Preface
How many applications with AI assistants have you encountered in the past month? The past week? Do you even notice anymore, or does it just seem that in any significant application or role something labeled as AI is now included?
It doesn’t feel like much of a stretch to say that every company now wants some kind of AI helper embedded in its product. The world has become fascinated with the ability to have conversations with AI and the models that back it. Nearly every industry is working feverishly to figure out how to gain an edge from this capability.
Likewise, growth in AI skills is not only surging but becoming expected. For example, a study from PwC finds that:
- Growth in jobs that require AI specialist skills have outpaced all jobs since 2016.
- Skills sought by employers are changing at a 25% higher rate in occupations most able to use AI.
- Jobs that require AI specialist skills carry up to a 25% wage premium in some markets.
Perhaps in no other industry are there greater expectations for what incorporating AI can do than in the software industry. After all, software is the most expensive content being generated today. The same industry that gave us AI is now poised to take the greatest advantage of its generative capabilities. The possibilities are amazing—and confusing.
As an engineering leader, you no doubt want to (or must) make sure that you are adopting the AI tools and processes that are relevant, useful, and offer genuine value-add. These need to be considered ...
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Read now
Unlock full access