There are myriad articles on artificial intelligence and its application in business. As AI continues to grow and permeate seemingly 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.
I’m the founder and CEO of an AI-based customer relationship management platform. Through this experience, I’ve learned a few ways leaders can determine their 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 business-to-consumer or business-to-business company, you might 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, and it continues to reinforce the right steps to get to an endpoint.
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 that data can help get ahead of the competition. You can spot trends early and 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.
AI can also impact your CRM system and team productivity by helping identify leads, building effective nurture campaigns or personalizing the customer experience. (A number of companies, my own included, offer CRM and marketing AI solutions.)
Although there’s some concern about AI replacing jobs, I believe there’s an opportunity for AI to help, not hinder, the performance of marketers, salespeople and customer service representatives. However, taking steps to introduce it successfully is critical.
How can you 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. Remember: It’s not a black box.
When introducing any new technology, it’s always good to begin with a 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 reached the right conclusions. The first project is really about the journey more than the end goal.
Finally, consider any challenges that might come your way. For example, there are two sides to managing AI expectations. Some people on your team might think it’s awesome and will solve a lot of problems. Others might get scared, thinking it’s going to replace their jobs.
Try to address the expectations and concerns of 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?
You can start by using available cloud computing resources, which can be helpful for small to midsized companies because you don’t need to know a lot of underlying methodologies.
Alternatively, you might decide to set up AI technology on-premises. If you go this route, keep in mind that you’ll need some hefty horsepower and someone with a lot of knowledge of the underlying analytical algorithms and statistics to run through big datasets and get the highest ROI from AI.
Increasingly, I believe 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.