MathWorks Adds AI Copilots to MATLAB and Simulink for Faster Development
MathWorks released AI-powered copilots in its 2026a software update designed to speed up embedded systems development. Engineers can now ask questions to an AI assistant instead of manually searching through code or studying complex models.
The copilots generate code suggestions, explain difficult programming lines, and identify where changes are needed in large Simulink models. Work that once took days can now happen in minutes.
Who Benefits Most
Engineers inheriting massive legacy models from other teams stand to gain the most. An engineer working alone on unfamiliar code can ask the AI to explain what previous developers built, cutting onboarding time significantly.
Not all customers are ready for AI adoption. Industries with strict security or regulatory requirements can continue using MATLAB and Simulink without generative AI features.
AI Doesn't Replace Verification
MathWorks acknowledges that AI models can generate different answers for the same question, making them fast but not always fully dependable on their own. The company built its AI capabilities on top of a trusted engineering foundation created through years of testing and validation.
Verification and validation still require experienced teams. Engineers must review, test, and validate every part of the system before deployment. In automotive and embedded systems, where small errors create serious risks, deterministic analysis tools like Polyspace remain critical alongside AI-assisted development.
Data Security and IP Protection
As AI integrates deeper into engineering workflows, concerns about data security and intellectual property have grown. MathWorks said it does not store customer data or use it to train AI models.
Real-World Applications
Mercedes-Benz engineers used AI to predict cabin airflow without adding new hardware. The AI model was more cost-effective and more accurate than physics-based models, improving cabin comfort while reducing hardware complexity.
An Indian truck manufacturer used AI to estimate vehicle payload without extra sensors. The engine can now optimize torque delivery more efficiently, improving fuel economy and lowering operating costs for fleet operators.
Teamwork Remains Essential
Different engineers bring different expertise to projects. AI can accelerate coding and model development, but speed matters less than having a common set of tools and a single source of truth across teams.
Low-code and no-code platforms are bridges to understanding complex systems, not replacements for engineers. Graphical interfaces can visually explain what the AI has done and allow users to make changes and test ideas.
Handling Large Projects
MathWorks built AI tools that intelligently pull only the relevant information needed for a particular task instead of loading an entire codebase into memory. The system requests more details only when necessary.
The company is developing specialized AI "skills" that activate only when needed - for debugging code, testing software, or improving development quality. This approach makes AI more focused and practical rather than generating generic output.
Engineers should not lose touch with fundamentals. AI should assist human creativity and productivity, not replace engineering understanding completely.
Learn more about AI for Product Development and how teams are adopting these tools in practice.
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