AI Personalization

CMOs, This Is Where Your Marketing Automation Stalls

Anjali Yakkundi

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June 6, 2025

Why the Next Era of Marketing Belongs to Teams Who Are Ready to Let Go

For years, automation promised marketers more time, more scale, and more results. And to a degree, it delivered. Scheduling tools got better. Rules-based engines got smarter. But somewhere along the way, automation stopped being about better marketing, and started being about running the same convoluted, arbitrary processes a little faster.

Today, a new shift is underway. Autonomous marketing isn’t just an upgrade; it’s an entirely new model. One where AI agents execute campaigns, test creative, and optimize performance without waiting for a calendar slot or manual review. The role of the marketer doesn’t disappear—it shifts into something bigger, something it was always meant to be: the strategic and creative visionary behind every experience.

This is where marketing has been headed. But adopting autonomy isn’t just a tech upgrade. It’s a mindset shift. No matter where your team is on the automation journey, this blog will explore how leaders can help them unlearn old habits, adopt new workflows, and focus their time where it matters most.

Phase One: Manual - Where Everything Starts—and Stalls

This is where most marketing teams begin: building campaigns manually from the ground up. Segments are pulled by hand, creative is manually mapped to a segment,, and performance reports are generated one at a time. The benefit of this stage is control—every message is reviewed, every list is intentional, and every step is known. But that control comes at a cost.

Without automation, teams are stretched thin. Personalization is limited. Testing is inconsistent. And campaigns are often reactive instead of strategic. Progress feels like a grind, with time spent maintaining processes instead of improving results.

What leaders can do: Encourage your team to track where manual effort is slowing down production, from segmentation to creative updates to QA. Look beyond cost savings and identify where energy is being spent on repeatable work that could be streamlined. Then champion the right investments or partnerships to help your team spend less time building and more time strategizing.

Phase Two: Rules - Based - Comfortable, Common—and No Longer Competitive

In this phase, teams move into a more structured approach. Campaigns run on scheduled logic. Personalization is driven by pre-set rules and audience attributes. Modular templates update automatically. Compared to manual execution, this stage is a leap forward—teams move faster, and messaging becomes more consistent.

But the rules are fixed. Once set, they rarely evolve. Segments and journeys operate on assumptions that may no longer match real-world behavior. While this approach can drive strong performance for known audiences, it often struggles to adapt when new customer signals or trends emerge.

What leaders can do: Don’t mistake automation for completion. Have your team revisit the rules and logic they’ve set up, like what’s still built manually, and what hasn’t been touched in months. Push for regular reviews, external audits, and continuous iteration. This phase is a strong foundation, but not a final destination.

Phase Three: Automated - Responsive Campaigns, Repeatable Paths

Automation gets more advanced here. Campaigns respond to customer behavior. Lifecycle journeys are mapped in advance and triggered in real time. Personalization gets deeper, spanning more data points and dynamic content. This stage is efficient and repeatable, and it’s great for maintaining steady performance across segments and touchpoints.

The trade-off? Flexibility. Every journey, rule, and trigger still requires manual setup and maintenance. When new use cases emerge or performance dips, teams have to dig in and rebuild. It’s effective, but it can become resource-heavy. Teams often find themselves optimizing existing programs instead of exploring new ones.

What leaders can do: Protect your team’s ability to innovate. Create space for experimentation by reallocating time or budget away from maintenance. Encourage a clean-up of underperforming automations, and don’t be afraid to sunset outdated journeys. At this stage, teams have the infrastructure—they need your support to use it more strategically.

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Phase Four: Augmented - Human Execution, Machine Input

This phase marks a turning point. Instead of relying on instinct or historical playbooks, teams begin using AI to actively shape decision-making. It’s a shift from reactive marketing to predictive execution—where every campaign benefits from data-driven input before a single message is sent. For leaders, this means fewer missed opportunities and a more consistent path to measurable performance.

Here, marketers still own execution, but they’re supported by AI that recommends what to send, to whom, when, and how often. Solutions like Da Vinci take traditionally static programs—like batch sends—and elevate them. They optimize content selection, timing, frequency, and subject lines based on individual behavior, improving performance with every send.

What leaders can do: Rethink what productivity really means. Shift your team’s KPIs from campaign-based metrics (engagement, clicks, opens) to business outcomes like customer retention, lifetime value, and revenue growth. Invest in tools that surface real-time insights and prioritize training so teams can act on those insights to build stronger, longer-lasting customer relationships, not just launch faster campaigns.

Phase Five: Autonomous - Strategy from Marketers, Execution from Machines.

This is the most advanced stage, where AI doesn’t just influence decisions—it executes them. Marketers set the goals, define the constraints, and provide the creative assets. AI Agents take it from there, determining how to deliver the right message to the right person across every touchpoint. Campaigns become continuous and self-adjusting, unlocking exponential engagement and financial lift.

This phase unlocks agility at scale. Teams are freed from reactive workflows and manual management. Instead, they focus on strategy, creative innovation, and high-level experimentation. Autonomous execution doesn’t replace marketers, it allows them to take on the roles where they can truly thrive. 

What leaders can do: Support the shift with structural change. Rethink roles, KPIs, and team design to reflect the new balance of strategy and automation. Push your partners to offer autonomous options that reduce complexity, not add to it. If partners talk about Agents, make sure they are actually executing marketing rather than being glorified chatbots.  At this stage, marketing evolves from just a cost center to a performance engine, and it needs leadership that thinks accordingly.

Where to Go From Here

Every team is somewhere on the automation curve. The question is whether they have the support to keep moving forward. Marketing leaders don’t own the day-to-day, but they do need to set the pace. That means funding what’s working, clearing roadblocks, and pushing teams to think beyond the status quo.

Automation isn’t just about doing things faster. It’s about making space for better work. Your job is to make sure your team has the time and tools to do it.