World Congress 2026 Europe - Virtual Stage • Jul 2, 2026 • Session details

AI and Agility: The Dynamic Duo for Disruption

Christopher May

Why do 70% of enterprise AI projects fail? Survive disruption by evolving agile frameworks to treat AI agents as official team headcount and multiply development velocity.

Pause
Mute Enter Fullscreen
#1 about 3 min

AI adoption barriers and process struggles

Why organizations fail to achieve value from investments due to unaligned human workflows and legacy structures.

#2 about 4 min

Rewards and potential disruption risks of AI

Balancing massive efficiency gains against future cybersecurity vulnerabilities and shifting workforce models.

#3 about 3 min

Enabling hyperagility multipliers through agentic tools

How automated systems compress iterative feedback loops and permanently supercharge agile team velocity metrics.

#4 about 3 min

Core dimensions of supercharged accelerated prototyping

Leveraging dynamic data simulations and real-time generation to test complex hypotheses in hours rather than weeks.

#5 about 4 min

Combining emotional intelligence with processing power

Why nuanced human judgment pairs perfectly with the endless pattern recognition capabilities of large models.

#6 about 4 min

Five essential human capabilities for machine collaboration

Adapting continuous learning, prompt engineering, and ethical governance to validate machine-generated solutions securely.

#7 about 2 min

Integrating intelligent support into modern agile practices

Enhancing everyday team rituals using project risk assessment trackers and fully automated retrospective summaries.

#8 about 4 min

Analyzing how tech leaders deploy agile automation

How data-driven deployments optimize functional feedback cycles inside top modern enterprise architectures.

#9 about 2 min

Evaluating current enterprise artificial intelligence production maturity

Bridging the massive execution gap between struggling early proof of concepts and robust functional deployments.

#10 about 5 min

Shifting responsibility to top-down operational strategy mandates

Constructing formal governance frameworks and role expectations instead of relying exclusively on localized team experiments.

#11 about 2 min

Self-assessing organizational readiness for functional algorithm scaling

Measuring internal systemic capacity through standardized evaluation parameters to identify necessary operational growth paths.

#12 about 5 min

Three foundational phases of enterprise-wide strategic adaptation

Progressing consistently from clean data architecture foundations towards fully measured operational innovation labs.

#13 about 6 min

Proactive resolutions for systemic infrastructure and compliance bottlenecks

Combatting inherently poor model output through strict centralized data validation and comprehensive change management upskilling.

#14 about 4 min

Top baseline behaviors among competitive market leaders

Why integrating deep cultural investments directly connects to extremely fast execution speed and reliable deployments.

#15 about 4 min

Developing healthy sustainable environments for localized experimentation failures

Embracing transparent continuous experimentation missteps directly into the core corporate development lifecycle to fuel insight.

#16 about 5 min

Constructing the unified dual-track agentic operating model

Splitting discovery hypotheses logically from continuous production delivery loops and infrastructure health monitoring.

#17 about 3 min

Rebuilding daily sprint ceremonies around measurable hypothesis tracking

Modifying standard iterative progress updates into strict tactical feedback checkpoints targeting model accuracy and precision.

#18 about 2 min

Comparing traditional software delivery increments to neural workflows

Transitioning entirely away from fixed feature requirements toward constantly adjusting business KPI generation targets.

#19 about 3 min

Final technical pillars to ensuring ethical sustainable deployments

Guaranteeing properly robust automated reliability pipelines remain fully combined with clear explainability thresholds before shipping.

Matching moments

2:08 min

The collaboration gap between AI influence and agile processes

Vera Slavnić Vera Slavnić · Europe 2026 Virtual

3:01 min

Adapting team structures and agile workflows for agentic tools

Clemens Wasner Clemens Wasner +4 · World Congress 2026 Europe

5:29 min

Redefining the scrum master role as an AI orchestrator

Vera Slavnić Vera Slavnić · Europe 2026 Virtual

1:47 min

The growing necessity of orchestrating AI in software teams

Vera Slavnić Vera Slavnić · Europe 2026 Virtual

4:08 min

Transitioning software engineering teams to AI-native development workflows

Florian Deter Florian Deter +4 · World Congress 2026 Europe

2:16 min

Shifting from individual to organizational productivity

Ajita Kanchivakam Ananth Ajita Kanchivakam Ananth · World Congress 2026 North America

Upcoming sessions on this topic

Open session

AI Is the Easy Part: Why Faster Engineers Don't Make Faster Businesses

  • Bharat Sharma

    Booking

    Senior Engineering Manager

Open session

What If AI Helps Us Build the Wrong Product Faster?

  • Sekhar Burra

    Sain Innovation

    CEO

Open session

How is SWE & EM roles are changing in the age of AI

  • Amol Sharma

    Stripe

    Engineering Manager

Open session

Beware of Strangers Bearing Code: Open Source Trust in the Agent Era

  • Vikram Vaswani

    Consultant

Open session

Autopsy of an Autonomous Incident: When the Agent Made It Worse

  • Navin Pai

    StackGen

    Director of Engineering

Open session

Architecting Trusted AI: Coupling Multi-Agent Systems with dbt Semantic Store for Zero-Hallucination

  • Pushkar Mishra

    J.P. Morgan

    Senior Vice President