Episode Details

What's up everyone, today we have the pleasure of sitting down with Tata Maytesyan, Growth Consultant, Keynote Speaker, and AI Trainer.

• (00:00) - Intro
• (01:08) - In This Episode
• (01:46) - Sponsor: GrowthLoop
• (02:50) - Sponsor: Attribution App
• (04:34) - Which Marketing Tasks Are Actually Worth Automating
• (13:07) - Why Deep Generalists Outperform Channel Specialists in Marketing
• (26:07) - Sponsor: MoEngage
• (27:04) - Sponsor: Knak
• (35:06) - Why Marketing Org Charts Are Not Getting Flatter
• (43:01) - Why Change Management Determines Whether AI Adoption Actually Sticks
• (48:03) - The Fear of Automating Yourself Out of a Job
• (53:13) - The Voice Diary Technique for Tracking Your Own Energy at Work

Summary: Tata Maytesyan runs an AI bootcamp for marketers on Maven and consults with scaling companies across Europe. In this episode, she breaks down why the best AI automation targets are the boring, repeatable tasks nobody talks about on LinkedIn, and why the specialist-to-generalist shift in marketing is already happening whether your org chart reflects it or not. She also gets direct about what's really going on inside companies claiming to go flat, the 100-hour threshold for building genuine competence across domains, and the self-preservation fear she hears from leaders every week. If you have ever wondered whether you are building your career around the right foundations, this episode is worth your full attention.

About Tata Maytesyan

Tata Maytesyan is the founder and CEO of Grow Global Tech, where she builds AI-powered marketing systems for tech scale-ups and runs a hands-on AI bootcamp for marketers on Maven. She spent 15+ years leading growth inside Nike, Deloitte, and Picsart, including a stint as Head of Product Strategy and Operations for Picsart's content and AI division, a platform with over 100 million monthly active users. She has since advised more than 40 companies across 12 countries on go-to-market strategy and AI adoption, and consults primarily with CMOs and CEOs at companies between a few million and $200 million in annual revenue.

Which Marketing Tasks Are Actually Worth Automating

The wrong starting point for AI adoption in marketing is inspiration. Most marketers scroll LinkedIn for jaw-dropping use cases: ad creative generated at scale, competitive analysis in 10 minutes, entire campaign briefs written by agents. It looks impressive. It's also almost never applicable to your specific job on any given Tuesday. Tata has spent years watching this pattern play out with consulting clients and bootcamp students. Her fix is deliberately boring.

At the start of every engagement, she asks everyone in the room to close their AI tools. Then she opens Miro and maps how the team actually works. From there, 3 questions run against every process on the board: how often the task repeats, how acceptable an imperfect output would be, and whether it's something you actually enjoy doing.

Those 3 questions quietly eliminate most of what people think they want to automate. Frequency kills off exciting-but-rare workflows not worth touching. Risk tolerance separates contexts where imperfect output is acceptable (most content tasks) from those where it isn't. Tata advises a healthcare client where certain work is patient-facing, and mistakes there carry real consequences. The enjoyment filter protects the parts of the job people actually like, because automating something you love is just spending money to make work less interesting.

Her own example from the day this episode recorded: she built a script to pull LinkedIn post metrics (impressions, comments, likes) into Notion. Before that, an assistant handled it. Before that, she did it herself. She describes the task with open contempt, which makes it the perfect candidate: something done constantly, where i