Artificial Intelligence for Agilists: Are You Ready?
Artificial intelligence (AI) is finally coming into its own. Technologies such as ChatGPT, DALL-E, driver-assistance, and autonomous robots are clear signs of an AI-driven market shift. AI technologies are being applied in all sectors of the economy, and your organization is likely to be soon experimenting with AI if it isn’t already working with it. Are you ready?
This talk overviews AI and how AI-based solutions are developed, including supervised learning, unsupervised learning, and semi-supervised learning. The talk discusses the similarities to non-AI development that will help agilists to transition to AI teams. We also explore several critical challenges, including: the experimental nature of AI solutions; that data quality is critical to your success; the high failure rate of AI initiatives; and the ethical considerations surrounding AI. We examine the implications of these challenges and work through strategies to address them.
What You’ll Learn About Artificial Intelligence (AI) for Agilists
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- What is(n’t) AI?
- AI terminology in a nutshell
- Developing AI solutions: Agile or Lean?
- Overcoming the data quality challenge
- The development skills you’ll need
- Business implications of AI
Audience For This Presentation
This presentation is targeted at existing agile practitioners who want to learn how successful AI initiatives work in practice, rather than just in theory. There are important nuances that makes AI development different than the application development that you’re used to, nuances that require differences in your way of working (WoW).
Why You Want to Hear About Artificial Intelligence From Me
I’ve been a thought-leader in the agile space from the very beginning. I’ve done significant work in agile architecture, agile data, and hybrid ways of working, all of which are critical for AI. I’m currently working on a Masters degree in Artificial Intelligence and have been consulting part-time in parallel.
