5 steps to create an AI-savvy workforce

AI is reshaping how work gets done. Many People leaders wonder if their teams are ready to make the most of it. For most organizations, the path forward lies in strategic upskilling. 

Here's how to take your team from curiosity to capability in using AI:

1. Understand your team's AI baseline

The first step is understanding where your team stands. What do they know about AI? Are they using tools like ChatGPT or automation in their roles? Gather input through surveys or focus groups to uncover how AI is currently being used. This will give you a clear starting point.

Objectives:

• Gain a clear picture of your team’s current AI knowledge, usage and comfort levels.
• Identify gaps in understanding and potential areas for development.

Actions:

• Conduct surveys to assess familiarity with AI tools and concepts.
• Hold focus groups to explore how team members are experimenting with AI in their work.
• Review current AI-related processes or tools already in use within the organization.

Additional considerations:

• Segment findings by department or role to tailor upskilling programs.
• Use baseline insights to set realistic AI training goals.

2. Spot opportunities for AI integration

AI is most effective when applied to the right problems. Identify tasks that are repetitive, data-driven or require rapid analysis. Marketing teams might use AI for content creation, while HR could explore tools for resume screening or employee engagement. Pinpointing these areas helps direct your team’s learning.

Objectives:

• Identify where AI can deliver the most value in your organization.
• Prioritize tasks and processes where AI can save time, reduce errors or improve outcomes.

Actions:

• Map out workflows across teams to find repetitive or data-heavy tasks.
• Collaborate with department leaders to pinpoint processes ripe for automation or augmentation.
• Research AI tools that align with your team’s specific needs, such as content creation or data analysis.

Additional considerations:

• Focus on high-impact opportunities that will showcase clear benefits.
• Involve employees in identifying pain points or inefficiencies they experience.

3. Establish a culture of AI experimentation

Encourage your team to test AI tools without fear of failure. Share small successes and stories of how others have used AI effectively. Create an environment where exploring new tools is seen as part of the process, not a risky endeavor.

Objectives:

• Foster an environment where employees feel comfortable exploring AI tools and processes.
• Encourage innovation and learning through experimentation.

Actions:

• Highlight examples of successful AI implementation within your organization or industry.
• Provide safe spaces for employees to test new tools without performance pressure.
• Recognize and share lessons learned from both successes and failures.

Additional considerations:

• Create informal learning groups or AI champions to drive peer-to-peer sharing.
• Offer incentives for innovative AI use, such as internal awards or showcasing team achievements.

4. Build strategy into AI skill development

Experimentation is useful, but it’s more effective when guided by a strategy. Align AI training with organizational goals. For instance, if improving customer service is a priority, focus on tools that enhance responsiveness and personalization. A strategic approach keeps learning relevant and impactful.

Key components of an AI upskilling program

Effective upskilling focuses on three areas:

• Foundational knowledge: Ensure your team understands the basics of AI and its limitations.
• Practical application: Train employees on tools and workflows relevant to their roles.
• Ethical considerations: Help your team navigate responsible AI use, avoiding issues like bias and privacy violations.
• On-demand resources: Offer ongoing access to tutorials, toolkits and expert guidance to support continuous learning.
• Regular refresher sessions: Keep the team up-to-date on evolving AI technologies and best practices.

5. Measure the impact of AI readiness

Once your team begins applying AI, track the results. Are processes becoming faster? Is productivity improving? Use metrics aligned with your goals to assess progress and adjust your approach as needed.

Objectives:

• Evaluate the effectiveness of your team’s AI training and application efforts.
• Identify measurable improvements in productivity, efficiency or other key metrics.

Actions:

• Define specific KPIs tied to your AI goals, such as time saved on repetitive tasks or increased output quality.
• Monitor performance metrics before and after implementing AI tools.
• Gather qualitative feedback from employees on how AI has impacted their workflows.

Additional considerations:

• Conduct regular reviews to ensure alignment between AI use and organizational goals.
• Share results with stakeholders to build support for continued AI initiatives.
• Use findings to refine training programs and address any gaps or challenges.

Next step: AI readiness training with Electives

Developing an AI-savvy workforce takes more than experimentation — it requires a structured, tailored approach. Electives provides live, instructor-led AI readiness training designed to help your team confidently integrate AI into their daily work. With programs customized to your organization's needs, you can start seeing measurable outcomes quickly.

Our AI readiness training covers critical skills and strategies, including:

• Prompt engineering: Create effective prompts for better AI results.
• AI-driven workflows: Seamlessly incorporate AI into everyday operations.
• Ethics + bias: Address ethical challenges and minimize bias in AI use.
• Productivity + creativity: Use AI to streamline tasks, enhance collaboration and inspire innovation.

Don’t leave your team’s readiness to chance — partner with Electives to equip your organization for an AI-driven future.

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