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Your New Colleague is a Copilot: Aligning Technology, Talent, and Trust

Name: Your New Colleague is a Copilot: Aligning Technology, Talent, and Trust
Author: Jared Matfess
ISBN: 9798868826191

by Jared Matfess

May 2026

201 pages

3h 51m

English

Apress

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Inside Copilot
Your New Colleague is a Copilot
Introduction
Acknowledgments
Table of Contents
About the Author
About the Technical Reviewer
1. GenAI in the Workplace
The SparkAI Is the New SparkGenAI “in Plain English”Key Technical Concept: Large Language ModelsExtending GenAI to Your Business’s DataIGNITE: A Framework for Introducing GenAI to Your OrganizationI – InspireG – GaugeN – Nail PilotsCopilots vs. AgentsI – Iterate Fast: Learning LoopsT – Track ImpactE – Embed Governance and CulturePreparing for ChangeThe SetupThe ExecutionKey Takeaways
2. The Business Case for AI
The Business Case for AIBusiness Case Patterns for AIReturn on EmployeeReturn on InvestmentReturn on the FutureTypical Elements of a Business CaseCrafting a Vision StatementKey Takeaways
3. Gauge Your Readiness
Evaluating Data, Operational, and Cultural RisksData Risk: Knowing What AI Can and Should SeeThe Anatomy of Data RiskData Risk in the Age of RAG and Fine-TuningContent Readiness As a Change InitiativeClarifying Roles and OwnershipSetting User ExpectationsUpskilling the Support NetworkGovernance and Compliance AlignmentFrom Data to DecisionOperational Risk: Managing Systems, Models, and GuardrailsUnderstanding Operational RiskThe Human-in-the-Loop ImperativeCase Vignette: When a Well-Meaning AI Pilot Hit TurbulenceBuilding Your AI Governance PlaybookMonitoring, Measurement, and Incident ResponseCultural Risk – Building Trust, Curiosity, and ConfidenceUnderstanding the Human Side of RiskCreating a Learning CultureMeasuring Cultural ReadinessWorkshop: Building Your AI Readiness Heat MapKey Takeaways

4. Nail Pilots
From Hype to EvidenceDefine the Purpose of Your PilotBalancing Pilot vs. ProductionYou Don’t Know What You Don’t Know!Step 1: Define the High-level Use CaseStep 2: Identify Candidate Data SourcesStep 3: Score Each DatasetStep 4: Plan Next ActionsReference: Red Flags in Unstructured DataThe “Pilot Playbook”Measuring ImpactDocument Learnings and Share OutcomesCommon PitfallsKey Takeaways
5. Iterate
Move Fast and Break ThingsBuilding a Team That Can Iterate Together!Why Waterfall Doesn’t Work for AISuccess Criteria: Not “Done,” but “Useful”Designing Your Feedback RitualsWhat to Technically Iterate On?User Experience As an IterationCreating a Project Risk LogHow to Fail Fast?Executive Stakeholder SupportStep 1: Score the Pilot Across Four Dimensions (10 Minutes)Step 2: Apply the Matrix (5 Minutes)Step 3: Reflection Exercise (5–10 Minutes)Bonus Topic (Optional)Key Takeaways
6. Track Impact
Stop Trying. Start Proving.Why Track Impact Matters More Than EverOrganizational GoalsBusiness Case Patterns for Technology InvestmentsDefining Measurable OutcomesPerforming A/B TestingQuantitative TrackingThe Role of User Behavior in ImpactEnterprise TrackingCommunicating ResultsUsing Scorecards to Drive RepeatabilityKey Takeaways
7. Embed Governance
Why Governance Matters NowEmbedding Governance into Your AI Operating ModelYour Greatest Resistor: Your CultureGovernance Step 1: The AI Working TeamGovernance Step 2: The Intake ProcessGovernance Step 2: Establishing Responsibility BoundariesGovernance Step 3: Who’s the Decision-Maker?Step 3: Digging into the DataStarting Remediation: Prioritizing the Most Sensitive Data FirstTooling and Inventory: Navigating the Gaps in ReportingRemediation: It’s More Than Just Labels!Building Guardrails Instead of GatesAvoiding AI SprawlTying It All Together by Embedding Governance in Your Operating ModelKey Takeaways
8. Building AI Literacy
Preparing Your People for an AI-First WorkplaceAI Literacy for LeadersTeaching the Rest of the OrganizationUnderstanding the Key Persona GroupsTeaching the Rest of the OrganizationHow to Sustain AI Literacy Over TimeCommon Pitfalls When Rolling Out AI LiteracyMeasuring Progress and ConfidenceTeaching People to Think with AIMeasuring Progress and ConfidenceKey Takeaways
9. Designing Your AI Operating Model
AI Will Not Scale ItselfWhat Is an AI Operating Model?Pillar 1: Ownership and AccountabilityPillar 2: Roles and ResponsibilitiesPillar 3: Processes and Lifecycle ManagementPillar 4: Support and EnablementPillar 5: Tools and PlatformsKey Takeaways
10. The Road Ahead: Scaling and Evolving Your AI Strategy
It’s Not a Project, It’s a TransformationWhat “Scaling AI” Really MeansPrerequisites: The Conditions You Must Have Before ScalingThe AI Adoption FlywheelYour Scaling Architecture: Centralized, Federated, or HybridRemoving Blockers That Prevent ScaleKey Takeaways
Index

Content preview from Your New Colleague is a Copilot: Aligning Technology, Talent, and Trust

J. MatfessYour New Colleague is a CopilotInside Copilothttps://doi.org/10.1007/979-8-8688-2619-1_5

5. Iterate

Jared Matfess¹

Jared Matfess

Email: Jared.Matfess@avepoint.com

Move fast and break things. Unless you are breaking stuff, you are not moving fast enough.
—Mark Zuckerberg
Founder, Chairman, and Chief Executive Officer (CEO) of Meta Platforms, Inc.

Move Fast and Break Things

You have inspired people to care about AI, and you have built a business case that leadership can stand behind. You have gauged your readiness across data, operations, and culture so that you are not walking into risk with your eyes closed. You have selected pilots that are meaningful, responsible, and positioned to win. This is the ...

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Your New Colleague is a Copilot: Aligning Technology, Talent, and Trust

by Jared Matfess

5. Iterate

Move Fast and Break Things

Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.