Tips on introducing artificial intelligence in your business

Business & tech

by   Anthony Smith

This article was originally published on Forbes.

There are myriad of articles on artificial intelligence (AI) and its application in business. As AI continues to grow and permeate every aspect of business, it’s important to cut through the noise and focus on where AI fits in your organization and how to best implement it. Here are a few ideas to help you determine your own approach to AI.

A brief overview of AI application in B2B

Broadly speaking, AI is a branch of computer science concerned with replicating human intelligence in machines. Depending on whether you run a B2C or B2B company, you may find some types of AI more relevant to your business than others. In B2B, AI is all about data and analysis to make better-informed decisions. For example, if you have enough sales and customer data, you can use predictive analytics to figure out your ideal customer profile and/or potential customer base and adjust your marketing strategy and campaigns accordingly.

In more technical terms, AI applications in B2B can be broken into three types of machine learning: supervised, unsupervised, and reinforcement.

In the case of supervised learning, you or someone with business intelligence skills feeds the data to the learning algorithm (a statistics algorithm) and sets a goal (what you want to get to or what you’re looking for). The machine then tries to match that goal.

In unsupervised learning, the algorithm looks at the data and searches for patterns. As the name suggests, there are no instructions given prior to the analysis. For example, it can look at your customer data and decide that you have a cluster of customers in the manufacturing industry that looks really promising.

Finally, in reinforcement learning, which is more advanced, the algorithm looks at the data and comes up with a set of conclusions. You don’t provide a predefined dataset or any guidance, it’s more of a trial-and-error method. You look at the results and tell it whether the conclusions are correct or not and it continues to reinforce the right steps to get to an end point.

How can AI benefit your business?

For businesses that collect a lot of customer data at every point, being able to use AI to derive meaning from data can really help to get ahead of competition. You can spot trends really early, identify areas where you’re losing revenue or where you could potentially gain revenue. You can then make data-driven decisions and quickly adapt to changes. Compare this to waiting until the end of the month, when someone is going to pile all the sales numbers by hand, produce a report using one of your analytics tools or a dashboard to show you what you already knew was happening. With AI’s real-time analysis you can run a truly agile business and stay ahead.

AI can also make a big difference in your customer relationships management and team productivity. Whether it’s helping to identify the hottest leads, building effective nurture campaigns, or personalizing customer experience–AI can help marketers and salespeople to prioritize campaigns and focus their time and resources on high ROI activities.

There’s some concern about AI replacing jobs. This is mainly in the robotics branch of AI and it concerns manual work, like packing and putting things in boxes. But for knowledge workers such as marketers, sales and customer service reps, there’s a big opportunity for AI to help, not hinder their performance.

How to introduce AI in your business

Make sure you are clear on where in the business you want to use AI and what you hope it will solve for you. Keep in mind that you need to have enough data to make your AI investment worth it. Once you’ve done that, train your employees on how it’ll work. It’s not a black box!

When introducing any new technology, it’s always good to begin with a really small project and work from there. Start with a hypothesis and a goal and at the end analyze how well you did and if you had reached the right conclusions. But the first project is really about the journey more than the end goal.

Finally, there are two sides to managing AI expectations. Some people on your team may think it’s really awesome and is going to solve a lot of problems. Others may get really scared, thinking it’s going to replace their jobs. Try to address the expectations and concerns on both extremes. AI is not going to solve everything and, in a B2B company, it most likely won’t replace jobs. You have to tamp down both the enthusiasm and worries surrounding AI to ensure buy-in before you make it part of your business.

What technology do you need to implement AI for the first time?

Start by using available cloud computing resources, which are great for small to mid-sized companies. Microsoft’s Azure and Amazon’s AWS cloud platforms recently introduced affordable tools that can help you get up and running pretty quickly. You don’t need to know a lot of underlying methodologies. Whereas, if you decide to set up AI technology on premise, you’ll need some hefty horsepower and someone with a lot more knowledge of the underlying analytical algorithms and statistics to run through big datasets and get the highest ROI from AI.

Increasingly, it’s not a question of if, but when you should implement AI in your business. The sooner you figure out your AI approach, the sooner you’ll start reaping its benefits.

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