AI Automations: Redefining Work

The DAS crew kicked off the show by discussing AI automation at a high level. They talked about where automations are being implemented, how deep you need to go, and where to start if you're just beginning to explore AI in your business. The goal was to provide an overview of what makes an automation.

Key Points Discussed:

• Automations involve programmatically designing repeatable processes that can be applied many times. AI is often a component in larger automations, assisting with information processing and response generation.


• When considering automations, it's important to identify repetitive, data-driven tasks that don't directly contribute to employee job satisfaction. This avoids pushback.


• Automations range from simple to complex. Even small pieces of repetitive tasks can potentially be automated to save time.


• Proper planning is crucial before automation to map out processes and ensure the automation will be effective. Jumping in too quickly can lead to failure.


• Monitoring automations is key as they can break over time. This will likely become a dedicated role in many companies.


• User-friendly automations involve leveraging tools your team already uses daily, like Slack or email. This avoids friction.


• AI chatbots can be automated via APIs after refining the chatbot interactions manually first. This ensures quality results.


• Prompt engineering is critical to get quality output. Asking AI to clarify understanding helps, like you would with a human.

Key Takeaways:

• Identify repetitive, data-driven tasks that could benefit from automation. Break them down into smaller sub-tasks.


• Plan automations meticulously before implementation to avoid failure. Refine sub-tasks manually first.


• Expect to monitor and maintain automations continually. Don't set and forget.


• Make automations easy for employees by integrating tools they already use daily.


• Apply prompt engineering principles like clarifying understanding to get the best AI results.