How the Right LMS Platform Can Bridge the AI Skills Gap Through Strategic Training

As companies embrace artificial intelligence (AI), ensuring enough talent to harness it has become a key issue. Businesses can have state-of-the-art AI tools to augment operations, but without people with the right skills, they’re next to useless.

A recent survey of HR executives and managers indicates that most are convinced of AI’s impact on the workplace. Nearly two-thirds agree that AI is changing in-demand skills, and less than half expect to face a skills gap. As a result, there’s been a major push to invest in learning and development (L&D).

With the skills gap unlikely to be resolved in the short term, upskilling makes sense in this economy. Here’s an in-depth look at AI training and how tools like an LMS platform can help in this digital transformation.

Training as a Strategic Advantage

The latest Digital Leadership Report by UK-based digital consultancy Nash Squared/Harvey Nash found that the AI skills shortage has grown exponentially. Based on its survey of over 2,000 technology leaders and professionals, the firm found that AI has become the most scarce skill—from sixth place—in 18 months.

The report, which has been published annually since the late 1990s, stresses that it’s the largest jump observed in over 15 years. It points to the surge in AI investment, given that upskilling has struggled to keep pace. (1)

If a business struggles with finding talent, an alternative is to train its current workforce in the necessary skills. Upskilling or internal training, especially through online courses, is a cost-effective alternative due to the following advantages:

• Builds loyalty and retention: Internal training helps employees better understand their role in the company or organization. It grants them a platform to fully use their skills, leading to quality deliverables that their leaders appreciate.

• Personalized learning: Focusing training on the necessities related to the employee’s work helps sharpen their primary skills.

• Reduces time to productivity: Employees who apply everything they’ve learned in training produce higher-quality deliverables for less time.

Internal training also benefits from existing domain expertise. AI is only as good as the data it’s fed with, making a team member’s wealth of specialized knowledge an ideal partner.

Here’s a tip for effective internal training:

Facilitate training in a digital learning environment using an LMS platform. Conduct content management, reporting, and analytics with its array of features and tools, all controlled from the user interface. It benefits current and new hires, as it serves as a repository of learning content.

Priority Skills in Training Programs

One important thing to note in AI training is that it should be cross-functional. Because AI affects every facet of modern business, upskilling shouldn’t be limited to technical staff like IT. Those in operations, down to the rank and file, can harness AI just as much. There’s no need to look far for examples, such as AI assisting HR departments in hiring.

A good upskilling plan can start by developing AI literacy. The AI Literacy Framework, jointly developed by the European Commission and Organisation for Economic Co-operation and Development, can be a viable basis. Remote learning through this framework can integrate disciplines like computer and data science, digital and media literacy, and ethics. (2)

Training goals can also include AI’s impact on businesses to help employees understand its importance in achieving objectives. Having something to work towards instills a sense of significance and, more importantly, camaraderie in the team.

Separate training courses can be held for role-specific upskilling. Those who work with data and train AI can participate in model deployment and MLOps training. Anyone who performs non-tech duties can be trained on using generative AI tools.

Building an AI-Focused Training Strategy

Formulating the best approach to AI upskilling boils down to three crucial elements.

Training KPIs That Matter

If there’s one thing that will remain the same amid the rise of AI, it’s the need for the following key performance indicators (KPIs).

There’s a long list of KPIs for AI upskilling, but here are ideal starting points.

• Pre/post training assessment: This KPI measures the employee’s AI knowledge before and after the training. It uses assessment tools like questionnaires, performance evaluations, and skill assessments.

• AI tool usage rate: Also called the adoption rate, this KPI measures the number of active users of a particular AI tool. An increase indicates that employees have been using their training effectively. (3)

• Internal talent mobility: Also called career mobility, it assesses employees’ movement to other roles within the company or organization. Increased mobility suggests a seamless professional development of skills in the workforce.

• External hiring reliance: Current employees delivering quality results reduce the need to augment or replace them with new hires. A low rate in this KPI also saves the company or organization on employee onboarding training costs.

As metrics of a program or process’s success, these KPIs quantify and qualify how effective the training has been. They also distinguish what works and what doesn’t.

Conclusion

Sustainable AI and digital transformation begin with the people already working for you. CIOs and tech leaders must spearhead the effort through effective HR and L&D.

 References

1. "AI creates the world’s most considerable tech skills shortage in over 15 years, finds Nash Squared/Harvey Nash report," Source: https://www.harveynash.co.uk/latest-news/digital-leadership-report-2025

2. "Milberg T. Why AI literacy is now a core competency in education," Source: https://www.weforum.org/stories/2025/05/why-ai-literacy-is-now-a-core-competency-in-education/

3. "Chinoy H, Liu A. Measuring gen AI success: A deep dive into the KPIs you need," Source: https://cloud.google.com/transform/gen-ai-kpis-measuring-ai-success-deep-dive