AI Shortcuts for Creative Ops That Saves Time & Gets Results

Most Creative Ops teams aren’t short on ideas. They’re short on time!

Every day, I log in or talk to peers and see the same thing: broken systems, overwhelmed teams and a long list of things that could be better with a little more space to think.

I like being productive. What I don’t like is busywork. The repetitive, manual tasks that eat up time but don’t really move the work forward. Early in my career, I used to joke I’d go insane if my job became a checklist of the same tasks on repeat.

Then AI showed up.

At Visa, we were asked to set annual goals tied to AI. At first, it felt abstract. My job was built on relationships, judgment and problem-solving. Where did AI fit into that?

But once I started exploring what it could actually do, it clicked. AI isn’t here to replace the work. It’s here to take real work off your plate. Used well, it can reduce friction, speed things up and create space for better thinking.

Here are a few shortcuts I use to move faster and get better outcomes without adding more process:

Research analysis
AI is great at reviewing long documents, synthesizing themes and turning scattered inputs into something structured. It can compare vendors, analyze spreadsheets or map timelines across a project, product or company.
IRL Example: We needed to summarize current pain points for another department. I uploaded our recent work and asked AI to organize insights by my Creative Ops framework. It did about four hours of synthesis in under a minute. I reviewed and refined with a teammate, but the heavy lift was gone.

Drafting copy and copyediting
Sometimes I dump unstructured thoughts and ask AI to clean them up. Other times, I use it as a ruthless editor. It’s useful for tightening language, shifting tone, pressure-testing arguments or rewriting to fit constraints like slide space or character limits. It’s also helpful for adapting content across formats.
IRL Example: I used AI to proofread and tighten this post after writing it in a caffeine-fueled sprint.

Brainstorming
AI is still a bit like an intern here sometimes, but it’s a useful starting point when nothing is coming to mind. It helps generate options, even if most are average. You only need one good idea to get momentum.
IRL Example: I’ve used it to kickstart campaign directions at work and, more practically, to figure out solutions for everyday problems like managing cat litter without losing my mind.

Answering repetitive questions
This is where AI really earns its keep. If the same questions come up over and over, AI can handle the first response and free up your team.
IRL Example: At Visa, we built a chatbot that surfaced answers from our Digital Standards Manual and internal resources. It reduced the constant back-and-forth and let teams self-serve instead of waiting on a PM to respond.

First reviews and audits
AI is great for a first pass. It can check for completeness, flag gaps or evaluate work against a set of criteria before it ever reaches a human reviewer.
IRL Example: At AAA, I built a structured intake approach and used AI to review incoming requests against those standards. It helped identify missing information, unclear objectives and misaligned priorities before work starts.

Explaining and summarizing
AI is the fastest way to get up to speed. You can ask it to explain something at any level, from beginner to executive. It’s also a lifesaver for summarizing long threads or dense materials.
IRL Example: A stakeholder once sent a 92-page deck as input for a copy project. Instead of digging through it line by line, I used AI to summarize the key points and build a working brief.

Where AI still needs work

Image rendering
Still inconsistent. Great for exploration, not always reliable for final output.

Details and accuracy
It can miss small things. Typos slip through. Hands still have too many fingers. You still have to review the work.

Resume reviews and “expert” advice
It tends to default to generic best practices. Useful for structure, less useful for differentiation. And it still leans heavily on keyword matching, which gets muddy when everyone is optimizing for the same terms.

Being human

AI still lacks the ability to imitate human emotion effectively (thank goodness) and it lacks taste. It can't review it's work with years of design or copywriting experience. This is why human first, human last is a much necessary part of any AI process.

AI isn’t perfect. Not even close.

But used alongside experience and judgment, it’s one of the most useful tools Creative Ops has right now.