Managed Cloud, Accounting/ERP Software, Managed IT, and Cybersecurity
Charting Your AI IMPACT Journey
Prepare is the second stage of the AI IMPACT Framework.
In the Architect stage, leadership established direction, priorities, and ownership. Now it’s time to prepare the organization, and your technology environments, for broad AI adoption and long-term performance.
- How do we create a secure AI infrastructure?
- How do we leverage complete and accurate data?
- Who owns AI governance efforts?
- Where should we focus our investments?
- How are we messaging our investments internally and externally?
Prepare turns those decisions into organizational readiness.
Architect
Define the vision, align leadership, and build the strategy.
Prepare
Assess readiness, define the foundation, and enable success.
You Are HereOperationalize
Deploy solutions, drive adoption, and enable AI in the business.
Transform
Scale successful initiatives and embed AI into operations.
Optimize
Continuously improve performance, measure impact, and stay ahead.
AI ROI Progress Depends on Consistent Measurement
As AI becomes more integrated into operations, leadership teams begin asking new questions:
- Which initiatives are producing the strongest outcomes?
- Where are investments generating measurable returns?
- What new risks require attention?
Organizations answering these questions consistently are better positioned to improve performance and make informed investment decisions.
Next Stage: Operationalize
Operationalize focuses on employee adoption, training, communications, and incorporating AI into daily work.
Results Depend on Readiness
Leadership teams often focus first on technology selection and implementation. The organizations realizing measurable business value are the ones that prepare the broader operating environment required to support AI at scale.
The harder work requires the intense effort of entire departments and influential managers. That involves preparing data, governance, and compliance oversight, enforcing acceptable-use policies and best practices, and engaging leaders and employees for broader adoption.
When those elements are overlooked, several issues emerge:
These challenges rarely originate from software. They reflect how prepared – or unprepared – an organization may be to use AI.
The Questions Prepare Answers
Is Our Data Ready?
Your data fuels AI, so data access, quality, structure, and governance issues can limit the usefulness of AI initiatives.
Are Governance Expectations Clear?
Leadership teams rely on carefully crafted policies, oversight, accountability, and decision structures to guide AI implementation.
Which Opportunities Deserve Attention?
Every use case should be evaluated based on relevance, feasibility, risk, and expected outcomes.
Is the Workforce Ready?
Employees need clarity, support, and AI-specific skills to approach AI with confidence and get the most out of the technology.
Do We Have the Right Operating Foundation?
Leadership needs the right processes and protocols in place to support AI expansion without creating unnecessary risk.
What Prepare Delivers
Prepare strengthens an organization’s ability to adopt AI and maximize long-term performance.
Data Readiness
Assess and address data quality, access, structure, security, and governance considerations that affect AI performance.
Environment Analysis
Assess licensing, permissions, data access, platform configuration, and technical dependencies to optimize AI readiness and long-term performance.
Governance Structures
Develop the policies, oversight mechanisms, councils, and accountability models that enhance compliance and reduce risk.
Organizational Alignment
Create clarity shared across business leaders, IT, operations, risk, HR, and other stakeholders to codify responsibilities and expectations.
Use Case Prioritization
Evaluate opportunities based on feasibility, business value, risk, and organizational readiness.
Responsible AI Foundations
Establish expectations for risk management, usage, and decision-making.
Communication Planning
Prepare leadership and employee communications that support awareness, enhance understanding, and encourage adoption.
Common AI Readiness Challenges
Governance Lags Behind Adoption
Employees gain access to tools outside of the organization’s environment or before policies and oversight are fully established.
Too Many Potential Use Cases
Leadership teams struggle to determine where resources should be concentrated.
Data Quality Issues
Important data remains fragmented, unstructured, or unreliable across systems, departments, and processes.
Limited Internal Capacity
Organizations that lack dedicated AI teams need to embrace an approach that suits existing resources.
Workforce Uncertainty
Employees are unclear about the expectations, support, and future workflows associated with AI integration.
What You Gain
Through Managed AI Services, CBIZ helps organizations strengthen AI readiness and support AI at scale across the business, technology, governance, security, and workforce.
Support includes:
- Data readiness assessment and planning
- AI governance council design
- Responsible AI policy development
- Use case identification and prioritization
- Workforce readiness assessment
- Executive alignment workshops
- Platform implementation planning
- Communication strategy development
- Support model preparation
These are the prerequisite structures and processes required to support long-term business results.
Continuity Beyond Readiness
AI readiness requires continued attention as priorities change, technology evolves, and adoption expands.
Governance structures, policies, workforce capabilities, and operating requirements must develop alongside an organization’s AI portfolio.
CBIZ provides ongoing support in areas such as:
AI governance oversight
Policy refinement
Portfolio prioritization
Workforce readiness
Executive decision support
Risk management
Performance monitoring
This continuity of service enables the organization to maximize adoption and optimize implementation.
Meet Our AI Consulting Leadership Team
David Fisher
National Leader, AI Services & VP, Artificial Intelligence
Rob McGillen
VP, Artificial Intelligence
James Winfrey
Director, AI Go-To-Market
Build Your AI Strategy and Roadmap
Architect establishes direction, ownership, governance priorities, and investment rationale.
Drive Adoption and Workforce Readiness
Operationalize helps employees incorporate AI into daily work.
Return to AI Consulting Services
Review the complete framework and identify the stage aligned with your current priorities.
Build the Foundation for Measurable AI Impact
If your organization is already establishing governance, assessing data readiness, encouraging workforce preparedness, prioritizing use cases, and planning implementation, the next step is turning preparation into long-term results.
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