may be surprised at how quickly you see results. More importantly, you’ll be creating an opportunity to grow your company into a stronger, more productive organization, both now and well into the future. Integrating AI isn’t an easy thing to do, but it’s also not something that any innovative organization can ignore for long.

 

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