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AI Strategies for the Public Sector
Aligning Value, Governance and Data Readiness:
A Roadmap for Successful AI Implementation

This program is structured as a four-module, live-virtual executive workshop series, tailored to the strategic, governance and implementation interests of senior federal and provincial civil service executives in policy, strategy and IS/IM functions.

Outcomes:

• Accelerate digital transformation
• Enable human-centred, trusted and collaborative AI
• Reduce costs and risks
• Enable data-driven decision making
• Improve service delivery and drive innovation

Benefit from Custom Team Sessions:
Intervista relates emerging methodologies and architectures espoused by AI, Data Strategy and Governance experts and delivers these approaches and best practices in customizable programs tailored to your organization's key issues, skill gaps and pain points.

1. Generative AI: From Policy Mandate to Public Value This module focuses on the 'Why' and 'What' of AI at the executive level, linking technology to public sector mandates and high-level organizational strategy. AI Business Value, Digital Government & Public Impact Outcomes Understanding Large Language Models (LLMs) and Agentic AI capabilities and limitations Identifying High-Impact Use Cases: Shifting from efficiency to transformational service delivery (e.g., personalized citizen services, proactive policy compliance, regulatory modernization, decision-support) Measuring Public Value: Defining and tracking AI ROI beyond financial metrics (e.g., citizen trust, faster service, reduced bias, etc) Business Transformation Challenges: Adopting an 'AI-First' public service - reimagining workflows, organizational structures and workforce talent 2. Governance of AI: Trust, Ethics and Accountability This module addresses the 'How to Govern' AI, focusing on the unique legal, ethical, and accountability requirements of the public sector. The Canadian Federal Government context Bias Mitigation: Techniques for identifying and addressing algorithmic bias in high-stakes public decisions (e.g., funding allocation, risk assessment) Privacy Policies & Responsible Data: - Data Access vs. Privacy - Strategies for enabling data sharing across departmental silos to train better models while maintaining security, data residency and citizen privacy standards - Privacy-preserving AI: Concepts like federated learning and differential privacy for sensitive data AI Impact Assessments (AIIAs) - Mandatory processes for documenting, mitigating, and accepting risks before deployment Accountability and Explainability (XAI) - Establishing clear lines of accountability for algorithmic outputs and methods for explaining AI decisions to citizens and oversight bodies Procurement & Vendor Oversight - Governing the Black Box: Strategies for mandating transparency, auditability, and ethical compliance in COTS AI solution 3. Data Strategy: The Foundation for Successful AI Implementation This is the 'How to Architect for AI' module, grounding AI ambitions in practical data strategy, architectures, data stewardship and data management and deployment best practices. Data Readiness & Data Architecture Data Maturity Assessment: Benchmarking the organization's data quality, cleanliness, and metadata management against AI requirements Semantic Layers + Ontologies for AI: Operationalizing business meaning Data Architecture for AI: Understanding modern data stacks Managing security, data sovereignty and the AI-ready data centre in a Canadian Public Sector context Data-Driven AI-enabled Service Delivery AI-enabled Decision Automation: Identifying high-volume, low-complexity decisions suitable for end-to-end automation and ensuring human-in-the-loop oversight for complex decisions Data lifecycle management checklist for AI: collection + preparation, storage + accessibility, analysis + insight, model training + validation and performance + monitoring 4. Key Elements of the AI Roadmap AI and Business Architecture + Strategy; - Accelerating business process and decision support design + innovation Operationalizing Data Models: Moving from data science notebooks to fully managed, integrated AI services (MLOps) Change Management: Leading a cultural shift toward data-driven decision-making and acceptance of algorithmic assistance Addressing Implementation Challenges: Talent & Procurement Gaps Prioritizing AI Use-Cases Based On Value, AI Maturity and Feasibility Scaling from Pilot to Production: Overcoming the 'pilot purgatory' and standardizing platforms for enterprise-wide deployment Legacy Systems Integration for AI Ensuring Cybersecurity and Data Privacy at Scale Integrating The Critical Role of Human In The Loop (HITL): Using Design Thinking, Human Centred Design, and Personas for Successful and Relevant AI Applications Managing the AI Portfolio: Strategic Alignment, Prioritization, Resource Allocation, Risk Management and Value Optimization

Who should attend Deputy Minister Assistant Deputy Minister Director General Chief Information Officer Chief Technology Officer Chief Data Officer Chief Cybersecurity & Privacy Officer Chief AI Officer IT/IM Director Director, Digital Transformation Director, Artificial Intelligence Director, Business Intelligence Director, Information & Data Management Director, IT Governance Director, Digital Innovation Director, Product Management Enterprise Architect Business Architect Data & Information Architect Security Architect AI Consultant/Advisor Privacy Advisor IT/IM Manager AI Program Manager Product Manager AI Policy Manager Manager Program Risk & Ethics Business Analyst Policy Analyst

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Fees
$1995 per person (minimum of 10 people). Applicable taxes extra.

🍁 Intervista relates emerging AI methodologies and architectures and delivers these approaches and best practices in customizable programs tailored to your organization's key issues, skill gaps and pain points.

Contact us about how to schedule this program for teams of 10 or more.

Each participant will receive a certificate of completion.

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"The presentation was excellent and the instructor was fantastic. I got great value out of the material and was able to apply the knowledge gained to my current BI practices and dealings with Enterprise Architects. Thank you for bringing a sense of passion to material presented.."
Katherine Jenkins
Senior Program Officer
Border Services Agency

"Directly applicable to my work. I can apply what I learned immediately to improve results."
Adele McDonald
Former Enterprise & Data Architect
City of Edmonton

"Excellent course! Kent Bimson knows about the subject and his passion is contagious!"
Herve Ethier
Former Chief Information Officer
Human Rights Commission

"Thank-you John. Very informative and entertaining."
Joel Racicot
Senior Advisor, Architecture Centre of Excellence
Shared Services, Government of Canada

"Wonderful contextual explanation of semantics."
Ginny Nisbet
Enterprise Manager, Knowledge Management and Data Access
Saskatchewan Ministry of Environment

"Exactly the info I was after. How often does that happen?"
Mike Proudlock
Project Manager
Regin of Peel

"This was great! I am walking away with a million ideas!"
Connie Washburn,
Associate Professor, Business Information Systems
Georgia Perimter College

"An intellectually stimulating course offering that is addressing key concepts of tomorrow's enterprise architectures."
Robert Weisman, PhD, PEng, PMP, CD
CEO, Chief Architect, Build the Vision
Former Chief Information Architect, National Defence and Executive consultant/ EA Practice Lead, CGI

"Informative and engaging."
Derek Rutherford
Former Director, Application Architecture & Standards
Province of British Columbia

"Very though overview. Mr Chikofsky masters very well the subject matter and was able to provide pertinent examples contextualized to the Public Service reality."
Eric Lavergne
Director, Portfolio Management
Environment Canada

"Best, most useful training in a classroom!"
Regius Brown
Senior Advisor/ Manager Health
Canada