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From AI Strategy to Implementation: Cisco’s AIBIZ and AITECH Paths
By Brad Haynes | 52 Min Video
Artificial intelligence is rapidly becoming a core capability for every organization, but successful adoption requires both a strong business strategy and effective technical execution.
Cisco introduced the Cisco AI Business Practitioner (AIBIZ) and Cisco AI Technical Practitioner (AITECH) courses.
In this video, we highlight the learning paths, explaining how they work together to help organizations adopt AI responsibly, strategically, and at scale.
Watch more videos like this on our YouTube Channel.
AI Business Practitioner (AI Biz) Highlights
Audience: Business professionals, leaders, managers, sales, marketing, operations, customer success, and executives who influence strategy and compliance.
Focus Areas:
- AI literacy and strategic leadership.
- Use of generative AI tools for productivity (e.g., Co-Pilot, GPT).
- Development of AI governance and adoption frameworks (e.g., NIST AI Risk Management Framework, ISO 42001).
- Ethical AI use covering privacy, bias, compliance, and risk management.
- Understanding large language models (LLMs) and prompt engineering basics.
- Hands-on exposure to AI ecosystems like Hugging Face for model exploration.
Outcomes:
- Confident AI discussions and decision-making.
- Enhanced productivity via AI-assisted content creation and research.
- Strong governance awareness and ability to formulate AI adoption roadmaps.
- No technical background required; focuses on outcomes over implementation.
AI Technical Practitioner (AI Tech) Highlights
Audience: IT engineers, network engineers, automation teams, AI ops practitioners, architects, and technical leads.
Focus Areas:
- Practical use of AI tools in coding automation, data analysis, and operational workflows.
- Application of AI-assisted coding to generate and validate network configuration code.
- Integration of AI into existing IT workflows ensures stability, security, and scalability.
- Exploration of agentic AI (bots autonomously interacting with bots).
- Security and governance in AI pipelines, including data integrity, authentication, access control, and monitoring.
- Awareness of risks like shadow AI (unauthorized AI use) and policies to mitigate them.
- Hands-on labs simulating real-world AI-enabled environments.
Outcomes:
- Improved ability to automate legacy processes and support AI platforms.
- Enhanced collaboration with business stakeholders.
- Validation of practitioner skills with digital badges and CE credits.
- Requires foundational IT knowledge but no data science expertise.
Instructor Bio:
Brad brings over two decades of experience in the IT industry, with a specialized focus over the past 12 years on technical education and workforce development. He holds professional certifications in networking and cybersecurity from Cisco, ISC2, and CompTIA, and has a strong foundation in designing and implementing secure, scalable technology solutions.