Why IT Leaders Must Rethink AI Deployments for Flexible Work

As organizations debate about the future of work and whether employees should return to offices, stay remote, or settle into hybrid models, one factor remains non-negotiable: Technology must adapt to people, not the other way around. Flexible work environments thrive only when tools empower employees to do their best work seamlessly, regardless of location. AI, with its rapid growth and potential, promises to be the great enabler of this future. Making this a reality, however, is more complicated.

Many IT leaders are eager to declare AI deployments a success, while employees often tell a different story. A recent study from GoTo shows that 91% of IT leaders believe their organizations are using AI effectively in flexible work models, yet only 53% of employees agree. This disconnect represents more than just a perception problem. It potentially reflects wasted investments, underutilized tools, and a growing risk that employees could view AI as a burden rather than a benefit.

For AI to truly deliver on its potential, IT leaders must rethink their approach to deployment. Rather than rolling out new solutions driven by speed or novelty, the emphasis should be on empowering employees, solving specific pain points, and building trust in the technology. Successful AI in flexible work is not about adopting more tools, it is about deploying the right ones in the right way with people at the center.

The Promise and Pitfalls of AI in Flexible Work

Employees across functions now rely on AI for tasks ranging from scheduling meetings to automating service requests to enhancing collaboration. When applied well, AI can reduce friction, streamline processes, and take away tools including manual and repetitive tasks to ultimately enable employees to focus on higher-value work.

For example, Generative AI-driven service desks can potentially help answer questions and resolve routine issues instantly, freeing up both employees and IT teams. Similarly, AI-enhanced remote support tools can ensure that technicians benefit from expert knowledge or remediation solutions derived from automated session summaries, also improving the experience for employees regardless of where they are working from.  For organizations juggling the complexity of hybrid and remote setups, these tools can act as connective tissue, ensuring no employee feels left behind regardless of location.

Yet the pitfalls are equally real. Training is often limited or delivered as a one-time activity, which can make it challenging for employees to use AI tools effectively. When tools fall short of expectations or introduce new challenges, trust in AI can diminish. This creates a gap between leaders’ optimism and employees’ day-to-day experience.

Rethinking Deployment: A Roadmap for IT Leaders

Closing this gap requires a shift in mindset. AI should not be viewed as a technology rollout alone, but as a people-inclusive change initiative. IT leaders must champion a deployment approach that prioritizes usability, learning, and problem-solving. Below are three strategies to help make this shift a reality.

1. Upskill Employees with Regular, Outcome-Informed Training

Training is often the first casualty of fast AI adoption. Many organizations announce a new AI tool, hold a single onboarding session, and assume employees will figure out the rest. AI is still a relatively nascent and sophisticated technology, however, and demands ongoing, adaptive learning. This is especially important for flexible working environments, where employees may not be surrounded by others they can learn from in terms of using AI effectively.

Instead of one-size-fits-all training, IT leaders should implement continuous programs that focus on outcomes. Employees need to see how AI helps them save time, reduce frustration, or achieve goals that matter in their specific roles. For instance, a sales team might benefit from AI that accelerates proposal writing, while customer support staff might need training on using chatbots that triage service requests.

By tailoring training to outcomes, IT leaders boost adoption and build confidence in AI. The more employees trust the tools, the more they will experiment and uncover new use cases for themselves.

2. Provide Guidance on Optimal Use Cases to Encourage Experimentation

While some employees may embrace AI naturally, many hesitate to use tools without clear guidance. Fear of misusing AI or being replaced by the technology can stifle creativity. IT leaders have a critical role in framing AI as an assistant that works in concert with employees rather than a threat.

This means actively promoting specific, high-value use cases. For example, an IT team might showcase how AI helps resolve password resets instantly or how a meeting assistant can generate accurate summaries for absent colleagues. By spotlighting these wins, leaders normalize AI use and encourage employees to test the technology in low-risk situations.

Experimentation is key. Flexible work environments are dynamic, and employees are often best positioned to identify pain points that AI can solve. By fostering a culture of exploration with clear boundaries around responsible use, organizations can unlock innovation from the bottom up.

3. Design Robust Troubleshooting Systems to Tackle Implementation Challenges

Even the best-engineered AI tools can occasionally make mistakes. What matters is how quickly and effectively organizations respond when they do. Without strong troubleshooting systems, employee frustration mounts and adoption stalls.

IT leaders must ensure that support for AI is as seamless as the tools themselves. This could mean building dedicated support capabilities for AI-related issues, incorporating AI diagnostics into existing help desks, or assigning champions within departments who can assist peers. The goal is to remove friction swiftly, so employees see problems as temporary setbacks rather than reasons to abandon the tool altogether.

Troubleshooting should go beyond fixing issues. It should generate feedback loops that inform future deployments. If employees consistently report that a chatbot struggles with certain requests, IT leaders should use that insight to refine both the tool and the training that accompanies it.

Building Trust in AI

At its core, successful AI deployment is about trust and active usage. Employees must believe that AI is here to support them, not replace them. They must feel confident that the tools are reliable, secure, and aligned with their needs. Encouragingly, recent research shows that nearly all employees (95%) and IT leaders (92%) support their company’s current investment in AI tools or feel their company should be investing more. This enthusiasm is a strong foundation, but it can be undermined if deployment is poorly executed or if employees struggle to see the value in day-to-day use.

Trust is built deliberately through transparency and responsiveness. IT leaders should communicate openly about what AI can and cannot do, the data it uses, and the safeguards in place to protect privacy. Leaders should also listen to employees’ concerns and act on them. When workers see that their feedback shapes deployment decisions, they become partners in the process rather than passive participants.

From Hype to Real Impact

The excitement around AI is undeniable, but hype alone will not transform workplaces. In fact, 62% of employees feel AI has been significantly overhyped. This underscores the importance of focusing on real impact, how AI tangibly improves productivity, connection, and employee satisfaction in flexible work models.

By rethinking deployment with a people-inclusive mindset, IT leaders can close the gap between perception and reality. That means committing to ongoing training, providing clear guidance on use cases, and creating robust support systems. Most importantly, it means designing AI rollouts that respect the needs and experiences of employees.

Organizations that embrace this approach will not only maximize the value of their AI investments but also create flexible work environments where employees feel empowered and supported.  Thoughtful AI implementation is key to shaping a more productive and connected workplace of the future.