Human-Centric, Ethical, and Practical AI
Augment the power of your organizational DNA through machine learning and artificial intelligence.
Talk to an AnalystExplore, Expand, and Evolve Your Organizational DNA Through AI
Getting to “Go”
Get ready to start, optimize, and operationalize AI with human-centric use cases.
Strategize & Govern AI
Start aligning data and security strategies and approach AI ethically.
Plan a Proof of Concept
Prioritize and plan your first purpose-driven AI use case.
Architect AI
Build an architecture that effectively supports practical AI.
Select Technology
Select the right tools and technologies.
Develop & Deploy
Design, develop, validate, and deploy AI use cases.
Champion & Communicate
Collaborate, communicate, and co-create competitive advantage.
Getting to “Go”
When making an AI go/no-go decision:
- Understand what AI really means for your organization and how it can solve your business problems.
- Learn what others are doing in your industry to leverage AI technologies for competitive advantage.
- Define the use cases that maximize the value of your AI investment.
- Ensure that the organization is ready for AI.
Strategize & Govern AI
- Make sure that your data is ready for AI.
- Align your data and AI strategy with your business goals and objectives.
- Define AI and data governance operating and resource models.
- Align with the analytics strategy.
- Ensure you take an ethical approach to AI and data.
AI Governance
Build a Robust and Comprehensive Data Strategy
Mitigate Machine Bias
Establish Data Governance
The Road to ITSM AI: Develop an ITSM AI Strategy
Plan a Proof of Concept
- Ideate and define AI use cases and choose the first AI proof of concept.
- Identify a specific problem where the AI solution will meet business needs and enable business and technology transformation.
- Create the business case for AI.
Business Case Workbook
Idea Reservoir Tool
Build a Chatbot Proof of Concept
Prepare to Privacy-Proof Your AI Technology
Architect AI
- Build your target-state architecture from predefined best-practice building blocks. Using architecture building blocks will speed up the architecture decision phase.
- The success rate of AI initiatives is tightly coupled with data management capabilities and a sound architecture.
Create an Architecture for AI
Build a Data Pipeline for Reporting and Analytics
Modernize Data Architecture for Measurable Business Results
Architect Your Big Data Environment
Select Technology
- Select a technology platform that meets your data science, machine learning (ML), and AI requirements.
- Select an off-the-shelf AI tool.
Drive Business Value With Off-the-Shelf AI
Build a Strategy for Big Data Platforms
Investment Banking AI Platforms Report
Build Your Infrastructure Roadmap
Develop & Deploy
- Start with the proof of concept.
- Design and develop your first AI/ML solution.
- Test, deploy, and validate.
- Build your data, data science, ML, and AI operations practices.
Champion & Communicate
- Create a change management strategy to ensure adoption across the enterprise.
- Use talent management to drive the success of AI initiatives and help with the culture shift.
- Create a communication strategy.
Master Organizational Change Management Practices
Establish a Communication and Collaboration System Strategy
Change Management Communications Plan