How Workforce Development Strategies Can Accelerate AI Adoption

With its potential to transform businesses by improving efficiency, uncovering new insights and driving innovation, organizations everywhere are eager to adopt artificial intelligence (AI) initiatives. However, many businesses that have already begun investing in AI to support their daily operations may be finding that adopting AI is not an “easy button” to modernization.

Without a comprehensive plan for adoption, many organizations struggle to find the real value of AI in their everyday work. So, what’s the best way to reap the benefits of this new technology while ensuring that your teams are maximizing the value of your AI investments? It all comes down to creating a strong foundation for AI implementation across teams through comprehensive technology training strategies.

Training is key to getting the full value from any technology or initiative, sparking faster ROI, improved engagement outcomes and long-term project success. In fact, organizations with comprehensive training programs report 218% higher revenue per employee than those without (Association of Talent Development).

Leading with hands-on instruction and targeted training initiatives, organizations who take the time to holistically grow their teams will see faster, more successful AI adoption rates, empowering team members to produce better business outcomes in the process.

Whether your organization is prepared for it or not, teams and individuals have begun using AI in their everyday work, but adoption rates and effectiveness remain inconsistent across organizations.

A few of the top roadblocks to AI adoption include:

1.    Disparate adoption across teams: AI adoption often occurs in silos where individual departments experiment with tools based on their specific job functions. While this localized usage can yield small wins, it rarely results in the broad integration required to unlock AI’s full potential. Instead, these "islands of adoption” can impede seamless collaboration and business alignment.

2.    Lack of directed change management: Change management issues frequently derail AI initiatives. A mere introduction of AI tools without a structured plan to encourage adoption leads to confusion and resistance. Organizational change demands deliberate planning, from identifying team champions to outlining ways that AI aligns with day-to-day operations.

3.    Training and skills gaps: The most significant barrier to AI adoption is a lack of training. Investing in AI tools without equipping your workforce to use them effectively is a recipe for underperformance. Too often, businesses face disillusioned employees who are unable to integrate AI into their daily workflows. This leads to wasted investments and missed opportunities for operational improvement.

Overcoming barriers like these means implementing strategies that prioritize your organization’s people, processes and technology. A well-trained, empowered workforce is central to a successful AI adoption process. According to a recent report, though the percentage of workers using artificial intelligence tools rose from 8% in 2023 to 35% by the end of 2024, only 31% of workers indicated that their employer provided AI training. At the same time, 59% of learners enrolled in AI training reported at least weekly use.

Despite a sharp increase in roles demanding AI skills, a recent survey found that only 13% of employees received any AI training in the past year, yet 74% of workers expressed interest in upskilling. Among those who haven't adopted AI, 32% cited lack of training as a barrier.

By enabling team members to acquire the skills they need to adapt to evolving technologies through structured learning programs, organizations will be better positioned to maximize the value of their AI investments. When building an AI-focused learning program, consider these best practices:

Rather than approaching AI as a one-off purchase, it’s important to begin your journey by aligning AI adoption to your long-term business objectives. Effective training programs help teams understand not only how to use tools but why those tools are essential to their success.

Organizations should start by mapping out ways in which AI solutions align with their broader goals. Define the specific outcomes the team hopes to achieve. Are you hoping to use AI to automate repetitive tasks? Optimize production workflows? Rather than determining how to build new processes around an AI tool, start by determining how that AI tool can help you achieve your current goals.

Successful AI adoption requires collaboration across sometimes disparate departments. Before purchasing or implementing a tool, leaders should first outline clear expectations, define responsibilities, and create a feedback loop that aligns AI tool usage across teams.

At the same time, employee training shouldn't necessarily follow a one-size-fits-all approach. Instead, determine how best to tailor individualized learning paths with different teams and tasks.

Teams entirely new to AI, for example, may benefit from foundation courses such as CDW’s AI for Business Users, which breaks down the basics and emphasizes practical application. For teams exploring generative AI, courses like our Prompt Engineering for Business Users help demonstrate ways to derive value from generative AI tools in daily operations.

Organizations scaling operations with AI may want to invest in more specialized training like MLOps and AI Security or in tools specific to their ecosystems, like Designing and Implementing Microsoft Azure AI Solutions.

Though there is value in one-off e-learning training as supplemental support for small-scale skillsets in your training initiative, there is no substitute for instructor-led courses featuring hands-on labs and demonstrations.

Whether delivered in-person or virtually, instructor-led courses are designed to instill AI skillsets in your teams and help them apply those skills within their work. A quality course will be informed by the instructor’s real-world experience to help your team achieve its specific goals, rather than a how-to manual focused on one simple tool. With lessons built around specific job functions and opportunities for learners to receive immediate feedback, instructor-led courses are the key to successful adoption.

Self-paced, on-demand courses can also be valuable as a supplement to live, instructor-led training. If a member of your team is finding it difficult to remember the steps required to deploy containers in Azure AI, for example, a brief, five minute training video may provide the just-in-time assistance they need to complete their task. 

Often, the success of employee training hinges on its relevance to your teams. Navigating organizational shifts when implementing transformational technology like AI requires expertise and close collaboration from discovery to execution. A well-designed training strategy will involve expert partnerships in both the discovery phase — when diagnosing gaps and identifying needs — as well as during the execution phase when implementing a customized training program.

Engaging with an expert partner like CDW from the beginning of your technology training journey means having a trusted collaborator throughout the process, from addressing common adoption challenges to building thoughtful training programs, developing an AI-focused curriculum and setting benchmarks to measure the success of your organization’s AI adoption.

With more than a dozen AI-focused courses available, CDW’s technology training experts can customize a high-impact training program at any stage of your technology training journey, tailoring your resources to align with your adoption timeframe, user groups and team objectives. From there, our teams will also help measure the success of your organization’s AI adoption with statistics around productivity improvements, reductions in manual errors or increases in AI usage rates.

AI adoption accelerates when businesses prioritize tailored training programs. The right training programs provide not only skills but also confidence, encouraging employees to integrate tools more effectively. By investing in your team, you don't just adopt AI; you foster a culture of innovation.