Editorial
We all know or have heard that AI, including generative AI, is reshaping how we learn, develop and work. According to research by Accenture, 97% of global leaders see generative AI as a game-changer for their companies and industries. Because of its prevalence, leaders know they need to implement AI now or risk falling behind. However, they don’t always know how to integrate AI into their organization or where to start.
At the same time, many leaders realize that they’re sitting on talent gold within their organizations but don’t know how to tap into it. While leaders have talked about tapping into employee skills for years, technology hasn’t kept up.
As AI implementation remains a C-suite priority, leaders across the business are experimenting with new ways to incorporate AI to supercharge growth and productivity. One of the use cases leaders are prioritizing is leveraging AI for skills-based learning and development to create more personalized, on-demand learning that better aligns to employee, business and workforce needs.
If organizations want to implement AI for workforce development and reap the benefits, there are three key things they need: leadership buy-in, technology and AI governance for learning and development.
1. Leadership Buy-in
Before investing in any new solution, leaders must be bought into the idea. They will want to know what AI will bring to the table, in terms of skills-based talent acquisition, learning and development and how it’ll benefit the business: Will AI suggest high-potential individuals for new roles? Notify leaders of skills gaps? Proactively suggest learning opportunities for teams? Predict future roles required to grow as a company? Providing clear answers to their questions — and clearly articulating the business value — is key for earning leaders' trust and gaining their full support.
Many leaders also have concerns about AI taking away decision making from humans, which may make them less likely to implement the technology. The reality is AI will augment and automate work, while creating new jobs, so employees can focus on projects that are higher value and fundamentally human. AI enhances rather than replaces human decision making by offering data-driven insights and recommendations. A great way to make AI easier to understand is by pointing out how it’s already being used in our daily lives.
Take Netflix, for instance. The streaming service uses AI to analyze what we watch, what we like and what we rate highly. Then, based on all that info, it suggests other shows and movies we may enjoy. But here's the thing: Netflix doesn't force us to watch anything. It just gives suggestions, and ultimately, we're the ones who decide what to watch. In the same way, AI for workforce development is like having a helpful assistant offering suggestions (e.g. new trainings, certificates or roles), but the final call always rests with employees and their managers.
2. Technology
Once you have leadership buy-in, here comes the tactical part: technology. The most important thing to keep in mind when implementing AI skills technology is to start small, iterate and let AI fine-tune over time. Instead of attempting extensive overhauls all at once, organizations should focus on manageable interventions to minimize risks and achieve quicker wins.
One way to start is leveraging AI with existing resources. For example, an organization can look at implementing AI within an existing course catalog to focus on recommending related courses based on an employee’s goals and skills. Starting with these smaller initiatives allows organizations to address immediate pain points and demonstrate the value of AI without overwhelming their workforce.
Starting small also allows organizations to gather feedback and insights for ongoing refinement. Through iterative cycles of implementation, feedback collection and adjustment, companies can continuously improve their AI initiatives. This iterative approach ensures that AI technology evolves in line with employee feedback, leading to more effective and impactful solutions over time.
3. AI Governance for Learning and Development
When crafting an AI governance framework for workforce development strategies, organizations must ensure that AI learning recommendations are transparent and aligned with organizational objectives. For example, AI can analyze employee performance data and goals and recommend personalized training courses or development opportunities to help them achieve their aspirations. However, it's essential to communicate clearly to employees that these recommendations are meant to enhance their learning experience and growth, rather than dictate their career paths.
This is where managers play a critical role in interpreting AI recommendations and guiding employees' learning journeys. For instance, if AI suggests a particular training program for an employee, the manager can review the recommendation, consider the employee's career goals and performance and weigh additional context that supports their decision making, such as one-on-one growth conversations. By involving managers in the process, organizations can ensure that AI recommendations contribute to employee professional development effectively and align with personal conversations and goals.
Webinar
Sep
25
CMS Briefing: A Live Look at What’s Next in AI-Driven Platforms
Learn how leading organizations are using AI‑driven tools to publish faster, personalize smarter and stay secure.
Register
Webinar
On demand
Ready or Not: How Data-First Organizations Are Unlocking Agentforce Potential
Learn how to cut through the noise, activate Agentforce and build a Salesforce AI strategy that actually delivers.
Watch Now
Webinar
On demand
AI in Customer Service: Faster Resolutions, Happier Customers
Don’t let rising demand burn out your team. See how to build a smarter, more resilient support org.
Watch Now
Webinar
On demand
From Hype to High-Impact CX Strategies That Actually Scale
Turn buzzworthy AI and outsourcing trends into measurable CX wins with fresh 2025 data.
Watch Now
Webinar
On demand
Insights to Action Rethinking the Contact Center for Real Business Impact
Join our exclusive webinar to hear CX executives share their innovative strategies for transforming service delivery.
Watch Now
Webinar
On demand
Accelerating Healthcare Ops with AI
Sign up to see how your peers are putting AI to work — and making it stick.
Watch Now
Lastly, ensuring the privacy and security of employee data is a must in AI-driven workforce development initiatives. Organizations can showcase their dedication to safeguarding data by implementing rigorous security protocols and access controls within their learning platforms. For example, AI algorithms can analyze training data to pinpoint skill gaps and recommend relevant courses, while ensuring that confidential information remains securely stored within the organization's internal data infrastructure.
By addressing these key considerations — leadership buy-in, technology and AI governance for learning and development — organizations can tap into the full potential of AI in workforce development, driving innovation, engagement, growth and most importantly, unlocking human potential.
Learn how you can join our contributor community.
