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Overview

AI transformation is one of the most complex workforce challenges organizations face today. Employees need new skills quickly, at every level of the organization, while leaders need visibility into where capability gaps exist and whether upskilling efforts are working. SkillsDB gives HR teams, learning and development leaders, and managers a unified platform to manage every stage of an AI transformation initiative. Rather than relying on spreadsheets or disconnected tools, you can define your AI competency expectations, measure where your workforce stands today, deploy targeted learning resources, and track progress — all in one system. This tutorial covers the full workflow from initial setup through ongoing monitoring. It is organized into phases that map to how a transformation typically unfolds. Each phase identifies who is responsible and what actions they take. Who this tutorial is for:

• Administrators — Build the skills framework, configure careers, and manage the platform
• Managers — Assess team members, set benchmarks, assign learning, and track progress
• Employees — Complete self-assessments, pursue learning resources, and track their own development

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Phase 1: Build Your AI Competency Framework

Who does this: Administrators Before you can assess or develop AI skills, you need to define what AI competency means for your organization. This means structuring an AI career path, creating the individual skills that make it up, and defining what proficiency looks like at each level.

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Create an AI career path

A career path in SkillsDB is the top-level grouping that organizes related skills into a coherent development track. For AI transformation, you will typically create one or more careers such as “Artificial Intelligence,” “Data and Analytics,” or “AI Engineering.”

1. Navigate to Company > Library > Careers in the left sidebar.
2. Select + New Career to open the career creation form.
3. Enter a career name (for example, Artificial Intelligence) and a description that summarizes the scope of skills covered.
4. Select Save.

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Define sections and skills

Within each career, organize skills into logical sections. Sections help employees and managers navigate a large skill set by grouping related competencies together. Common sections for an AI transformation career might include: | Applied AI | AI for Process Automation, AI-Assisted Decision Making | For each skill, navigate to Company > Library > Skills and select + New Skill. Provide a clear name, a description that explains what the skill entails in practice, and link the skill to the relevant section in your AI career.

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Set proficiency levels with grading rubrics

A grading rubric defines what each level of proficiency means for a skill. Clear rubrics make assessments more consistent and help employees understand what they are working toward. Your organization’s administrator configures the grading scale (for example, a 1–5 or 0–7 scale). For each level, provide a short label and a detailed description. For AI skills, rubrics might look like: Navigate to Company > Settings to configure grading rubrics. Once set, rubrics apply across all skills in your organization.

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Phase 2: Baseline the Organization

Who does this: Administrators and Employees Once your framework is in place, the next step is to understand where your workforce stands today. SkillsDB provides two complementary tools for establishing a baseline: surveys for gauging general AI readiness and sentiment, and self-assessments for capturing skill-level proficiency data.

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Deploy an AI readiness survey

Surveys let you ask open or structured questions to your entire organization or targeted groups. Before launching formal skill assessments, use a survey to gauge employee familiarity with AI tools, comfort level with AI adoption, and awareness of your organization’s AI strategy. Administrators create surveys in Company > Surveys. A readiness survey might include questions such as:

• “How familiar are you with generative AI tools such as ChatGPT, Gemini, or Copilot?”
• “How confident do you feel using AI tools in your current role?”
• “What barriers do you experience when trying to use AI tools at work?”

Once deployed, survey responses are tracked and aggregated. Administrators can view response rates and results from the survey management interface.

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Launch self-assessments

Self-assessments ask employees to rate their own proficiency on the skills defined in your AI career framework. This gives you a self-reported baseline across the organization. Administrators launch assessment cycles from Company > Assessments. When a self-assessment cycle is active, employees receive a notification and can access their assessment from Profile > Assessments in the left sidebar. From the employee’s perspective:

1. Select Assessments from the Profile section of the left sidebar.
2. Select the active AI skills assessment.
3. For each skill, select the proficiency level that best describes their current capability using your organization’s grading scale.
4. Optionally add a comment to provide context.
5. Submit the assessment when complete.

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Phase 3: Identify Gaps and Prioritize

Who does this: Administrators and Managers With baseline data collected, you can now identify where the organization’s AI skills fall short of your target state and prioritize where to focus development efforts.

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Explore AI skill coverage across the organization

The Find Experts search in Explore Your Org lets administrators and managers search for employees with specific skills at specific proficiency levels. Use this to identify who already has strong AI capabilities — these employees are candidates for AI champion or internal mentor programs. Navigate to Explore > Find Experts and search for skills such as “Prompt Engineering” or “AI Literacy” to see who in your organization holds these skills and at what grade level.

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Analyze skill gaps in the Skills Matrix

The Skills Matrix gives managers a side-by-side view of their team’s AI skill grades compared to the benchmark targets set for each skill. Cells are color-coded with directional indicators:

• Up arrow (blue) — Grade exceeds the benchmark
• Star (green) — Grade meets the benchmark
• Down arrow (red) — Grade falls below the benchmark
• Gray circle — No grade recorded

Managers access the Skills Matrix by navigating to Team > Skills, selecting the AI career path, and then selecting the Total Assign stat card on the Career Overview page. Use the Below Target filter in the Skills Matrix filter panel to quickly surface the team members with the largest AI skill gaps.

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Flag AI champions and at-risk employees

People Flags in SkillsDB let you apply custom labels to employees that can be used for segmentation, filtering, and targeted outreach. For AI transformation, administrators can create flags such as:

• AI Champion — Employees with strong existing AI skills who can lead peer learning
• Priority Upskill — Employees with significant AI skill gaps in roles where AI adoption is critical

Administrators configure people flags in Company > Settings > Configure Flags. Once flags are created, managers can apply them to individual team members. Flagged employees can then be filtered in reporting and search views to support targeted interventions. See Skill Flags for more detail on how flags work.

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Phase 4: Build Learning Pathways

Who does this: Administrators and Managers Identifying gaps is only useful if employees have a clear path to closing them. SkillsDB’s training library and learning plan system gives you the tools to connect skill gaps to specific learning resources and track who is working on what.

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Add AI learning resources to the library

Before you can assign AI training to employees, those resources need to exist in your organization’s training library. Administrators add training resources in Company > Library > Training. For each resource, you can specify: | Skills | Which AI skills this resource helps develop | Linking training resources directly to skills is the key step — it connects your competency framework to actual learning content and enables the system to surface relevant resources when a skill gap is identified.

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Assign learning resources to team members

Managers assign training resources to their direct reports from the team member’s learning plan. Resources assigned this way appear in the employee’s personal learning plan under the To Do status. To assign a resource from the library to a team member:

1. Navigate to Team > People and select the team member’s name.
2. Open the Learning Plans tab on their profile.
3. Select Add resource to add a custom entry, or assign a library resource directly from the library record.
4. The resource appears in the team member’s plan with your name as the person who added it.

For bulk assignments — for example, adding the same AI Fundamentals course to all team members — navigate to the library resource record and use the assign option to select multiple people at once.

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Let employees self-direct with custom resources

Employees can also add their own learning resources to their personal learning plans — books, online courses, internal workshops, or any development activity they are pursuing independently. Employees access their learning plan via Profile > Learning Plan. Encouraging employees to log their own AI learning — even informal exploration — gives your team visibility into the full scope of learning activity happening across the organization.

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Phase 5: Run Manager Assessments and Set Benchmarks

Who does this: Managers Self-assessments capture how employees see themselves. Manager assessments provide an independent, externally calibrated view of each employee’s actual AI skill proficiency. Running both creates a richer, more accurate picture of the team’s capability.

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Launch a manager assessment cycle

Administrators create assessment cycles from Company > Assessments. Once an assessment is created and assigned to managers, each manager sees the active assessment in Team > Assessments with a Begin or Continue action button.

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Grade team members using batch grading

The batch grading view is the core workflow for manager assessments. It allows you to work through one skill at a time, grading all team members before moving to the next skill — which is more efficient and promotes grading consistency than assessing one person completely before moving to the next. For each AI skill in the assessment:

1. Select Assessments from the Team sidebar section.
2. Locate the active assessment and select Begin or Continue.
3. The batch grading view opens, showing your team in a table with columns for prior grade, new grade, focus toggle, and benchmark.
4. For each team member, select their grade from the proficiency scale.
5. Navigate to the next skill using the skill panel on the left.

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Set benchmarks for target proficiency

For each AI skill and team member, you can set a benchmark — a target proficiency level that defines what “good” looks like for that person in their role. Benchmarks appear in the Skills Matrix as directional indicators, making it easy to see at a glance who is on track and who needs additional support. To set a benchmark during batch grading:

1. Locate the team member’s row in the grading table.
2. Select the cell in the Benchmark column, or press B on the keyboard when the row is highlighted.
3. Select the target proficiency level from the dropdown.
4. The benchmark saves immediately.

For teams where everyone in the same role should have the same benchmark, use multi-select: hold Shift and click multiple rows, then press B to set the benchmark for all selected people at once. See Customizing Benchmarks for a full walkthrough of the benchmark workflow.

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Phase 6: Track AI Certifications

Who does this: Administrators and Managers Formal AI certifications — such as vendor credentials from Google, Microsoft, AWS, or professional bodies — represent externally validated competence that complements internal skill assessments. SkillsDB’s certifications system lets you assign, track, and monitor these credentials at the individual and team level.

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Set up certifications in the library

Administrators create certifications in Company > Library > Certifications. For an AI transformation initiative, you might set up certifications such as:

• Google Cloud AI Fundamentals
• Microsoft Azure AI Engineer Associate
• AWS Certified Machine Learning Specialty
• Responsible AI certification (internal or external)
• Tool-specific credentials (e.g., platform-specific Copilot or Gemini certifications)

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Assign certifications to employees

Once a certification exists in the library, managers or administrators assign it to specific employees. The employee receives the certification as an Assigned task and is prompted to complete the certification and submit their credential for approval. The certification lifecycle follows this progression:

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Monitor certification status across the team

Managers track their team’s certification status from Team > Certifications. The certification tracking page shows every assigned certification, its current status, and expiration date. Certifications expiring within 30 days are flagged as Expiring Soon, giving managers enough time to prompt renewals before credentials lapse. See Certification Tracking for a full guide to the certification workflow.

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Phase 7: Monitor Transformation Progress

Who does this: Administrators and Managers AI transformation is not a one-time event — it is an ongoing initiative that needs regular measurement. SkillsDB provides several views that help you monitor whether skill levels are improving, whether learning is happening, and where the organization still has critical gaps.

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Review the Career Overview for AI skills

The Career Overview is a dashboard that aggregates statistics across all team members assigned to a specific career path. For your AI career path, it shows:

• Total People — How many employees are assigned to the AI career
• Meets Target — Percentage whose average grade meets or exceeds the benchmark
• Below Target — Percentage with grades falling below benchmark
• Skills with Training — How many AI skills have linked training resources available

Navigate to Team > Skills, select the AI career from the table, and the Career Overview opens automatically.

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Use the Skills Matrix to track skill-by-skill progress

The Skills Matrix gives you a detailed, person-by-person view of how AI skill grades have changed over time. By comparing grades from one assessment cycle to the next, you can identify which employees are progressing, which skills are improving organization-wide, and where targeted intervention is still needed. Switch between the Manager and Employee tab in the Skills Matrix to compare self-assessed grades with manager-assessed grades. Persistent gaps between self-assessment and manager assessment on AI skills can surface overconfidence or underconfidence that may need coaching attention.

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Export data for leadership reporting

Both the Skills Matrix and the My Team Skills views support Excel export. Use exports to build leadership-facing reports showing:

• AI skill adoption rates by department
• Progress toward benchmark targets since the last assessment cycle
• Certification completion rates

Select Export in the Skills Matrix toolbar to download the current view. Apply filters before exporting to produce targeted extracts — for example, filter to the AI career and export only employees Below Target for a gap-focused report.

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Putting It All Together: The Transformation Timeline

A typical AI transformation initiative in SkillsDB follows this phased timeline. The table below summarizes who does what and when:

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Common Questions

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