Zendesk has announced the appointment of Craig Flower as the new Chief Operating Officer (COO), a move that the company frames as part of its transition to an “AI-first” model and its goal to enhance internal coordination to deliver a more robust service to its customers. The announcement, made on February 3, 2026, comes at a time when customer service is undergoing an accelerated transformation: companies seek to automate more, respond faster, and maintain quality when human intervention is required.
In his new role, Flower will be responsible for strengthening customer engagement and service across all areas of the business, accelerating the shift toward Artificial Intelligence, and improving operational performance. The company views this appointment as a key element in execution: it’s not just about launching new AI capabilities, but ensuring they are adopted consistently and deliver measurable value.
From CIO to COO: a promotion with a “operations + technology” focus
Craig Flower is not an external hire. Previously, he served as Zendesk’s CIO (Chief Information Officer), a position from which he led the modernization of internal tools and the application of AI and machine learning to improve processes and inter-team support. That background is crucial for understanding the shift: the company is placing someone with internal knowledge — who has worked specifically on connecting departments, data, and internal platforms — at the head of operations.
Tom Eggemeier, Zendesk’s CEO, justified the appointment with a sense of competitive urgency. He highlighted that AI is reshaping the future of customer service and that, to stay competitive, organizations must accelerate with “radical changes” in speed and efficiency. In this context, Flower appears as the executive tasked with “bridging teams” and turning vision into tangible results.
Flower himself frames his challenge around the blend of customer focus, business strategy, technology, and operational excellence — which, in his view, should define the modern COO. His motto, summarized in a short phrase —“Strategy matters, but execution wins”— reflects what many companies are discovering in practice: AI can be a great showcase, but the real difference lies in daily, week-to-week implementation, with processes and metrics guiding progress.
An “excellence center” for adoption: the common point where enterprise AI often falters
Zendesk has detailed that one of the new COO’s priorities will be maximizing the value customers derive from AI tools by simplifying adoption, enhancing support, and fostering knowledge sharing. To this end, the company plans to establish an “excellence center” where customers and employees can exchange learnings and best practices.
This is significant. In reality, AI adoption in customer support often stalls over very mundane issues: integrating with existing systems, knowledge base quality, response governance, bias control, or impact measurement. When AI remains in pilots or prototypes, the problem is rarely the model itself; more often, it’s organizational change, data challenges, or the absence of clear processes for safe scaling. Zendesk seems intent on addressing this bottleneck from an operational perspective.
Additionally, the company states that Flower will need to innovate and streamline processes, align operations, and enable faster execution. In practical terms: reducing friction between product, sales, and support; breaking down silos; and fostering continuous improvement cadence.
The focus on the “Resolution Platform” and controlled AI
In conjunction with the announcement, Zendesk introduces its approach as a platform designed to “resolve” support cases by combining automation with human judgment. The company describes its Zendesk Resolution Platform as a suite of tools integrating AI agents, a knowledge graph, actions, and integrations, plus layers of governance, control, measurement, and insights.
For technical leaders, the emphasis on governance and control sends an important message: in customer support, the risk isn’t just making incorrect responses, but doing so repeatedly and at scale — which can impact reputation, compliance, and costs. If the goal is to deploy AI agents more broadly, the promise must include traceability, boundaries, oversight, and audit capacity. Zendesk is positioning this narrative as central to its “AI-first” transition.
A seasoned profile in transformation: from TriNet to Hewlett-Packard
Before Zendesk, Craig Flower was CTO at TriNet, where, according to the company, he led product re-platforming, digitized key processes, and accelerated cloud migration. Previously, he spent over 20 years as CIO at Hewlett-Packard, with a track record of innovating business models and transforming processes and IT, helping — according to corporate statements — to improve revenue and margins.
This background aligns with Zendesk’s current challenge: turning AI into a sustained operational and commercial advantage, with organizational changes that go beyond marketing campaigns.
The remaining open question is whether this appointment will catalyze a visible acceleration for customers and partners in the upcoming quarters: simplifying AI deployment in real-world environments, sharing best practices, and aligning execution across teams. By 2026, it’s clear that the market no longer rewards merely having AI, but successfully integrating it without disrupting service.
Frequently Asked Questions
What does it mean for Zendesk to be an “AI-first” customer service company?
AI moves from an additional feature to the core of product, operations, and support, focusing on automating and improving case resolution without sacrificing oversight.
What does a COO do in a software company like Zendesk?
Typically, they coordinate daily execution across departments (product, support, sales, operations) to ensure strategy translates into repeatable processes, metrics, and results.
Why is an “excellence center” important for AI adoption in customer service?
Because successful implementation depends on technology, processes, and data: best practices, integration, governance, measurement, and training often matter more than the model itself.
What risks should companies watch out for when deploying AI agents in customer support?
Knowledge quality, response control, compliance, traceability, data security, and measuring impact on resolution times and customer satisfaction.
via: zendesk.com.mx