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How young is too young to start AI model training?

How young is too young to start AI model training?

Nowadays, all companies at all stages should be thinking about artificial intelligence (AI) and machine learning. AI has the ability to forecast and make informed decisions about every aspect of your company. Not only can it help a company decide whether to make a huge pivot in business strategy, it can also predict who in the office is most likely to dance on the table at the annual holiday party. AI has been transforming finance, human resources, marketing and sales, logistics and operations departments, as well as research and development across the globe, and its possibilities are endless. Decisions that normally would be made by human instinct or basic data tests are being backed by AI models that help businesses make the most accurate forecasts possible. But for many adolescent startup companies, it’s unclear what age is appropriate to get active in AI. So, for all the prepubescent startup companies that are ready to experiment intelligently, consider this “the talk.

It is not always age that matters, it’s more about maturity. Does your company have the maturity to perform AI? Many companies use AI as a buzzword to draw in investors, but its the performance that matters. In order to make sure your model building means something, companies must have two things to make the most of their first machine learning experience.

1. Data

Companies with access to proprietary data are very well positioned to begin using AI because they have unique data that is available only to them. These companies have the ability to acquire and use their data to constantly improve their product based on the market, consumer behavior, or even employee behavior. Data-rich companies can be sitting on a goldmine if they leverage that data with the use of AI. Take a company like Amazon for instance. They collect massive amounts of data on consumer behavior that belongs only to them. Amazon has been able to use this data to power their entire operation, expand into new markets, make purchase recommendations, and become one of the world’s most powerful companies — and it all stemmed from data.

2. Concrete objective

Plenty of companies incorporate AI as a means to no end. A company must specify exactly why it is leveraging its AI. How AI is applied to any business is important, as AI does not run on nothing. Believe it or not, human input is required to leverage AI to build models that answer real business questions. For example, let’s say your company wants to vamp its customer service to be the best. You might consider using AI specifically to improve customer satisfaction and wait time. Machine learning can turn data into customer satisfaction by learning what makes a customer satisfied, and replicating the customer service process for each inquiry. This is a specific objective that will create a competitive advantage and a higher ROI.  

However, if your company does not have these vital puzzle pieces quite yet, that doesn’t mean you cannot plan for AI adoption. Any company can plan for ways to take advantage of AI in the future to stay competitive in the market. Think about it like this: Ten years ago a company could survive without having a website, but today it is almost impossible to reach anyone without an internet presence. Ten years from today, AI will be incorporated into most software, and the ability to leverage it will be the way to differentiate your product and using it creatively will help a company come out on top.

So, even if your company is not ready to take the next step, planning and maturing can make losing your AI virginity that much more special. It’s never too young to be thinking about AI and considering ways to apply it to your company’s business needs. Continue doing your research, and slowly start bringing up the topic in quarterly meetings. There is no reason to be shy about the birds and the bees of AI, as long as you use it responsibly.

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