AI Was Supposed To Do The Dishes: The Real State Of AI In Business Operations

“I want AI to do the dishes so that I can go do art”

AI is advancing fast, but for ops teams, the day-to-day reality often looks very different from the headlines. This talk is a grounded, practitioner-focused look at where AI actually is today in business operations, where it’s already delivering value in the way that enhances the human experience (“doing the dishes” for us), and where expectations still don’t match reality (and taking away from the human experience).

WHAT WE WILL COVER:

• Current AI capabilities & recent advancements
  What today’s models are genuinely good at — and what still breaks quickly in real operational environments.
• Tools being used in ops right now
  Automation, analytics, copilots, internal tooling, and where AI is showing real ROI.
• Concerns & limitations
  Data quality, governance, hallucinations, security, compliance, cost, the human-in-the-loop and job replacement problem.
• What to look forward to
  Where AI is trending toward doing the “dishes”, and how ops teams can prepare for what’s coming next.
• Group discussion
  Let’s discuss some of your personal thoughts, opinions and concerns

This is an honest discussion for operations professionals who want to understand:

• What’s worth experimenting with now
• What’s still risky or premature
• How to think strategically about AI adoption in ops over the next 12–36 months

Come for practical insights, stay for real-world discussion with people who are actually trying to make this stuff work.

WHO SHOULD ATTEND:
This event is for people who work close to the real machinery of the business, including:

• Business Operations professionals
• Operations leaders and managers evaluating AI adoption
• Process improvement, automation, and systems owners
• Analytics, data, and tooling partners embedded in ops teams
• Operators responsible for scaling internal operations

You’ll get the most value if you’re:

• Curious about AI but skeptical of the hype
• Responsible for tools, workflows, or operational outcomes
• Trying to understand where AI fits practically , not theoretically

No deep technical background required.