How to empower employees to engage with AI

Many jobs involve repetitive tasks that AI agents can effectively manage at scale, but implications for workers will differ. For some, automated customer support tools are a godsend. AI agents quickly respond online to those needing basic information. They triage inquiries to more efficiently provide human support and help service representatives find key information or next best actions; rapidly scan and evaluate invoices to avoid payment or policy errors, allowing managers to focus on contract negotiation instead of rote processing; help developers code more efficiently with fewer errors; and enable data scientists to make discoveries more quickly and reliably.

Will AI agents completely handle customer support, negotiate contracts, and perform software engineering in the next decade? Fifty-six percent of U.S. employees surveyed in 2024 indicated they expect automation to change their work considerably (IDC’s 2024 U.S. Employee Experience Survey). Thirty-one percent of IT and LOB leaders IDC asked about how GenAI will disrupt job roles identified impacts on product design and development practices and shifts in expectations of how data-leveraging decisions would be made (IDC FERS, Wave 10, 2025).

AI automation will reshape common job roles to emphasize critical thinking, enabling faster and more accurate work completion and identifying better ways to build business or engineering processes.

Teams largely welcome repetitive task automation when proper communication and training accompany its rollout. Issues arise when organizations fail to properly explain the adoption of new AI-enabled applications or disclose strategies for the long-term evolution of functional roles and individual responsibilities.

Tip for Success: Disclose a long-term AI strategy for evolving functional roles and responsibilities.

Globally, organizations lack employees with highly developed technical and human skills. In many cases, the trope that nobody does the job they went to school for is true. IDC predicts that AI-enabled work models will replace or redefine 95% of current IT and LOB roles by 2030 (IDC FutureScape: Worldwide Future of Work 2025 Predictions). Inevitably, IT must collaborate more deeply with HR, operations, and LOB as support and security protocols change. Leaders from the C-suite to first-line managers must adapt to guide their teams through strategic shifts in development, go-to-market strategy, governance, and flexible work guidelines. Employees expect experiential learning and on-the-job training, but traditional teaching methods cannot keep pace with the rapid technological shifts.

To overcome concerns about job change and loss, organizations must embed skills development into their AI-enabled business growth strategies. IDC has found that although one-quarter to one-third of IT leaders have extensively engaged AI copilots, assistants, and/or agents, IT skills shortages keep them from using these solutions ubiquitously (IDC’s 2024 FoW Predictions Report). Employees seek upskilling and cross-skilling with clear career development pathways, not just short-term job security. Employers must appreciate and utilize employees’ expertise to build a culture of learning that drives competitive growth. Organizations should budget for ongoing skills assessments and development tools to ensure the successful deployment of AI-enabled apps and speed to expertise in new job roles, including executive management. Organizations must pivot from "one and done" teaching models to AI-enabled learning across workflows and platforms. They can do this in-house and alongside third-party partners.

Tip for Success: Ensure skills development for employee and business growth.

Alongside faster and more effective onboarding using automation for badging, laptop configuration, and HR registration processes, the current AI era brings confusion with new tools, work policies, and reporting structures. Amid this disruption, defining success by measuring productivity alone will inevitably cannibalize organizational culture. IDC predicts that by 2027, 60% of G1000 will use AI to create new metrics from collaboration, integrated applications and behaviors, linking them to business outcomes not currently measured. In the rush to measure how much efficiency can be driven with AI, organizations mustn't lose sight of how they will measure competitive growth through innovation. How quickly will employees be able to learn new skills that not only drive productivity but drive product or service innovation? Rushing to drive efficiency with AI, organizations mustn't lose sight of how they will measure competitive growth through innovation. How quickly can employees learn skills that drive product or service innovation alongside productivity?

For AI adoption to succeed, employees must feel both valued and valuable, not just for the short-term transition to AI-enabled ways of working but for their organizations’ longer-term growth. Some balance sheet measures will endure, but AI-enabled systems offer far more sophisticated means of evaluating the long-term systemic impact of technology adoption and new work practices. Organizations should also ensure metrics such as the voice of the employee are not isolated to HR.

In terms of where, how, and with what devices employees and their leaders work, 2025 will be a pivotal year. For AI adoption to succeed, leaders must demonstrate to their employees how these technologies will both increase their productivity and engage them in building future working practices.