Artificial Intelligence, Machine Learning, and Automation Services

The vendor required to provide artificial intelligence (AI) is to advance the economy of the province by promoting technology development and application, performing applied research, and providing expert advice, technical information and scientific infrastructure that is responsive to the needs of the private sector and supports activities in the public sector.
- Provide professional services in support of artificial intelligence, machine learning, and automation initiatives, which may include, but are not limited to:
•    Artificial intelligence and machine learning solution design, development, and implementation 
•    Generative artificial intelligence solutions such as summarization, drafting, and virtual agents 
•    Advanced or agent-based artificial intelligence solutions supporting complex decision workflows 
•    Business process automation using configurable, low-code, no-code, or robotic process automation platforms 
•    Data engineering, data preparation, and data integration to support artificial intelligence initiatives 
•    Advisory services related to artificial intelligence strategy, governance, risk management, and responsible use 
•    Pilot, proof-of-concept, and proof-of-value initiatives
•    Training, documentation, and knowledge transfer to internal teams
- Their responses according to these categories:
•    Artificial intelligence and machine learning solutions
•    Generative artificial intelligence
•    Advanced or agent-based artificial intelligence
•    Business process automation and workflow automation
•    Data engineering and artificial intelligence readiness
•    Advisory, governance, and responsible artificial intelligence enablement.
- Artificial intelligence and machine learning solutions
•    Client organization and industry
•    Business problem addressed
•    Data sources and data preparation required
•    Techniques or approaches used
•    Model training, fine tuning, and feedback loop methodology
•    Model evaluation, observability, accuracy, precision, TPR, bias and AI ethics
•    Outcomes achieved (quantitative where possible)
•    Lessons learned relevant to agency
- Generative artificial intelligence
•    Human oversight was incorporated
•    Accuracy and reliability risks were managed
•    Explain ability and auditability considerations
- Advanced or agent-based artificial intelligence
•    Points handled by artificial intelligence versus humans
•    Explain ability and auditability considerations.

- Questions/Inquires Deadline: February 12, 2026