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Now that you have a basic understanding of what AI is, let’s take a look at how you can get on the path to adopting it in your business!
Here at Amii, we use the AI Adoption Spectrum to gauge a company’s AI capabilities and map out how they can move forward – and it all begins with “Exploring: Discovering potential applications and approaches”.
Here are three things you can do to get to that first step:
Start with developing a shared, common language around AI and machine learning, as well as basic understanding of the concepts. Laying this groundwork is critical for teams who want to have meaningful conversations around the projects and ideas that will accelerate the outcomes that matter most to your business.
There are lots of classes and resources available online for beginners, including our own ML Foundations 1 & ML Foundations 2 classes. The important part is ensuring that everyone on your team is taking in the same information, so that you are growing your vocabulary and understanding together.
AI and machine learning algorithms are only as good as the data they’re built and tested on. Taking stock of the data you’re currently collecting, how much you have, the format it’s in, and the processes around collecting, processing and storing it will be important – this will inform what types of systems you will be able to build.
Mapping this out will also help you see any gaps in your current processes. Generally, AI systems require foundational pieces to reach their full potential, such as capabilities for data storage, management and analytics.
Once your team has built a shared vocabulary around AI and machine learning and understanding of the company’s data, you’re ready to begin investigating possible opportunities!
Get together with your team to brainstorm opportunities. Take inspiration from what your competitors or others in your industry are doing. Once you have a list of ideas, determine how much effort each would take, as well as the risk level.
The best beginner projects are those that require low effort and hold low risk (we call these quick wins). Beginning with these projects will allow your team to build experience and confidence. While exploring quick wins, consider the long-term, strategic direction you want to take with AI. It has been shown that companies with a long-term view see a better ROI.
We’ve seen great value in guided brainstorming through our AI Planning and Initiating (AIPI) sessions, where Amii experts help companies to examine their current data and discover and prioritize possible AI and machine learning opportunities. Finally, top ideas are refined further using our AI lean canvas.
Once you’ve chosen the problem you want to work with, it’s time to decide who should develop your AI solution – that is, whether you’d like to build the solution in-house, buy an existing solution, or partner with another organization to build a custom solution. There are pros and cons to each option, which we’ll explore in next month’s article!
May 11th 2023
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Russ Greiner — Amii Fellow, Canada CIFAR AI Chair and one of the founding members of Amii — is being recognized for his outstanding contribution to furthering computing science with a Lifetime Achievement Award in Computing Science from CS-Can | Info-Can.
May 3rd 2023
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On April 14, Sunil Vedula—founder of Nanoprecise Sci Corp — presented “IoT + AI enabled predictive maintenance & operational excellence for asset intensive industries ’" at the AI Seminar.
May 2nd 2023
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All are invited to attend the multi-day event, with diverse programming catered for AI researchers, industry leaders, pop culture enthusiasts and anyone who has ever been curious about artificial intelligence.
Looking to build AI capacity? Need a speaker at your event?