At Exelement we see two realities at once. AI pilots are producing value in specific processes. At the same time many companies struggle to scale wins beyond isolated teams. The difference often comes down to the maturity of the operating model. Clean data, shared ways of working, and a clear view of the customer determine whether AI becomes a real advantage or just another tool everyone talks about.
Our senior Marketo consultant Fredrik Stokke breaks down the three most important takeaways and how they show up in real work.
1. AI is moving from concept to contribution
Adobe’s research shows that the most mature use cases are in customer support and chat. These are already delivering measurable ROI for a meaningful share of practitioners. Leaders expect the biggest near term benefits to be better quality interactions and more consistent communications, which maps closely to what we see in the field.
Outside support, growth is strong in AI assisted personalization and content generation. Adoption is uneven though, and many teams are still in experimentation mode.
Independent surveys back this picture. McKinsey reports a rising share of companies that can point to revenue uplift from gen AI, with service operations among the first functions to show financial impact.
What this means for you
Move your AI work away from one off experiments and into named processes with owners and service level expectations. For marketing and RevOps that usually means:
- A governed pipeline for AI generated content tied to brand, compliance, and performance checks
- Predictive scoring that is reviewed weekly with sales leadership and tuned against actual conversion and cycle time
- Assisted service flows where AI handles classification, summarization, and suggested replies while agents own the conversation end to end
2. Disconnected systems are still the biggest brake on performance
Customers want consistent experiences across channels and they want control over their data. Brands struggle to deliver that without a unified data strategy and real time capabilities. Adobe’s customer engagement analysis highlights consistency as a core expectation.
The tooling is there. Customer data platforms exist to unify records, improve quality, and activate audiences. If identity, consent, and event data do not come together, every AI use case will underperform.
Salesforce’s latest State of Marketing research points in the same direction. High performing teams invest in a unified data strategy and use that foundation to scale personalization.
What this means for you
Prioritize the data. Your personalization engine will only be as good as the data that feeds it.
- Define the golden customer profile and make it available in the tools where people work
- Set clear SLAs for identity resolution, consent capture, and event freshness
- Treat data quality as a product with an owner, a roadmap, and a budget
3. Technology is not enough without human judgment and shared ways of working
AI can point to the next best action. People still need to make the right call. The companies that translate signals into results redesign workflows and decision rights while they deploy AI. Senior ownership of governance and cross functional processes is a common factor among leaders according to McKinsey & Company.
Adobe’s 2025 announcements underline another shift. We are moving from assistants that suggest work to agents that execute work inside enterprise systems. This raises the bar for governance, testing, and exception handling. You need clear guardrails so teams can trust what the system does on their behalf.
What this means for you
Codify how insights become actions.
- Create joint rituals where marketing, sales, and success review AI insights together and commit to experiments for the next sprint
- Define human in the loop checkpoints for anything that changes a customer record, triggers a message, or adjusts commercial terms
- Measure the full loop, from model output to customer outcome, and retire use cases that do not move a business metric
A practical midyear checklist
Use this simple test to see if you are getting real leverage from AI right now.
- You can show a before and after for at least two use cases where AI improved a business metric such as conversion rate, cycle time, or cost to serve.
- Your customer profile is unified across channels and is available in the tools where marketers, sellers, and service agents work.
- You have a content operating model that governs prompts, brand standards, approvals, and performance feedback.
- There is a standing forum where leaders review AI insights and agree on experiments, with clear owners and time boxes.
- You can explain how consent and privacy rules flow through your AI stack. If you cannot, pause new use cases and fix that first.
What this looks like in Marketo
Here are three Marketo centered plays we implement to turn insight into action.
Predictive lead and account prioritization
Use predictive scoring to identify leads and buying groups that are likely to move this week. Pipe the list to sales with short context that a human can use in a first contact. Tune the model against stage progression and closed won, not clicks or opens.
AI assisted personalization at the moment of engagement
Combine your CDP segments with Marketo audience rules and web personalization. Serve content variations based on intent and account signals. Use human review for strategic pages and let the system adapt lower risk assets inside clear guardrails.
Service to growth loops
Feed support insights into lifecycle programs. When Adobe and the broader market point to chat and support as early ROI zones, treat service data as fuel for retention, expansion, and content planning.
So, did the predictions come true
Yes, in the areas that depend on well structured processes and clean data. Not yet in organizations that expect technology to overcome fragmentation or unclear ownership. The most visible gains are in support and operations. The next wave is personalization at scale once the data foundation is in place.
How Exelement helps
We build the operational backbone that lets you turn signals into outcomes. As a certified Marketo partner we connect your data, set practical guardrails for AI, and align teams around shared rituals so that insights lead to action.
If you want a focused midyear audit we can map your current stack, quantify the gaps, and deliver a 90 day plan that your teams can execute immediately. Or we could work together on a monthly basis. Feel free to reach out.
