Zendesk's Chief Legal Officer Shana Simmons has reframed how enterprise organisations should approach AI governance, arguing that governance has quietly displaced data quality as the primary blocker to AI adoption. Speaking at Zendesk Relate 2026, Simmons positioned governance not as a legal compliance problem to be solved in isolation, but as a cultural imperative that must be embedded across product, engineering and development teams. Rather than treating compliance as a reactive checklist of certifications, she advocates for what she calls "cultural muscle memory" – a privacy-first mindset baked into organisational DNA from the outset. This represents a significant departure from how many vendors approach AI deployment: whilst almost every platform can produce a compelling proof-of-concept, far fewer can credibly explain how their systems behave under sustained pressure across thousands of customers and use cases. For CX teams already managing Zendesk implementations, this signals that governance maturity will increasingly become a competitive differentiator between vendors, and that your own internal processes around AI guardrails, accountability and transparency should mirror this embedded approach rather than treating them as post-deployment concerns.
The second pillar of Simmons' argument centres on how automation reshapes rather than displaces human work. Her experience visiting a Manila legal team revealed capable professionals drowning in repetitive tasks, yet fearing automation would eliminate their roles entirely. Instead of pursuing pure productivity gains, Simmons now hires for two attributes: AI literacy (teachable) and agency – the willingness to identify broken processes and build systems to fix them. This reframes how support teams and CX leaders should think about their own workforce planning. The implication is stark: teams that treat AI as a tool to eliminate headcount will struggle to retain talent and build the institutional knowledge needed for effective implementation, whilst those that position automation as a means to elevate human capability will attract employees who actively contribute to operational improvement. For support team leads and CX consultants, this suggests that your hiring criteria and team development strategies should shift away from pure technical competency toward identifying people who demonstrate curiosity and a willingness to engage with new tools – qualities that will prove far more valuable as agent-based systems become standard.
Underlying both arguments is Simmons' conviction that empathy and authentic leadership are not soft skills to be compartmentalised, but essential capabilities in an AI-driven workplace. She describes observing how candidates treat people they perceive as "less important" – a signal her executive assistant often provided – as more revealing than formal qualifications. This philosophy extends to how she builds diverse teams and communicates across technical and non-technical stakeholders. For CX professionals, the practical takeaway is that your credibility in driving AI adoption depends less on mastering the technology itself and more on demonstrating genuine respect for how automation affects your teams and customers. In an environment where almost every vendor claims governance maturity and AI capability, the organisations that will genuinely differentiate themselves are those whose leaders model the empathy and accountability they expect from their systems.
Zendesk CLO Shana Simmons: Empathy is the new superpower for AI leaders TechRadar
Zendesk CLO Shana Simmons: Empathy is the new superpower for AI leaders MSN
Zendesk CLO Shana Simmons: Empathy is the new superpower for AI leaders MSN
Zendesk CLO Shana Simmons: Empathy is the new superpower for AI leaders MSN
Zendesk CLO Shana Simmons: Empathy is the new superpower for AI leaders MSN
Zendesk CLO Shana Simmons: Empathy is the new superpower for AI leaders MSN
Zendesk CLO Shana Simmons: Empathy is the new superpower for AI leaders inkl