Generative AI has the potential to transform workplace productivity – but do organizations know how to deliver on that promise? New research shows that employees who use generative AI tools engage with them up to ten times per day, spending over three hours per week interacting with AI at work.
And yet within the same organizations, large groups of employees have never meaningfully engaged with these tools at all. Many hesitate to experiment, struggle to trust outputs, or abandon AI capabilities entirely. Because this friction is often silent, no alert flags it, no ticket captures it, and no dashboard reports it.
As long as enterprises roll out AI without ensuring employees know how to apply it in practice, the technology will struggle to deliver on its promise.
The organizations recognizing this are starting to ask a different question: not “How do we get employees to use AI?” but “What conditions make them choose not to?”
This shift in perspective changes everything. It reveals that success is not just about adoption metrics or support requests, it’s about enabling a zero-ticket workplace, where technology works intuitively and friction never even needs to raise a ticket.
Key takeaways
AI adoption introduces subtle friction: Unlike traditional software, AI tools rarely “break.” Hesitation, uncertainty, and disengagement are common and often silent, requiring proactive attention.
Prevention beat’s reaction: IT must move upstream: understanding where employees struggle, intervening before frustration builds, and embedding guidance in the flow of work.
Adoption is also a governance issue: When employees lack confidence in enterprise AI tools, they often seek alternatives outside approved systems. Without visibility into adoption behaviour and without change management to guide usage, organizations risk shadow AI usage, inconsistent outputs, and growing compliance exposure.
Zero tickets become a natural outcome: When friction is prevented, confidence grows, adoption rises, and support requests naturally decline — creating a zero-ticket environment as a byproduct of strategic enablement.
Looking beyond tickets in an AI-driven workplace
For decades, ticket resolution has been the fundamental unit of IT success, but tickets are reactive by design. While this model was already limited in pre-AI environments, it becomes even less sustainable today as AI tools introduce new challenges.
AI rarely “breaks” in obvious ways. Instead, it introduces subtle uncertainty such as questions about where to start, which tool to use, or whether the output can be trusted. Most of these moments never trigger a support request, leaving leaders unaware of the real challenges employees face.
Zero tickets, in this context, is not just a reduction in support requests. It represents a seamless environment where employees can access and use AI tools confidently, without hesitation or friction. It signals that technology is working intuitively, workflows run smoothly, and employees can focus on their work rather than figuring out how to use the tools.
The mental shift: from ticket reduction to behaviour change
Addressing this requires more than process improvement. It requires a redefinition of what IT is trying to optimise. For years, the core question has been: “How do we close tickets faster?” which is built on a flawed assumption that friction is inevitable, and IT’s role is to respond once it appears.
Especially in an AI-driven workplace, that assumption no longer holds because the most significant barriers to enterprise AI adoption don’t look like system failures. They look like hesitation, misunderstanding, lack of confidence, and those rarely generate a ticket, so IT only end up seeing a fraction of the problem.
Leaders therefore need to shift from measuring how efficiently disruption is resolved, to actively shaping the conditions that prevent disruptions in the first place. This requires a structured approach to change management: understanding where employees hesitate, where adoption stalls, and where confidence drops off, and providing support before disengagement becomes the default.
In other words, the focus moves from managing tickets to influencing behaviour that empowers employees with technology.
Equipping leaders to prevent friction before it starts
Prevention begins from the outset. Deploying an AI tool is only the first step; real value comes when employees make it part of how they work. Achieving this starts with visibility.
Leaders must look beyond access and usage metrics to understand how employees are interacting with AI, where confidence builds, and where engagement quietly drops off. Limited visibility not only clouds adoption patterns, but it also makes it difficult to detect shadow AI usage or ensure tools are being used in ways that align with governance and compliance expectations. When this behavioural insight is missing, decisions are made on incomplete signals. Once patterns of hesitation and disengagement become visible, organisations can act with precision to close adoption gaps before they widen.
Visibility provides the insight to act, but alone this is not enough. Employees also need guidance to help them navigate AI tools as they work. Traditional enablement approaches, designed for slower-moving software, cannot keep pace with today’s AI-driven environment. New features, updated prompts, and expanding use cases emerge rapidly, meaning static documentation and one-off training sessions fall out of date almost immediately.
Instead, employees need support that evolves with the technology itself – contextual, timely, and embedded directly into the flow of work. This allows them to build confidence as capabilities grow and receive guidance at the moment it is needed.
This is what a preventative approach looks like: addressing friction at its source before it escalates into frustration, avoidance, or support demand.
The real route to zero tickets
Zero tickets isn’t just a measure of IT efficiency; it’s a reflection of a workplace where technology works seamlessly, adoption is actively managed, business risk is minimized, compliance is ensured, governance is maintained, and the value of AI is fully realized.
It is the byproduct of an environment where technology is introduced with visibility, reinforced through in-the-flow enablement, and continuously shaped around real behaviour.
As Jason Conyard, former CIO at VMware, put it: “We have to remember technology needs to be in the service of people, not the other way around.”
Zero tickets reflects exactly that reality. A workplace where AI serves employees seamlessly, their experience is prioritized, and barriers to adoption are removed, while the organization retains control, mitigates risk, and meets compliance obligations. Support requests decline not because they are suppressed, but because friction is prevented before it exists. This approach ensures both employee empowerment and business protection, delivering measurable value from AI initiatives.
Unlike traditional software, AI tools rarely “break.” Friction is subtle as employees often struggling with the following: unsure how to start, which tool to use, or whether outputs are reliable. This makes visibility into behaviour and ongoing guidance essential.
AI adoption is also a governance challenge. When employees lack confidence in enterprise AI tools, they often turn to external or unapproved alternatives to complete their work. This can expose sensitive data, create inconsistent outputs, and introduce regulatory risk. Ensuring employees understand when, where, and how to use AI within approved workflows helps organizations maintain visibility, reduce shadow AI usage, and apply governance consistently across the workforce.
IT leaders can use tools like AI Drive to centralize AI visibility, usage, guidance, and measurement into a single vantage point. This provides a complete picture of how employees are interacting with AI, where adoption is strong, and where support may be needed, enabling leaders to act proactively rather than reactively.
Successful AI adoption requires leaders to guide employees through change, ensuring they understand not only how to use AI, but why, when, and where it adds value in their workflows.
Without this guidance, employees may hesitate to engage, struggle with outputs, or abandon tools altogether. This can lead to shadow AI usage, compliance violations, inconsistent work, and lost productivity. In other words, failing to actively manage the human side of AI adoption undermines the technology itself and exposes the organization to operational, regulatory, and financial risk.
Start by building visibility into how employees are interacting with AI tools, identifying where adoption stalls, and embedding guidance into workflows. Prevention starts at the moment of deployment, not after frustration occurs.
Traditional training can’t keep up with rapidly evolving AI tools. Effective guidance is contextual, timely, and integrated into the workflow, providing support exactly when employees need it, empowering them to build confidence and maintain adoption over time (Learn more).