As AI enters the resolution era, marketing teams are being forced to move beyond experimentation and prove that their strategies are delivering real, measurable outcomes.
With fragmented data, a saturated AI vendor landscape, and mounting internal budget pressure, marketing teams are now struggling more than ever to build a coherent picture of their customers.
As a result, the companies that automate everything will likely be unsuccessful as they struggle to identify which activities drive results.
Emma Acton, VP of Marketing at Zendesk, spoke to CX Today at Zendesk Showcase London to discuss how the successful marketers will be smart enough to know where not to use AI, and where to include a human instead.
“It is still the human in the loop, you are allowing AI to be in the areas that need to be automated and AI agents for those tasks,” she explained.
“But you’re then able to put humans onto those more valuable, kind of almost white glove approaches.”
Too Much Data Yet Too Little Clarity
As AI adoption accelerates across industries, marketing leaders are noticing the AI market has become increasingly crowded as more customer enterprises are receiving an overload of AI messaging from various technology vendors.
In fact, this constant stream of competing claims is now making it difficult for teams to separate innovation from noise as organizations are generating more customer data than ever before across systems and channels.
However, collecting more data does not automatically create better insight, as “your data sources have got to be taught to each other in order to form that picture of the customer,” notes Acton.
When systems remain disconnected, marketing teams are left with fragmented views of customer behavior, making it harder for teams to make confident decisions on experiences.
Furthermore, these marketing challenges are being amplified by increasing pressure to demonstrate ROI, as more marketing leaders are expected to show clear business outcomes rather than simply report activity metrics.
Unfortunately, when it comes to ROI visibility, “there’s very good, very bad, or none at all. There’s a middle ground,” she points out.
For many teams, that middle ground is often filled with partial data, inconsistent measurement, and an incomplete understanding of customer journeys.
Without a connected foundation, proving the value of marketing efforts becomes more difficult, raising the stakes for every technology decision and investment.
Putting AI-First Into Practice
Despite many companies still just discussing AI transformation, Zendesk is now focused on applying it within its own organization.
This includes having created an environment where experimentation is encouraged and giving teams access to both internal initiatives and external tools to explore new ways of working.
This continuous learning approach has enabled the vendor to further its “testing and experimenting, doubling down on what really works within kind of safety parameters,” Acton explained.
By making AI adoption practical and sustainable, this ongoing process of testing, refinement, and scaling will enable successful enterprises to continue delivering measurable value.
“Tom, our CEO, and the executive team, are incredibly supportive of that,” she continued.
“It’s because it’s in our nature to be an AI-first company.”
By investing in both experimentation and integration, Zendesk is in a strong position to help teams connect tools, workflows, and data sources around an organization’s broader objective.
By moving toward outcomes that directly reflect customer success, Zendesk can succeed in differentiation amongst the vendor noise through its resolution, outcome-based pricing model.
This enables customers to experience meaningful resolutions, as an AI’s value should ultimately be measured by the outcomes it delivers.
