Business Innovation: How Artificial Intelligence Is …

Today, business innovation andartificial intelligence(AI) seem to go hand-in-hand to improve many areas of a business. In customer service, for example, chatbots are now interacting with online customers to improve customer service. In HR, artificial intelligence is being used to speed up the recruitment process, and inmarketing, AI-powered tools are increasingly used to personalize the customer experience.

A 2018studyby McKinsey Global Institute predicts that by 2030, 70 percent of companies might have adopted at least one type of AI technology. (The study was based on two independent surveys of 1,600 business executives across industries worldwide and 3,000 corporations in 14 sectors in 10 countries.)

Despite common fears surrounding the impact of artificial intelligence on employment, AI is here to stay. AI and machine learning (a subset of AI) are at the forefront of business innovation.

Let's take marketing as an example: To get some insights into how artificial intelligence can help you take your marketing strategy to the next level, I spoke toNeal Schaffer, a leading social media marketing strategist.

(Schaffer is the author ofthree bookson social media, with his fourth book,The Age of Influence, set to be published in 2020.)

According to Schaffer, artificial intelligence isn't changing the approach to marketingyet.

"I think we're seeing, in the different tools that exist for marketers, that slowly these tools are beginning to leverage AI and machine learning to give [them] better insight into their marketing activities."

In this day and age, Schaffer adds, everyone is awash in data. Using these tools can help marketers analyze the data swirling all around them.

"I think AI is actually going to save marketers a lot of time and also make them look smarter," he says.

AI has found its way to influencer marketing, as well.

"How do you determine who is an influencer when there are so many fake followers and so much fake engagement that exists on the Internet?" Schaffer says. "We can teach the AI engine how to spot people when they have an unnatural spike in follower increase in a limited amount of time, which could be a sign of fake followers.

"If they average 1 percent engagement," he continues, "but all of a sudden have 5 percent engagement when they publish a sponsored post using #ad, we might suspect that they participated in an Instagram pod to boost engagement levels. These are some of the ways AI can automatically flag accounts that require further investigation when their influence should be questioned. We can teach artificial intelligence to look for these trends that might indicate that these people are faketheir influence is not authentic."

Artificial intelligence isn't just for huge companiessmall or medium-size business can also harness the power of AI to maximize the ROI of their marketing efforts. Achatbotthat interacts directly with users on your website is a great entry point for "companies to first really experience what AI can do for their business," Schaffer says.

Schaffer uses chatbot technology customized for his own use-case scenario on his website. Chatbots can increase engagement with a website visitor, Schaffer explains.

"People come to your website and not everyone engages. Not everyone goes to a contact form or buys a product," he says. "But a lot of people are very comfortable engaging with these bots these days. So I'm getting more people engaging with my bot and having a conversation with me there versus going all the way to my contact form and filling out that form."

There are a number of tools available right now that leverage AI and are accessible to smaller businesses. For example, there are tools that use AI and natural language processing to understand a company's keywords and brand messaging, and basically repurpose a company's content.

Adam Geitgey, software engineer and consultant

If you have a blog post, you can repurpose your content into a number of tweets or LinkedIn or Facebook posts, Schaffer says. This is intelligently using AI to provide, "bite-sized content that you can then use for your social media messaging or even your newsletter messaging," he explains. "So this is another very, very easy way to experience AI."

Machine learning is a key part of business innovation today, according to software engineer and machine-learning expertAdam Geitgey. Geitgey teaches software engineers how to build machine learning systems and is the author ofMachine Learning Is Fun.

"Machine learning," says Geitgey, "is very effective when you have a repetitive process that you want to automate, but the process is a little too complicated to automate with traditional programming."

Geitgey explained this with an example:

"Imagine that you are building an online business where users can upload their photos to your website or app. With user-generated content, you might want to make sure that your users aren't uploading illegal or inappropriate pictures. It would be too time-consuming to look at every photo yourself to pick out the bad apples, but machine learning is great at this. You can use a machine learning system to instantly scan each image and flag the ones that are most likely breaking the rules. That way, you only need to double-check a few flagged images instead of checking them all."

"Any place like this in your business," continues Geitgey, "where you need to sort throughlots of dataand make a quick decision about each piece of data is a place where machine learning might save you lots of time and money. So look for these kinds of opportunities."

Machine learning can also be used for transcribing audio to text, recognizing objects in photographs or videos or automatically understanding if a user is writing something negative or positive in a comment.

Embarking on an AI journey naturally raises concerns for any business. What are some mistakes that a company can avoid?

"The most common mistake I see," Geitgey says, "is when businesses feel pressure to 'get some AI' before they understand what it can actually do. It's the old problem of a solution looking for a problem. Machine learning and AI can be hugely beneficial, but it isn't magic, and it isn't always a good fit. Imagine a machine learning system as an employee who is really slow to learn, but once they know how to do something, they can do it forever without getting tired."

When working with a person, you only have to show them a few examples and give them the basic rules before they get it. But with machine learning, the system needs "hundreds of thousands of examples " before it understands, Geitgey explains.

"Because of this, machine learning is only going to work well for certain kinds of problems where you have lots of examples to work with," he says. "So be strategic! Start with the problems you most need to solve in your business, and then work backward and see if machine learning might be a good solution for them. Don't start by assuming that you need to use machine learning and AI just because everyone else is using it."

Should a company build a custom solution or use an off-the-shelf solution?

"Read up on what out-of-the-box machine learning systems from popular vendors can do and what requires building a new machine learning system from scratch. Many vendors already have great solutions for problems that lots of businesses face, like transcribing audio, classifying images and reading words out of images. If that's what you need, you can use an off-the-shelf solution quickly and easily.

"But if you are trying to automate a process that is very specific to your business and that depends on data that only you have," he adds, "you'll probably have to build a custom machine learning system. That takes more time and costs more money."

With AI poised to take over an ever-increasing number of industries, it helps to stay-up-to-date on this exciting emerging technology so that you can leverage it for your business. Business innovation is all about introducing new ideas into your business. AI is a new idea worth considering.

Read more articles oninnovation.

Photo: Getty Images, Neal Schaffer, and Adam Geitgey

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