Learn how to use AI for research, writing, analysis, problem-solving, automation, and the everyday tasks that come with your work.
Follow a structured path, practice what you learn, get useful feedback, and keep building your skills as you go.
For individuals and teams.
How would you use AI to research the market without relying on unsupported claims?
Add a verification step before using AI-generated information in your final analysis.
You don’t need to learn every possible use of AI. Start with the skills, tasks, and workflows that are most relevant to the work you already do.
Research, writing, documents, meetings, analysis, and everyday problem-solving.
Research, content, campaigns, SEO, analysis and workflows.
03Research, prospecting, outreach, follow-ups and preparation.
04Knowledge, research, responses and support workflows.
05Planning, decision support, documentation and communication.
06Processes, reporting, documentation and automation.
You shouldn’t have to finish hours of content before finding out what you can actually do.
This skill supports several tasks in your current learning path.
The instruction is missing important context and an expected output format.
Specify what information should not be included in the final result.
Learning a concept is one thing. Using it in a realistic situation is another.
Work through questions, decisions, and practical tasks. Some exercises have a clear answer. Others ask you to explain your reasoning, compare approaches, or defend a decision.
Good AI instructions include enough information for the model to understand the task, important constraints, and what a useful result should look like.
“Write an email about our new product.”
“Write a concise launch email for existing customers who already use our analytics product...”
Rewrite the request so the AI understands the audience, objective, constraints, and expected output.
The objective is clear, but the request could be more reliable if you define what should not appear in the result.
Talk through how you would solve the task and why you chose that approach.
Finishing a lesson shouldn’t reset your learning.
Your level, goals, practice, assessments, and progress help BoltAI decide what may be most useful for you to work on next.
Explore AI Skills AssessmentLearning paths bring related skills, lessons, practice, and assessments together in a sequence built around a role or goal.
Build useful AI skills for research, writing, documents, analysis and everyday professional tasks.
Explore the path →Use AI across research, content, planning, SEO, campaign work, analysis and repeatable workflows.
Explore the path →Understand how AI, tools, automation and human review can work together in reliable workflows.
Explore the path →AI becomes useful when you can apply it to a real problem.
Different people use AI for different kinds of work. BoltAI helps teams learn around the roles and tasks that matter to them, while giving managers a clearer view of learning and progress.
Role-based learning Training that reflects the work people actually do.
Practice & assessment See more than course completion.
Team visibility Follow progress and identify areas that need attention.
Structured learning, practical exercises and feedback for individual professionals.
Role-based learning with team management and progress visibility.
A practical process for checking important information before it goes into real work.
Read the guide → PromptingLearn what context actually helps and what information usually creates unnecessary noise.
Read the guide → AutomationNot every repeatable task should be automated. Use a clearer way to decide.
Read the guide →Yes. Some learning paths start with the fundamentals, while others are designed for people who already use AI and want to improve specific skills.
No. Lessons are part of the experience, but BoltAI also includes practice, assessments, feedback, and structured learning paths.
No. Many courses focus on everyday professional work and do not require programming experience. Technical paths will clearly explain any prerequisites.
Your level, goals, learning activity, practice, and assessments can be used to recommend what may be useful to work on next.
Assessment formats depend on the course. They may include knowledge checks, practical exercises, open-ended responses, and interactive evaluations.
Some skills apply across many AI tools, while other courses focus on specific tools or workflows. Each course explains which tools are used.
Yes. Team plans are designed for organizations that want structured AI learning across multiple people, with team management and progress visibility.
Eligible courses and learning paths include a certificate after the required learning and assessments are completed.
Start with the learning path that fits what you want to improve and build your skills through learning, practice, and feedback.