As AI continues to progress, boosting productivity and efficiencies, organizations are actively looking for ways to equip their workforce with the skills and confidence to navigate the disruption. However, despite its growing importance, many employees remain hesitant. An Adecco survey reveals that only 25% of workers globally have received AI training and out of those who have — 75% report feeling unprepared to leverage the technology despite the training they have received.
This executive brief offers expert insights on overcoming AI adoption challenges through strategically designed training, scaling efforts, identifying roadblocks, and measuring success. With the right planning, organizations can empower employees to fully embrace AI as a valuable asset in their day-to-day responsibilities.
This roundtable was held on January 23, 2025
Overcoming Roadblocks & Designing Effective Onboarding Programs for AI Adoption
1. Communication
Convince instead of command — It’s important to create excitement among the workforce through engaging communications around AI. Simplify your messaging and relay objectives clearly to help shift employee skepticism. Share tips and examples of practical use cases or hold talks to let employees engage and ask questions directly.
For example, with the market sentiment on Microsoft CoPilot being that it is ‘not as good’, at times many companies face challenges in communicating the productivity benefits of the tool vs. the more popular ChatGPT. Establish the 3Ws when introducing a new tool for adoption — in this case, highlight the channels where employees are working (e.g., dropbox, SharePoint, etc.), what kind of work they are doing, and why AI is needed to assist with their job.
2. Training Modules
While generic AI training can help build foundational AI skills, it is too broad to be effective. Training programs should be differentiated for different roles and functions across the organization. In addition, the training modules should not be focused on technical skills, especially at the start. For example, it’s best to avoid going straight into security training right at the beginning as this will lead to employees being hesitant to proactively try and experiment with the technology.
Instead, include non-AI related skill building that will be useful when adopting AI. For instance, a course on structured problem solving will allow employees to systematically identify the source of their problem (question), the best way to solve it (instruction), and what to ask from AI to gain more accurate insights.
3. Resources and Tools
Make AI easier for employees to use. Go beyond surface-level onboarding to teach them how to ask the right questions when using AI tools. Offer structured resources on key aspects such as prompt-building techniques and how to frame queries effectively to achieve desired outcomes. Role-specific examples of prompts can help employees better understand AI’s capabilities and apply them meaningfully in their functions.
Tips: Train AI on how to think and communicate with you. This is similar to guiding a new intern — it doesn’t know everything upfront and requires clear instructions to deliver the desired outcomes. Specify the exact results needed and provide step-by-step guidance to help it meet their expectations.
4. Engagement & Motivation
Employees often feel threatened by AI — not just by the fear of replacement but by colleagues who are already more skilled in utilizing AI to stay ahead of the curve, leaving others behind. Use this to your advantage to create healthy competition and motivate employees to engage with the technology. Overcomplicating AI often ends up intimidating employees. Emphasize that AI is just another technological tool to help with an organization’s productivity not some villain with evil plans. Leaders also need to actively push back resistance by encouraging the workforce to consult with AI first for any work-related questions before going to others.
Some employees perceive retraining as a disruption to their workflow, especially when it involves tasks they can already perform quickly, like creating a pivot table. However, the key is to show AI’s practical values and how it can make these tasks more efficient in the long run. For example, summarizing key points from a document as a pre-read for meetings or shortening the time needed to look up certain internal information; empowering employees to focus on higher-priority tasks; saving time, reducing errors, freeing up space for higher-value work, and maintaining a competitive edge. By demonstrating how AI can streamline these processes, employees will see that investing a little time upfront for training can lead to much greater productivity down the road.
4 Ways to Scale AI Training & Leverage Champions to Drive Success
1. AI Readiness & Segmentation
Customize AI training to different roles and levels of readiness within the organization. For instance, media-focused teams might benefit from training on ad activation and social network insights, while senior stakeholders and middle managers require more strategic AI guidance. Take people through different levels of training and let them advance through the stages. Segmenting training ensures that content is relevant and actionable, meeting the employees where they are in their AI journey.
2. Develop a Comprehensive Strategy
Training, championing, and change management are interconnected — tackle them together for a smooth AI adoption. Without a solid change management plan, even the best training program can fall short, affecting rollout and engagement. Celebrate wins to fuel excitement and reinforce the long-term value of AI. Build demand and scale by creating a journey with onboarding and offboarding points, with training materials that evolve. Start with basic user knowledge, then let employees progress into buddy users who share knowledge through casual content around AI, e.g., in lunch & learn sessions. As you cultivate more champions, you can scale training modules and continue driving AI success.
3. Build Specialized & Dedicated Support
Create a specialized support function that can address both complex and simple AI-related issues. Whether it’s troubleshooting product integrations or helping with everyday use cases, having a dedicated team ensures employees aren’t left in the dark. This focused support empowers users to overcome obstacles quickly, boosting confidence, and driving consistent AI adoption across the organization.
4. Empower Champions & Opinion Leaders
Empower credible opinion leaders who understand the unique challenges within their functions to champion AI adoption and be the go-to people to provide support. These influencers can showcase practical AI applications, help address pain points, identify opportunities, and spark people's interest organically, you do not need to call them champions. Another effective approach is sharing ‘Day in the Life..’ content — demonstrating real, relatable AI use cases from someone within the organization to inspire broader adoption and share best practices across teams.
Measuring & Tracking AI Success
A focused, data-driven approach ensures organizations capture AI’s value and continuously optimize adoption strategies. On top of measuring hours saved or employee sentiment, you can track:
Usage Metrics: Monitor daily, weekly, and monthly engagement, number of applications used, and depth of adoption beyond basic tasks.
Productivity Indicators: Evaluate engineering outputs. For example, via GitHub contributions and production metrics.
Token & Query Analysis: Track query volumes to identify AI usage trends across specific topics or tasks.
Business Impact: Document tangible outcomes like improved activity completion and specific AI-driven success stories.
Conclusion
Equipping your workforce for AI success requires strategic approaches that combine clear communication, tailored training, active support from AI champions, and scalable training solutions. Proactively addressing potential roadblocks will help motivate and empower employees to adopt and experiment with the technology to enhance their productivity and drive meaningful transformations for the organization.
The Executive Council for Leading Change
The Executive Council for Leading Change (ECLC) is a global organization that brings executives together to redefine the landscape of organizational change and transformation. Our council aims to advance strategic leadership expertise in the realm of corporate change by connecting visionary leaders. It’s a place where leaders responsible for significant change initiatives can collaborate, plan, and create practical solutions for intricate challenges in leading large organizations through major shifts.
In a world where change is constant, we recognize its crucial role in driving business success. ECLC’s mission is to create a community where leaders can excel in guiding their organizations through these dynamic times.
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