Artificial intelligence is all around us.
Not so long ago, artificial intelligence (AI) existed only in the world of science fiction. But today, AI pervades our daily lives – whether we’re aware of it or not. Take these examples:
Have you used a ride-sharing service (like Uber or Lyft) lately?
These companies track millions of metrics each day, then employ machine learning (DL) and deep learning (DL) – both subsets of AI – to match drivers with riders, optimize routes, develop safety processes, and much more.
Some washing machine manufacturers are introducing next-generation models controlled by apps – and those apps use AI to determine the best cycle for the type of clothes you’re washing, and also help with maintenance and troubleshooting to ensure your machine is operating to optimal results.
In the healthcare space
, one organization has trained and taught algorithms to augment the work of radiologists, allowing them to make diagnoses more accurately and efficiently.
Three Ways to get Your Business AI Ready
Implementing AI is a science and an art.
The rapid growth of AI technology means that solutions are now affordable and available for organizations of all sizes. Here are three ways to get your business ready to reap the rewards:
1. Get some education
For an AI implementation to be successful, it’s imperative that your employees have adequate AI knowledge. This applies not only to your IT staff, but also to those responsible for preparing and using data and processes. Invest in employee education and plan to continue offering skills training for the foreseeable future.
2. Start small, then scale
Identify a few key areas where your business would benefit from AI (usually data-heavy environments), then choose a relatively small process or task for your first foray. You’ll quickly learn if your existing data and technology infrastructures – and your people – have what it takes to scale up your AI footprint. It’s better to test your capabilities in a low impact way than to go big and fail big.
3. Know your infrastructure limitations
Assess your existing data and technology infrastructures to ensure your business has the foundational ability to handle AI. This includes properly labeled data (AI has limited ability to analyze data without labels). As an example, by feeding AI clearly categorized support desk tickets, you’ll get more insightful results.
You’re not too late.
According to a recent Gartner survey*, only 4% of surveyed companies have invested and deployed an AI-based solution. *Gartner 2018 CIO survey
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