Transportation agencies face pressure to improve safety outcomes while budgets are constrained and systems grow more complex.

This session will explore approaches you can apply to digitize planning-to-operations workflows so you can reduce risk, improve coordination, and deliver safer road experiences.

• Advance safety outcomes by using data and modeling to identify high-risk corridors earlier.
• Transform roads into responsive systems using sensors and signals that adapt in real time to conditions and safety risks.
• Improve incident response by leveraging live data to anticipate congestion and coordinate proactive interventions.
• Reduce accidents and delays by applying analytics to uncover patterns and enable earlier interventions.

AI reshapes how threats emerge, scale, and propagate across government systems, creating new attack surfaces and adversarial capability.

This session will clarify what you need to secure so you can adopt AI without losing control, visibility, or public trust.

• Assess AI-driven threats such as automated phishing, deepfakes, and adversarial attacks targeting infrastructure and AI systems.
• Reduce risk by protecting data pipelines, training datasets, and models against poisoning, leakage, and extraction.
• Improve governance by embedding risk management and security controls across data, models, and operational deployment.
• Strengthen resilience through continuous monitoring for anomalies, model drift, and emerging threats.

AI solutions must be built around real government workflows and user needs, not idealized process maps.

This session will show how you can design human-centered AI that fits compliance and system constraints so you can drive adoption across diverse user groups.

• Improve outcomes by applying human-centered AI design in public sector contexts.
• Reduce friction by balancing usability with compliance and accessibility requirements.
• Optimize integration by fitting AI into existing service delivery systems without disrupting operations.
• Strengthen adoption by designing for diverse user groups and assisted pathways where needed.

Security cannot be an afterthought in AI systems, especially as multi-vendor environments expand the blast radius of weak controls.

This session will outline secure-by-design patterns you can apply so you can scale AI safely across agencies and partners.

• Advance Zero Trust principles for AI-enabled environments.
• Improve protection across data, models, and outputs throughout the lifecycle.
• Optimize compliance by mapping security controls to regulatory expectations.
• Reduce vendor and ecosystem risk through shared responsibility and assurance evidence.

Arizona is deciding how AI will be controlled, governed, and trusted before it scales across a federated environment.

This session will examine the control-layer choices you can make so you can scale AI as a force multiplier instead of a systemic risk.

• Assess ownership and accountability models for AI risk, decisions, and outcomes across agencies, including where human-in-the-loop review is required.
• Improve enforceability by connecting data inventory and classification to decision control, not just visibility.
• Reduce risk by establishing guardrails for bias management, model transparency, human-in-the-loop escalation, procurement, and auditability before scale.
• Advance operational governance by embedding controls into workflows, systems, and cross-agency collaboration.

As AI becomes embedded in government systems, responsibility for cyber risk becomes distributed and harder to enforce.

This session will clarify how you can define and operationalize shared responsibility so you can protect AI systems as they scale into real-world operations.

• Assess how responsibility is divided across pipelines, models, infrastructure, and endpoints.
• Reduce exposure by protecting training data, models, and outputs from manipulation, leakage, and unauthorized access.
• Improve enforceability by aligning responsibilities across internal teams and external partners.
• Optimize response by operationalizing continuous monitoring, detection, and rapid incident handling as systems evolve.

Securing approval is only the beginning; delivering AI at scale requires navigating integration, adoption, and execution realities.

This session will outline what you can do after funding is secured so you can move from approved initiatives to fully deployed, high-impact solutions.

• Improve deployment by ensuring AI solutions connect with existing systems, data environments, and workflows.
• Strengthen adoption by equipping the workforce with skills, confidence, and in-the-flow support.
• Optimize procurement by structuring approaches for flexibility, iteration, and continuity through scaling.
• Advance sustainability by embedding solutions into daily operations across agencies.

Compliance-first security models are struggling to keep pace as cloud complexity grows and AI-enabled threats move faster than traditional controls.

This session will outline practical shifts you can make to build proactive resilience so you can reduce exposure, improve response, and target investments where risk is highest.

• Assess where checkbox compliance creates blind spots across identity, endpoints, and critical services.
• Reduce risk by implementing control-based practices that verify security outcomes, not just policy adherence.
• Improve detection by applying AI and automation to surface anomalies, prioritize alerts, and shorten investigation time.
• Optimize cyber investment by aligning spend to the highest-risk scenarios and measurable resilience metrics

Roundtable Discussions for Government

Pick your topic. Pull up a seat and join a 45‑minute interactive discussion with your government peers. Facilitated by an industry expert, you’ll share challenges and swap practical approaches within the topic area. Take this opportunity to benchmark what good looks like, pressure-test ideas, and workshop next steps together.

1. Preparing Data for AI - IBM
2. GenAI & Analytics in Government
3. Public-Private Collaboration That Works
4. The AI Journey End-to-End
5. Data Inventory to Shared Assets
6. Governance as Guardrails (Not Gates)
7. Operationalizing Trust in AI
8. From Compliance to Control

2:15 PM - Knowledge Sharing and Feedback

A quick-fire share-back: we’ll take the mic around the room for the top takeaways from each roundtable, so you can catch the insights from sessions you missed before reconvening for the rest of the conference.

How Arizona Buys: What Government Is Funding Now and What Procurement Teams Look For

Buying patterns in Arizona are shifting as agencies modernize platforms, strengthen cybersecurity, and move from pilots to scalable data and AI capabilities.

This session will break down current buying trends so you can understand what’s being funded, how decisions get made, and what procurement teams need to see to move forward with confidence.

• Assess where spend is concentrating across platforms, cybersecurity, data modernization, analytics, and AI enablement.
• Identify the evaluation signals Arizona procurement teams prioritize (outcomes, risk, interoperability, security posture, and evidence of adoption).
• Clarify what “good” looks like in proposals: measurable value, implementation readiness, and realistic operating models for government.
• Improve alignment by mapping your approach to common buying pathways, contract vehicles, and approval realities across the state.