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!
Aug 16th 2023
In May 2022, Eleni Stroulia ,from the University of Alberta's AI4Society, presented "Exploring Challenges and Opportunities for AI Across Disciplines" at the AI Seminar.
Sep 29th 2022
Alberta's tech sector needs workers. And its tech students need jobs. Technology Alberta's Gail Powley talks about how the Alberta FIRST Jobs Program found great success connecting the two.
Sep 28th 2022
On July 15, Decebal Constantin Mocanu and Elena Mocanu, both with the University of Twente, presented "Sparse training in supervised, unsupervised, and deep reinforcement learning" at the AI Seminar.
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