Making AI Skills Accessible Through Learning and Digital Badges

What is AI Democratization?

AI capabilities have emerged as a vital business competency. Nearly 9 out of 10 IT leaders surveyed by Rackspace in a global study said their organizations were benefiting from AI. But those leaders also worry that AI skill gaps could stall progress. The solution lies in making AI skills learning widespread within an organization—what we refer to as AI democratization. This approach ensures that the technology is accessible to and utilized by the broadest range of employees.

Widespread access is key to unlocking AI’s potential to boost productivity and accelerate innovation:

Increased productivity & efficiency

by reducing time spent on repetitive and routine tasks

Enhanced innovation and creativity

because employees have time — and new tools — for innovation.

Greater workforce engagement

as training in AI skills makes employees feel valued and secure, reducing employee turnover.

Accelerated Upskilling and Career Growth

by creating continuous learning opportunities and empowering employees to grow their skills and advance in their careers.

Differentiation in the market

as widespread AI adoption enables businesses to develop new products and capabilities, as well as stand out as a workplace for potential employees.

Challenges of AI Democratization

However, making AI widely available across the organization comes with challenges.

Concerns about the quality and reliability of AI outputs can make employees and leaders hesitant to rely on the technology. Additionally, implementing AI requires an IT team skilled in integrating AI applications into existing systems and processes. There is also a risk of overreliance on AI, which can lead to the erosion of critical workforce skills. To address these issues, ongoing upskilling and reskilling are essential to ensure employees can use AI responsibly and effectively.

For many companies, this democratization will require a two-step process:

1. Making data and AI tools widely available across company networks.
2. Providing training that enables employees to use these new technology capabilities.

At AT&T, for example, the company “focused on analytic skill development and employee growth” as part of its effort to make data and machine learning applications available to non-technical employees.

Enhance AI Skills Accessibility Through Learning

1. Customized learning pathways

Recognizing that people will need individualized training. The best uses of AI will vary across job roles and business functions. Tailored AI upskilling that meets individual needs is more effective than a “one-size-fits-all” approach.

2. Interactive and engaging learning content

Dull content can hinder AI democratization. Interactive tutorials, hands-on labs and exercises, and simulations are among the formats L&D leaders can use to ensure that learners are actively engaged. This kind of learning content is more likely to be retained and applied in day-to-day work

3. On-the-job training

Instead of making learning separate from ordinary work, integrate AI training into jobs. On-the-job training shrinks the barrier to applying new AI skills in daily work routines. This style of learning, which makes it obvious how the training can improve job performance, is also more engaging.

4. Cross-functional teams

Technical teams are likely to start with stronger AI skills. Encouraging collaboration between technical and non-technical teams can lead to new business applications of AI and cross-pollinate AI skills.

How Digital Badges Drive Inclusive AI Skill Development

As organizations work to democratize AI, overcoming challenges such as accessibility and skill gaps becomes crucial. Digital credentials emerge as a powerful tool to address these challenges and promote inclusive skill development across your workforce. Here’s how they can make a difference:

• Transparency in skill levels: Digital credentials include detailed metadata that makes it clear exactly what skill and skill level a particular digital badge signifies.
• Personalized learning pathways: Credly’s new Pathways feature allows issuers to set criteria badges that automatically lead to a completion badge. By defining clear skill milestones and structured learning paths, it simplifies AI skills development, making it easier for employees to understand and achieve necessary skills, and supports a more inclusive approach to AI education.
  
• Standardized skill verification: Credentials give employers a standard way to understand what skills individuals have, including when they received training and how the skill was assessed.
• Motivation for continuous learning: The prospect of earning a shareable digital badge for completing a training program can be a powerful motivator, creating broader workforce engagement around AI training.
• Portable credentials: Digital credentials can follow individuals as they advance within an organization, giving managers clarity about a new or prospective team member’s skills. This portability can also be attractive to workers, who gain a career-boosting credential when they earn a digital badge.
• Tracking and analytics: Digital credentials provide L&D leaders and other senior leaders verifiable data about workforce AI skills. This enables them to understand how fast and effectively AI training is being implemented. It can also highlight potential AI skill gaps in the organization. These data-based insights lead to better decision-making.

Credly, the leading digital credentialing platform, hosts over 2 million AI badges from a wide range of organizations. Its secure credential management system and data privacy provisions make Credly a trusted platform to host digital badges for AI. 

To get a start on understanding the AI skill gaps in your organization, download the “Top In-demand AI skills In 2024 and Beyond” report below.