In the past, implementing artificial intelligence was risky – as with any new technology, it was difficult to predict future implications. We still have a lot to learn, and there are often more questions than answers. Luckily, you don’t need to know everything there is to know about AI in order to implement it effectively. But handing the reins of your company to a third party AI expert may seem just as frightening as jumping in blindly.
Fear no more. Now is the time to augment your workforce with a toolkit of artificial intelligence superpowers – not to replace them with a superhero who can only do half the job. Here’s what the experts say about how to keep up by effectively scaling AI in your organization.
You probably have to change the way you think about structure – and that’s OK
If you’re not already using AI or you aren’t planning on implementing it, you’re going to get behind (and quickly). No matter what stage you’re in, if you haven’t taken a step back to look at how AI implementation will impact every aspect of your company, you need to.
As Google AI’s Chief Scientist Fei-Fei Li says, “AI is empowerment, and we want to democratize that power for everyone and every business—from retail to agriculture, education to healthcare. AI is no longer a niche in the tech world—it’s the differentiator for businesses in every industry.”
The key to AI implementation is understanding that implementation will (and should!) look different in every company. But regardless of what industry you’re in, look at AI as a people problem. Instead of the use cases within the company, focus on how your people will use AI and what they need to know about it.
The foundation of AI implementation is a strong data strategy – all AI applications need high quality data to show results. If your organization is not set up to collect, curate, and share data from every aspect of its business processes, you will be left playing catch-up.
Push past your job description and make AI a team sport
The biggest mistake you can make in implementation is assuming that the technology will only be used by one department. You may not have software engineers on your marketing team, AI experts in your C-suite, or developers on your sales team, but that does not mean that your entire team shouldn’t have some knowledge about the technology and how they can use it most effectively. In fact, the members of your team who are involved in business operations are exactly the people who should understand the scope of the technology. This means reaching across departments to ensure everyone is on the same page. After all – teams work best when they work together.
Change is scary – embrace your fears and trust the experts
Implementation might seem uncomfortable, especially if you’re not an AI expert. Lack of in-depth knowledge at the leadership level could make training your team particularly difficult.
You’ll need to “curate, rather than create content” from experts, says Andrew Ng of Landing AI. You’ll learn alongside your team, and everyone has access to the information they need for implementation to be most effective.
Above all, remember that you control and direct the ways this technology is being used.
Understand how those around you are using AI, and how you can integrate (not just implement) AI into your company mission.
“No technology is more reflective of its creators than AI. It has been said that there are no ‘machine’ values at all, in fact; machine values are human values.” – Fei-Fei Li