Are we ready for AI?
The question every organization is – or should be – asking at the dawn of the age of artificial intelligence.
When the Internet first launched, it took a while for content to be added to it. At first, it had thousands, then hundreds of thousands, to millions, to billions of pieces of content, and now pretty much everything under the sun exists on the Internet. And with the explosion of content and unfettered access to consumers, businesses began to slowly embrace the Internet.
There was an adoption gap, though, between brick and mortar businesses and Internet-based businesses. It took brick and mortar business longer to realize their customers were moving to online shopping and they lost market share to the likes of Amazon.
And now, there is a similar chasm to the one that existed between businesses deciding if they wanted to be online or not. This new gap is emerging between business who are actively using AI to inform their decision making and those businesses who are not sure if they should join the AI revolution.
You may not fully feel it yet, but AI is permeating everything. You already carry a form of AI in your pocket, and some of you may have it in your businesses or homes with your smart speakers.
In this post, we intend to provide some simple guidelines to determine if your business is ready for AI or not. You probably are, but just in case you are not, now would be a good time to start!
1. Have you been diligent about collecting data?
Data is key for AI to become successful. The best analogy that can be offered here is that a person cannot make a decision about how to swim if they have never once in their life been exposed to swimming, let alone seen the mechanism of how to swim through any instructions. A person who’s never been taught how to swim would most likely flail their arms and sink.
The same applies to AI. In order to teach AI to perform a specific task or a series of tasks, it must have data. That data input is going to help the AI learn to make a recommendation or perform a task. The more data it gets fed, the better the outcome. So, if you have already been collecting data on your business and what matters the most, then you are already well on your way to be getting ready for AI.
2. Do you know what you want to improve in your business?
It’s very important that prior to putting an investment of time, resources, and capital towards building any sort of AI program for your business, that you have at the very least an idea of what you want to improve with your business.
It could be that there are many repetitive tasks that you and your employees at the company perform, and by automating that process, you would create efficiency of flow so that they could spend their time working on more meaningful tasks that require creativity and the human touch.
3. Is the data you have been collecting applicable to the business problem you want to solve?
If you have only been collecting data on your customers’ grocery shopping habits, you will probably not be able to launch a successful AI program to determine what colors to offer in your new line of electric scooters. Having the right amount of the right data for the problem you want to solve is critical.
Once you know what you want to improve and you determine that you have data that applies to your problem statement, then your mission takes you to the next step on this journey.
4. Are you an AI buyer or an AI builder?
Do you want to become more than a tech company, and actually build a team of data scientists that can perform research for your business and validate ideas? You could already be a tech company, but if you know anything meaningful about AI, you know that it will require quite a large capital and time investment to get anywhere.
And what about when you are done? Do you simply dissolve the whole team you created? Those are questions that only you can answer for yourself. So take your time in making this decision.
5. What kind of AI program do you need?
Now that you have hopefully learned a little bit about how AI could help your business, you need to decide if the investment of time, effort, and capital will provide you with meaningful ROI, because the bottom line is if it does not, then you should not go down this path.
Off-the-shelf AI solutions exist, but they are often not tailored to the needs of individual businesses and either need extensive customization to bring value or they simply never bring value at all. At the opposite end of the spectrum, many companies are attempting to build their own internal AI teams in-house, which takes significant time and capital with no guarantees of success.
At Dynam.AI, our approach of offering end-to-end tailored AI solutions enables customers with a world-class data science team and proven algorithms without the time and risk of building an in-house team.
If you are interested in learning more about AI and Machine Learning, sign up to follow our blog with the form below or download our free whitepaper.
About the author
Yashar is a 3x startup founder, who raised capital for all three companies, where he built, and shipped the products. His last startup was based in the Bay Area, where he was joined by famed VC Neil Weintraut of Palo Alto Ventures as his co-founder. Since 2017, at the birth of his daughter, he decided to focus his time and efforts in San Diego where he lives with his family. Since then, Yashar has joined Analytics Ventures where he leads Product and works with a brilliant team of AI Scientists, and Engineers.
In his spare time, Yashar loves to spend time with his family, going to the Zoo, the beach, and traveling as often as possible. He has also joined forces with other San Diegans to form San Diego Tech Hub to provide greater awareness and draw to the San Diego Tech Scene.
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