How AMII Helps Businesses Adapt to AI with Adam Danyleyko
Episode 314 features Adam Danyleyko from AMII (the Alberta Machine Intelligence Institute) breaking down what AMII actually does and how they help organizations move from AI curiosity to real adoption. Adam explains AMII’s foundation in world class research and how the institute translates that research into industry impact by supporting everyone from startups to large corporations through training, shared AI language inside teams, roadmap building, and hands on proof of concept work.
The real lesson of the episode is that adapting to AI starts with clarity, not hype. Adam walks through how the “right tool for the problem” mindset changes everything, why data strategy matters especially for startups, and why AI projects often require experimentation with no guaranteed outcome the way a typical software build might. He also touches on where AI is headed next through more efficient models, edge computing, and practical real world constraints, plus how AMII screens work through a principled AI lens focused on impact, fairness, and responsible use.
Additional note: This episode also marks three years of The Business Development Podcast.
Follow Adam Danyleyko on LinkedIn: https://www.linkedin.com/in/adam-danyleyko/
Learn more about AMII: https://www.amii.ca
Key Takeaways:
- AI is not a strategy on its own; it only works when it supports a clearly defined business problem.
- Starting with the tool instead of the bottleneck almost always leads to wasted time and stalled initiatives.
- Businesses need a shared AI language internally before they can successfully adopt or scale it.
- Data readiness matters more than model choice when it comes to real-world AI outcomes.
- AI projects often require experimentation, iteration, and learning rather than guaranteed deliverables.
- The right AI solution depends on context, constraints, and environment, not what is trending.
- Building internal capability is more sustainable than outsourcing all AI decision-making.
- Responsible AI requires intentional choices around fairness, impact, and long-term use.
- AI works best as an amplifier of good processes, not a fix for broken ones.
- Organizations that adapt to AI successfully treat it as infrastructure, not a magic product.
This episode of The Business Development Podcast is proudly sponsored by Hypervac Technologies and Hyperfab, our 2026 Title Sponsors. We’re incredibly grateful for their continued support of the show and the work they do building world-class industrial solutions right here in Canada. Hypervac and Hyperfab represent innovation, reliability, and execution at the highest level, and we genuinely appreciate them being part of this journey.
If you’re in the industrial space, we highly encourage you to check them out at www.hypervac.com.
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Mentioned in this episode:
Hyperfab Midroll
