AI, Skills, & Datapower – The Future of Qualification?

About Martin Knapp

Focused on creating modern learning technology environments, promoting product innovation and AI, and expanding strategic partnerships.

13 years of experience in industrial environments:

• Internal IT consulting & project portfolio management
• Team leadership in training design & development – internal full-service provider: consulting, eLearning content creation, trainers, LMS
• LMS, training, and reporting strategies including implementation, metric definition, and goal achievement (quality & quantity)
• Expansion of qualification management in production environments
• LMS expansion project management
• Establishment and expansion of a reporting landscape for complex training analytics & progress reports
• Piloting innovations in simulation & augmented reality

A good starting point is to examine the classical hierarchical structure of many companies. These are often organized by functional areas such as production, sales, or administration, and divided into multiple management levels.

Within such structures, a detailed analysis can help uncover the root causes of low participation rates and discover tailored solutions.

At this point, the use of a flexible software system becomes crucial. The system must enable modular and customizable assembly of qualification requirements into individual competency profiles. It should also recognize alternative qualifications as equivalent, allowing them to fulfill the same requirement. In other words, for a given competency, either Qualification A or Qualification B may be acceptable – providing much-needed flexibility for diverse career paths, prior experience, and alternative learning achievements.

Additionally, the system must account for differences based on location or country-specific regulations. For instance, safety standards at a production site may vary significantly depending on local laws and requirements. A modern qualification management solution should automatically incorporate such context-specific differences to ensure that the competency profiles remain accurate, complete, and relevant across the organization.

For HR / Learning & Development (L&D): Strategic Oversight and Portfolio Optimization

• What is the current qualification fulfillment level across the organization?
• Which departments or business units show particularly low compliance or qualification completion rates?
• How can we increase the overall qualification level—e.g., through new learning formats or structured campaigns?
• Which training programs are missing from our current portfolio to meet key requirements?
• Are there employees with significantly more or fewer trainings than expected—and why?
• What statistical insights can guide our planning?

– Percentage of employees who have completed all mandatory training
– Fulfillment rates by department, location, or business unit
– Trends in qualification completion over time

For Managers: Operational Oversight and Team Responsibility

• What is the current qualification status of my team?
• Are there team members who haven’t completed their mandatory trainings yet?
• Do I need to follow up or remind anyone to complete outstanding training?
• Which training programs can I recommend to a specific team member, based on their role, potential, or upcoming tasks?

For Employees: Transparency, Guidance, and Career Development

• How complete is my current qualification profile?
• Which requirements have I already fulfilled, and which ones are still pending?
• Are there specific training recommendations for me to complete next?
• Which learning opportunities could help me grow professionally—either in my current role or with a view toward future career goals?

Multi-Level Access to Information: From System Reports to Personal Development Dialogues

To ensure that transparency is not just theoretical but actively contributes to day-to-day operations, qualification-related information must be made available across multiple levels and channels—tailored to the roles and needs of different user groups.

• The Learning Management System (LMS) serves as a central platform for this purpose. It provides access to analytics, reports, and statistics—filtered by permission levels, allowing HR or L&D professionals broader access than individual managers or employees. In addition, managers and learners benefit from dedicated functions within the learning portal that provide clear overviews of qualification statuses and recommended actions.
• Automated system emails—such as reminders about expiring or outstanding qualifications—ensure that important deadlines are not overlooked and that users are prompted to take timely action.
• Beyond digital channels, personal interaction remains a vital component of effective qualification management. In development discussions between employees and their managers or HR representatives, individual requirements, strengths, and career perspectives can be discussed in depth and translated into concrete learning paths.

This creates a holistic system in which information is not only accessible, but also actively used—to support individual growth and organizational success.

For Staff Development & Academy

Here are some illustrative examples of findings that AI might surface:

• Leadership Development:
  A very small target group is served by a broad and strategically important training portfolio. This discrepancy may indicate a potential bottleneck in succession planning or an underdeveloped leadership pipeline.
• Machine Operators:
  A high density of technical training requirements (e.g., 10 trainings for 2 individuals) presents a risk of knowledge silos. If even one person is absent or leaves the company, critical expertise could be lost.
• Production Techniques:
  No current demand is registered. This raises the question of whether courses should be removed or the target group redefined.
• Sales Experts:
  A highly demanding and diverse training program suggests a clear investment in high-potential employees, which can be strategic but should be monitored for scalability and inclusiveness.
• Mandatory Trainings:
  These are required company-wide by law or policy. High completion rates are critical, and AI can ensure ongoing compliance monitoring, flagging gaps automatically.

By continuously interpreting qualification data in context, AI helps focus attention where it matters most—supporting resource allocation, uncovering hidden risks, and enabling proactive talent development.

Here are some practical application examples for leaders:

• Analysis & Prioritization:
  AI highlights employees with unusually large qualification gaps and prioritizes where action is needed.
• Define immediate actions:
  Such as assigning urgent training, setting personal development goals, or focusing on critical competencies.
• Understand and resolve root causes:
  Through one-on-one conversations, managers can clarify whether missing qualifications are due to structural issues, lack of training availability, time constraints, or other factors.
• Create individualized development plans:
  AI suggests tailored learning paths with specific goals, deadlines, and responsibilities for each employee with significant gaps.
• Encourage knowledge transfer:
  Recommendations might include pairing less experienced employees with mentors or senior colleagues to speed up development.
• Support regular monitoring and feedback:
  Progress can be tracked through automated alerts, progress reports, and smart suggestions for follow-up actions.
• Enable effective resource planning:
  AI insights can reveal training bottlenecks or optimal scheduling windows to better integrate learning into everyday operations.

Instead of searching through catalogs or training overviews for a long time, the employee can formulate their goal – for example:

"I work in manufacturing and would like to take on a team leader position in the medium term – what do I need to do for that?"

The chatbot automatically analyzes:

• the employee’s completed trainings and qualifications,
• the requirements for the desired position,
• relevant available learning opportunities,
• and company guidelines for internal career advancement.

Based on this analysis, it provides:

• Personalized recommendations and prioritization of upcoming trainings or qualifications
• Suggested development paths based on the employee’s current role
• A clear overview of required vs. completed qualifications (e.g., in PDF or table format for use in development conversations)
• Reminders for recurring mandatory training, such as annual safety instructions
• Guidance on how to apply for further training opportunities
• Advice on continuing education in specific domains like machine operation or manufacturing
• Support in preparing for development discussions with managers

This interactive, data-driven dialogue empowers employees to take an active role in shaping their learning and career paths—quickly, easily, and with tailored guidance.