AI for startups: 4 adoption recommendations entrepreneurs should keep in mind

AI’s rapid rise has swept up companies across the world. Here are four strategic considerations to weigh while leveraging the fundamental predictive enabler in your startup.

Monday February 17, 2020 , 6 min Read

Despite nationwide venture funding hitting a multiyear low, venture capital deployed to artificial intelligence (AI) startups has reached a record high.

Last year, VCs struck 859 deals with AI companies, nearly five times the number that signed on the dotted line four years earlier. To date, the market has 2,045 AI startups and more than 17,000 market followers, with more joining by the day.

AI’s rapid rise has swept up startups and enterprises alike, including US automaker Ford, which recently bought AI startup Argo for $1 billion. The acquisition cements experts’ suspicions of Ford’s coming foray into self-driving technology. Other startups — so many, in fact, that entrepreneurs need a “best of” guide — are betting heavily on bot platforms.

While we have just glimpsed the tip of this innovation iceberg, it’s clear AI is no longer some nebulous technology of the future. It’s an integral part of strategy for startups and enterprises.

Sixty-eight percent of marketing executives report using AI in their function. For a practice that only went mainstream in 2016 and barely existed four years ago, that’s a remarkable adoption rate.

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How, regardless of the platform you choose, can you join forward-thinking entrepreneurs and build your business with AI? Over the last few years, I have worked closely with multiple startups across genres and ,So far, four strategic considerations stand out to leverage AI in your startups:

1. Get to know your next customer

A politician wouldn’t dream of delivering a small-town stump speech to urban constituents. Why? Because you’ve got to know your audience. The same is true for entrepreneurs. Before you broadcast your message, you need to know who you’re trying to reach.

Node, an account-based intelligence startup, uses natural language processing — a fancy term for teaching a computer to understand how we humans speak and write — to develop customer profiles. Node is crunching vast swaths of data to connect the dots between marketers and companies they’re trying to reach.

Once you have ample customer data — Node uses data crawlers to scrape information from social media, news sites, and more — pair machine learning and natural language processing models to extract sentiments from unstructured data. Then, just as senators segment constituents into demographic groups, Node uses cluster analysis to sort clients’ customers into like cohorts.

2. See how people truly use your product

If, heaven forbid, you forgot to tag your neighbour at last week’s house party, Facebook was no doubt there to remind you of your error. How does Facebook know which of your friends you left untagged? It has gone all-in on an AI technique called convolutional neural networks.

Convolutional neural networks, which loosely model how the brain’s visual cortex interacts with the eyes, work by separating an image into tiny portions before running each of those specks through a multilayered filter. It then “sees” where each speck overlaps with other parts of the image, and through automated iterations, puts together a full image.

Many different ways exist to apply this technology, but retail businesses can start with image classification. Try using a convolutional neural network to break down photos of your products posted online. The model can identify customer segments that frequently use your product, where they’re using it and whether they commonly pair other products with yours. Essentially, this automated image analysis can show you how your products fit into customers’ lives, allowing you to tailor your marketing materials to fit.

3. Get inside the user’s experience

Success on social media requires careful listening and quick action. When a social campaign isn’t working, it’s best to put it out of its misery quickly. On the other hand, when one strikes a chord with customers, doubling down pays dividends. But to do so, you need real-time insights about customers’ reactions to your content.

Fortunately, AI can take the emotional temperature of thousands of customers at once. Dumbstruck, a video-testing and analytics startup that I advise, has added natural language processing to its emotional analytics stack. This allows it to provide moment-by-moment insights into viewers’ reactions to media. Dumbstruck’s model grows stronger with each reaction analysed, producing a program that perceives human emotions even better than some people can.

4. Provide affordable, always-on support

Customer service is — or should be, according to consumers — the department that never sleeps. More than half of people, 50.6 percent to be precise, believe a business should be available 24/7 to answer their every question and concern. When asked whether businesses should be available via a messaging app, the “yes” votes jump to nearly two in three. Fortunately, bots don’t sleep, eat or go off-script.

A well-built bot can offer cost-effective, constant customer service. Of course, grooming your bot to serve customers requires front-end data — ideally hundreds of thousands of example conversations — but you can get started with a human-chatbot hybrid. With this approach, the bot answers run-of-the-mill questions, while a human takes over for the more complex ones. Then, as data builds and the model matures, you can phase in full automation.

AI’s impact on startups

Startups will gain a competitive edge in capturing the AI market. Larger enterprises will provide the infrastructure to startups for building innovative services. It is somewhat similar to the business model followed when cable technology was introduced.

Startups leveraging AI technology for industry verticals, including agriculture, manufacturing or insurance, are bound to be successful.

Startups can empower established insurance companies like State Farm, Allstate, and Farmers with technology, enabling them to become more proactive in policy planning. For instance, a new AI insurance underwriter will help to forecast natural disasters and accidents, and adjust premiums.

The predictive, decision-making capabilities are more than just a novel technology. You can manage food supply chains with the help of AI. Startups could develop end-to-end farming solutions with AI analytics for reducing food waste. It will have a huge impact in tackling global issues of hunger and famine.

Whether serving as a research assistant in a large corporation or acting as a voice-activated resource in difficult medical procedures, AI is fast becoming a reality. The AI revolution will benefit new players who learn quickly to use it to their advantage.

AI will be a fundamental predictive enabler helping us solve large-scale problems, and startups are poised to gain a competitive edge.

Ground-level AI sentiment of startups

Regardless of which industry you operate, AI will affect your world in some way. Look into what is present now and how you can use it to gain a competitive edge.

The possibilities with AI are endless; enterprises will become efficient, intelligent, and cost-effective. Undoubtedly, the AI revolution will advance to a point where it will offer real-world benefits to every business, large and small.

(Edited by Teja Lele Desai)