Upward arrow drawn over wooden building blocks

Alongside myriad advantages, AI presents businesses with a range of challenges surrounding cyber security, data governance, and cross-functional implementation. Skilled professionals executing an informed strategy can mitigate most of these concerns. But ongoing tech talent shortages and a general lack of AI expertise in the workplace have left businesses struggling to maximize their ROI in AI systems.

Only 22% of organizations feel highly (or very highly) prepared to address talent concerns related to generative AI adoption. For the rest, cultivating expertise internally could be key to navigating the new, AI-powered business landscape. Providing employees with opportunities to upgrade their skills is often a cost-effective means for org leaders to close workforce skill gaps while maintaining a sense of org-wide continuity.

When designing a successful reskilling or upskilling initiative, accounting for the needs and preferences of participants is essential. Broad mandates and rigorous training schedules could be met with resistance from a workforce already grappling with significant changes to its standard processes. By offering flexible, goal-oriented training that addresses individual and departmental needs, businesses can improve employee buy-in while fostering productivity and innovation in the era of AI.

Defining big-picture training goals

Only 24% of companies draw a clear connection between skill-building efforts and corporate strategy. Failing to provide context for employee training may undermine reskilling and upskilling initiatives—and contribute to confusion and resistance among the workforce. This is especially risky at a time when 75% of org leaders are anticipating high employee churn as a result of AI adoption.

Defining broad objectives for the company's AI implementation can help set the tone for a purposeful and results-driven skill-building initiative. In addition, taking the time to show employees how they fit into the company's long-term plans can allay concerns over AI-related job displacement, making teams more receptive to new technology. A marketing manager, for example, may be more eager to deploy AI during the brainstorming process once they recognize the opportunity to focus on the more creative and fulfilling aspects of their job. A sales agent may be more willing to offload CRM data entry to their AI tool, when they see how this move allows more time for lead engagement.

When the full organization is working toward a common goal, businesses can expect less friction along the way, and more unified efforts to overcome roadblocks as they arise. Sharing broad strategies with employees, whether informally or through scheduled meetings, is often a powerful step toward achieving buy-in, both for organizational goals and the training required to achieve them.

Shaping programs around employee learning styles

Redefining the way employees perform their roles (and the technology they use to do so) can be time consuming—and at worst—disruptive to job performance. To build support for reskilling and upskilling, and optimize the results of their initiatives, businesses must design programs that take employee needs and preferences into account.

Most employees prefer to learn on the job, and could benefit from a less formalized approach to skill building. When equipped with self-service training resources, employees can troubleshoot challenges as they arise without detracting from productivity. However, due to the complexity of a large-scale tech implementation, self-service will likely need to be supplemented by some form of live training. To combine flexibility with in-depth exploration, organizations may need to consider assigning mentors or coaches to help employees navigate unfamiliar tech territory, either virtually or in-person.

A more formalized approach to reskilling usually requires a greater investment of time and other resources—but the trackability it offers can be a compelling advantage. A structured option, such as an online course, makes it easier to identify areas where individuals excel or struggle. Based on that information, team leaders can assess whether each participant is enrolled in a suitable training track and make adjustments as necessary. Further, a more formal approach helps businesses optimize their programs by determining whether the most crucial information is being effectively conveyed to the majority of participants. One person struggling with adoption is an individual issue. An entire team or department struggling with adoption is a systemic issue that should be addressed in a systemic way.

Assessing program impacts

A relevant and well-planned training program can have a powerful impact on employee engagement and even longevity with the company. By collecting employee feedback, leadership can gain a more precise understanding of how AI can best augment each role, and support various talents and skill sets. Once the program is implemented, org leaders should continue to check in with participants to ensure that their training is sufficiently comprehensive and applicable to the actual responsibilities of the job.

Employers can also benefit from monitoring the broader impacts of their reskilling initiatives on the organization as a whole. To prepare for this process, org leaders should consider meeting before their program launches, setting benchmarks for success, and determining how KPIs will be measured.

Routinely monitoring key program metrics will give employers a sense of how well their programs are preparing employees for the realities of the job, and how the training is being received by those enrolled. This way, businesses can quickly identify opportunities for greater program optimization, ensuring that both employees and the company as a whole are getting as much as possible from their reskilling and upskilling initiatives.

Supporting org-wide growth

Adopting technology at different rates, and to different degrees, across an organization often causes collaboration and consistency to suffer. In order to standardize processes and set appropriate quality benchmarks, organizations must ensure that all teams are equipped with the necessary resources, capabilities, and expertise.

Reskilling and upskilling help put all members of an organization on equal footing, so that each team can use AI to its full potential. In addition to maximizing ROI, this helps ensure that all departments are representing the organization and its goals in a unified way, leading to smoother operations, more fluid communications, and ultimately, more successful AI adoptions.

 


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