Key Takeaways
Ad Age found optimization and automation lead marketer demand, at 57% and 53%.
Ad Age reports 47% of marketers adopt AI mainly to work faster.
Ad Age found 62% of marketers now use AI at work and beyond.
McKinsey reports 88% of companies use AI in at least one business function.
Automation runs tasks unattended; optimization recommends the best channel, timing, and content.
Marketers have never had more ways to hand off the busywork. The real question is what you do with the time AI gives back.
That is where AI for marketers gets interesting. AI has split marketing into two distinct jobs: running tasks without you, and deciding how to make each one perform better.
This is part two of our four-part series with Wakefield Research and Ad Age on what marketers really think about generative AI.
What AI for Marketers Really Means: Automation vs. Optimization
Marketers often use these two words interchangeably. In practice they solve different problems, and knowing which is which changes how you invest.
The study drew a clean line between the two.
Automation | Optimization |
|---|---|
Runs tasks without human intervention | Recommends improvements to those tasks |
Sends a triggered message the moment a rule fires | Chooses the channel, time, and frequency a customer responds to |
Answers “did the message go out?” | Answers “was that the best way to send it?” |
As Ad Age explains in the study, “AI-driven automation features can help marketers strengthen customer relationships, improve brand performance, and meet their KPIs in today’s fast-moving marketplace.”
Optimization then works both inside and outside that automation, tuning send times and frequency. You send the triggered message with automation, then route it through the right channel and moment with optimization. Strong campaigns need both.
What Marketers Actually Want From AI
Marketers are clear about what they want AI to take off their plates. The Ad Age survey data points in one direction.
57% of the 1,200 marketers surveyed chose optimization as the AI that would most help them.
53% chose automation, ranking it the second most-wanted category.
62% already use AI both for their job and outside of work.
Adriana Gil Miner, chief marketing officer (CMO) at Iterable, has heard this firsthand, as she shared in the study:
“Marketers are telling us: I do not want to set up campaigns anymore. I do not want to crunch data or take a half-day to set up a three-stage welcome program. They’re saying, automate all of that for me, and surface the insights and recommendations to give me the option of making human decisions.”
The theme is consistent. Marketers want machines to carry the setup so they can spend judgment where it counts.
The Business Case for Automating and Optimizing
The payoff of AI for marketers is not only speed. It is capacity: fewer hours lost to setup, more attention for work that moves the business.
Nearly half of marketers, 47%, are drawn to AI because it helps them work more efficiently. As Ad Age puts it, “AI is now widely acknowledged as an essential driver of marketing efficiency and brand performance.” The other draws Ad Age recorded follow the same logic:
49% expect AI to improve business metrics and reflect well on their performance.
45% believe AI will sharpen their skills and make their work more accurate.
37% see AI as an integral part of their skill set.
The pattern reaches well beyond marketing. McKinsey’s State of AI 2025 report found that 80% of companies set efficiency as an objective of their AI initiatives. In the same McKinsey report, 88% now use AI in at least one business function.
For example, Redfin drove a 72% lift in activating dormant sellers and a 15% lift in activating buyers, without adding engineering support. They did it by scoring high-intent users with predictive audience modeling, the capability now built into Predictive Audiences.
Ashley Kramer, chief marketing and strategy officer at GitLab, sees the same shift on her own team, in the report:
“This report finds that marketers increasingly view AI not as a threat but as an enhancer […] AI can drive tremendous efficiencies throughout all organizations.”
That is the real advantage. When you no longer sweat the logistics of building a campaign, you free up room for the creative bets that deepen customer loyalty.
How Iterable Puts Both to Work Together
Knowing the difference between the two is one thing. Building both into daily work without engineering tickets is another.
Optimization has been at the core of our platform from the start. Nova Intelligence, our native AI layer, brings both into the same workflow instead of bolting AI on top of it.
Nova Decisioning, powered by Nova Intelligence, reads live engagement signals and decides the channel, timing, and content each individual is most likely to respond to. As behavior shifts, we adapt the campaign automatically. Three capabilities do the work:
Capability | What It Decides |
|---|---|
The time each person is most likely to open and act on a message | |
How often to reach someone before message fatigue sets in | |
Channel Decisioning | The channel each customer uses and responds to most |
The old mantra of “the right message to the right person at the right time” stops being a manual guessing game. We make those calls from observed behavior, so you can spend your attention on strategy and creative work.
Deciding how to send is only half the picture. You also need to know who to prioritize and what to send next.
Predictive Audiences, powered by Nova Intelligence, flags who is most likely to convert, so you focus effort where it will pay off. Campaign Re-engagement, also powered by Nova Intelligence, auto-detects the best next campaign for a given audience.
Frequently Asked Questions
1. What Is the Difference Between AI Automation and Optimization for Marketers?
Automation handles execution: it runs a task, such as sending a triggered message, without you touching it. Optimization handles judgment: it decides how to run that task better, choosing the channel, timing, and frequency each customer responds to. You need both, because automation gives you scale and optimization makes that scale perform.
2. Why Are Marketers Adopting AI to Automate and Optimize?
Most marketers are not chasing novelty; they want their hours back. AI for marketers takes over repetitive setup and data work, then surfaces recommendations they can accept or override. That leaves more room for the strategy and creative decisions where marketers add the most value.
3. How Does Iterable Use AI to Optimize Campaigns?
Within Nova Intelligence, Nova Decisioning reads live engagement signals and decides the channel, time, and content each individual is most likely to respond to. As behavior changes, we adjust the campaign automatically, so each send reflects current intent rather than a fixed schedule.
4. Will AI Replace Marketers?
No. The pattern across the research is AI as an enhancer, not a replacement. It manages the micro-decisions and manual setup, while marketers set the goals, guardrails, and creative direction.
Where AI for Marketers Goes From Here
The teams pulling ahead are not the ones with the most AI tools. They know which work to automate and which to optimize, then let the system carry the rest. If you want a structured path there, our checklist maps out the steps: Your Checklist for Unlocking the Power of AI.