Something to Think About
Krithika S. was the first marketer at OpenAI and Stripe. She’s a pretty big deal and occupies a lofty perch in the marketing pantheon. Follow her at krithix.com.
“How-To”
How to create the “What’s happening in AI” podcast
There’s a theme for this newsletter: AI Overwhelm.
I mean, I follow a bunch of newsletters and thought leaders to stay up to speed on what’s happening in the world of AI.
It’s really valuable to me that these people spend their time gathering relevant AI information and compiling it in a newsletter.
It’s still too much, though.
So I thought there had to be a better way to pull the really good stuff from all of these newsletters.
Here’s what I came up with.
I used a tool called FluxPrompt from the guys at Enhanced AI.
FluxPrompt allows you to build AI agents in a Miro- or Lucid-like canvas. But I’m sure these steps could be duplicated in other ways.
Here’s my recipe:
- I had my mail app automatically forward emails from certain addresses as they arrive and mark them as read in my inbox.
- These emails trigger the FluxPrompt workflow to…
- Use ChatGPT to analyze the email for the types of information I was looking for. For example, I want to hear about new products, new use cases, and product updates. I don’t care about ads, about the author’s journey, or about offers.
- Use Claude to write a succinct summary of the salient points in the newsletter.
- Format the output to favor AI transcribers.
- Add the summary to a text object.
Then I added another layer.
- Each morning at 10 am, do the following:
- Gather all the summaries from the previous 24 hours.
- Analyze them for duplicates and flow to create a master summary for the day.
- Use ElevenLabs to voice the summary.
- Email me the text and audio file.
- Clear out the text object for the next day’s entries.
Here’s an example of one of these digests.
Now I just listen to that audio file as I would a podcast, during a workout, driving somewhere, or tackling chores around the house.
What does AI adoption look like?
Here are some of the latest stats from Forbes:
- 97% of leaders investing in AI report positive ROI
- 49% of tech leaders say AI is integrated into business strategy
- ⅓ of total global VC investment in 2024 was in AI
- 30% say it is fully integrated into operations.
- 25% of enterprises say they will deploy AI agents in 2025
- 81% of workers are not using AI
- 39.4% is the current adoption rate of AI
Wait, what?
If 97% of leaders report positive ROI, but 81% of workers aren’t using it, doesn’t that sound like a huge mismatch?
I’m not sure we really know where we stand with AI across the board.
This list from Carilu Dietrich‘s report, Marketing’s AI Frontier: What 50 Tech CMOs Revealed is based on interviews with CMOs themselves. It feels a little more useful.
- AI is transforming every aspect of marketing
- Smaller companies often move faster than enterprises
- Significant tool experimentation (and thrashing)
- Heated build vs. buy debates
- Surprising return to on-premises solutions
- Early signs of AI replacing (not just augmenting) marketing roles.
- We’re still in a Wild West phase before tool consolidation
- The most successful leaders are digging deep with the smartest peers, experimenting deeply, and applying their marketing expertise to guide AI implementation
Essentially, we’re watching the ground shift beneath our feet. AI isn’t just augmenting roles anymore — in many cases, it’s replacing them. Amid tool thrash, heated build-vs-buy debates, and a surprising shift back to on-prem solutions, marketers are navigating a modern Wild West.
The “things are moving, but we’re not sure where they will end up” dimension resonates with me.
Headlines like these inspired this image…
A Problem of Pace
Just what does it take to be “up to speed” on AI?
Does it mean you’re informed? Do you have AI capabilities deployed? Is every AI initiative fully ramped and at 100% utilization?
All of these are tough when the landscape is moving so fast.
Check this out.
This is the release schedule for the biggest three LLMs over the past 2.5 years (since launch). This pace is an average of over 15 major releases per year!
More than one per month.
Just how fast are you supposed to react to new tech?
Here’s another graphic for perspective:
That’s almost 11,000 funded AI startups to keep track of.
There’s the real question. How durable is what you know about AI?
Let’s say you stayed abreast of all major updates to the AI landscape over the past 2.5 years.
Would someone coming up to speed NOW have an advantage because so much of the corpus of your knowledge was already obsolete?
And that’s where future-proofing comes in.
What principles can we deploy that will anchor us in this sea of change? Here are five that have served me well:
5 Future-Proofing Frameworks
1. JTBD
Break your work down into fundamental components — not just tasks, but the deeper purposes behind them. What truly needs a human touch? What is formulaic and easily automated?
Think: Right Brain vs. Left Brain. Brand vs. Demand. EQ vs. execution.
For example, if I’m tackling a marketing task by humans, I would separate tasks into content and creative versus analytics and ops.
Start by identifying:
- The most valuable tasks YOU perform
- Which ones are easily trainable
- Who else is solving similar problems you can learn from
2. Locate the Human
Ask yourself: Where is the human in this process?
For example, if I don’t have a functioning outbound SDR motion with human SDRs, what makes me think the AI version will be better? There could be reasons, but by default, I’m looking to scale something that works, not invest in something unproven.
AI is excellent at scale, memory, and speed, but humans bring empathy, nuance, and context. Make conscious decisions about where to insert or preserve humanity in your workflows.
Pro tip: Sometimes, your audience might not even be human (think bots or algorithms). Design accordingly.
3. Future-Proofing Teams
This is a big one. The teams of the future will be AI-fluent.
What are we doing to enable that?
- Do we have a mandatory AI use policy?
- Are we investing in AI-fluent teams: make space for their growth?
- Do we understand the difference between skills and abilities?
Invest in higher-order capabilities like:
- Soft skills
- Critical thinking
- Adaptability
- Mastery
These can’t be outsourced to machines.
4. Retain Flexibility
The Age of AI punishes loyalty.. Don’t lock yourself in with rigid contracts, tools, or platforms.
- Stay nimble on pricing
- Prepare for vendor consolidation
- Use middleware to keep your options open
And take advantage of this time to optimize your pricing and/or select vendors who offer the most flexibility. Many of these companies will be consolidated in the coming year. How will that affect your usage patterns?
Kyle Poyar from A new framework for AI agent pricing, 4/9/25
5. Embrace Experiments & Change Management
Change is uncomfortable. But innovation lives on the other side of discomfort.
Build muscle around:
- Experimentation – Run fast, small pilots
- Ambiguity – Not everything will be clear
- Change management – Help your teams move with confidence
Remember Mike Tyson’s words: “Everyone has a plan until they get punched in the face.”
Namaste
Chad Jardine, CEO at CMO Zen
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