AI in Energy Week Deep Dive Focus Day - March 1, 2027
Join your peers in a series of intimate, expert-led workshops designed to enhance your learning through hands-on discussions and practical problem-solving. With 12 interactive workshops to choose from, you'll gain actionable insights and practical strategies on advancing AI applications across energy operations.
7:30 am - 8:00 am
AI in Energy Week Deep Dive Focus Day - Registration Opens & Networking Breakfast
8:00 am - 9:30 am
Workshop A: Just Because AI Can, Should It? Making Smarter Decisions About AI Deployment
As AI capabilities rapidly expand, organizations have more opportunities than ever to automate tasks, accelerate decision-making, and transform operations. Yet the most successful AI initiatives are not always those that automate the most. This interactive workshop challenges participants to think critically about where AI delivers genuine business value, where human expertise remains essential, and how to make informed deployment decisions that balance innovation with practical outcomes.
• When does AI enhance human performance, and when does it diminish it?
• What are the risks of automating processes simply because technology allows it?
• How can organizations distinguish high-value AI opportunities from AI for AI's sake?
• What role should people play in oversight, decision-making, and accountability?
• How can leaders create a consistent framework for evaluating AI investment and deployment decisions?
TAKEAWAY:
Leave with a practical decision-making framework for determining where AI adds genuine value, where human expertise and oversight remain essential, and where automation simply isn't the right answer.
8:00 am - 9:30 am
Workshop B: Turning AI Investments into Measurable Business Value
Arundhati Biswas -
Senior Director, IT Strategy and Business Operations,
National Grid
As AI investment grows, the pressure is on to prove what is actually delivering value. This interactive workshop explores how organizations can prioritize high-impact opportunities, build stronger business cases and connect AI investments to measurable operational and financial outcomes.
• How do you define value before investing in AI?
• Which metrics best demonstrate operational and financial impact?
• How can organizations prioritize high-value opportunities over AI for AI's sake?
• How do you translate productivity and time savings into tangible business value?
• When should an AI initiative be scaled, adapted or stopped?
TAKEAWAY:
Build a clear framework for defining the value of AI, translating productivity and operational improvements into measurable outcomes, and deciding which initiatives to scale, adapt or stop.
8:00 am - 9:30 am
Workshop C: Establishing Governance Without Slowing Innovation
Larry Winters -
Director, AI, Data & Digital Transformation,
ONE Gas
AI governance has become one of the industry's most discussed topics, yet many organizations still struggle to define what it means in practice. While leadership teams want guardrails around security, compliance and risk, operational teams are concerned that governance can slow experimentation and delay value creation. This interactive workshop explores how organizations can build governance models that enable innovation rather than restrict it.
• What is AI governance, and why do organizations define it differently?
• How do we create governance that enables innovation instead of slowing it down?
• What levels of validation and human oversight are appropriate for different use cases?
• How should organizations govern AI agents and autonomous systems?
• What governance models successfully scale from pilots to enterprise deployment?
TAKEAWAY:
Develop a practical governance approach that applies the right level of guardrails, validation and human oversight to different AI use cases without creating unnecessary barriers to experimentation and innovation.
9:30 am - 9:45 am
Networking Break
9:45 am - 11:15 am
Workshop D: Combining Physics, AI & Digital Twins to Optimize Asset Performance & Advance Intelligent Operations
Explore how hybrid digital twins can combine physics-based simulation, AI/ML and real-world operational data to create a deeper understanding of asset behaviour. This workshop will examine how these capabilities can support virtual sensing, predictive insights and more informed asset-management decisions.
TAKEAWAY:
Discover how to combine physics, AI and operational data through hybrid digital twins to better understand asset behaviour, anticipate performance issues and improve operational decision-making.
9:45 am - 11:15 am
Workshop E: Seeing What Humans Can't: Applying Computer Vision Across Energy Operations
From identifying equipment anomalies and defects to improving inspection and operational visibility, computer vision is creating new ways to monitor complex industrial environments at scale. This workshop explores where computer vision can add the greatest operational value, what is required to move from a proof of concept into the field, and how organizations can turn visual data into actionable operational intelligence.
TAKEAWAY:
Build a practical roadmap for identifying, prioritizing and deploying high-value computer vision use cases across asset inspection, anomaly detection and operational monitoring
9:45 am - 11:15 am
Workshop F: Building Agentic Workflows That Deliver Real Business Value & Transform Operations
AI agents are moving beyond answering questions to reasoning, accessing knowledge, coordinating tasks and taking action across increasingly complex workflows. This workshop explores how agentic AI can augment employees, automate multi-step processes and support faster decision-making across business and operational environments, while examining what organizations need to successfully integrate agents into day-to-day work.
TAKEAWAY:
Gain a practical understanding of how AI agents are reshaping workflows, where human expertise fits alongside increasingly autonomous systems, and what foundations are needed to put agentic AI to work successfully.
11:15 am - 12:00 pm
Networking Lunch Break
12:00 pm - 1:30 pm
Workshop G: Using Causal AI to Understand What's Driving Operational Performance to Move Beyond Prediction
Traditional AI and analytics can identify patterns and predict what might happen next, but operational teams increasingly need to understand why an outcome is occurring and what action could change it. This workshop explores how causal AI can help organizations uncover the relationships driving operational performance, explain deviations from normal conditions and evaluate potential interventions before decisions are made.
TAKEAWAY:
Leave equipped with a practical understanding of how to move from predicting operational outcomes to identifying their underlying drivers and determining which interventions are most likely to improve performance.
12:00 pm - 1:30 pm
Workshop H: Using AI to Transform Asset Maintenance & Reliability by Predicting it Before it Fails
AI and machine learning are enabling operations teams to move beyond reactive and time-based maintenance towards earlier detection of equipment degradation and potential failure. This workshop explores how predictive maintenance can turn asset, sensor and maintenance data into actionable insights, enabling teams to intervene earlier, reduce unplanned downtime and make smarter maintenance decisions.
TAKEAWAY:
Discover how to move from reactive and scheduled maintenance towards an AI-enabled predictive approach that identifies emerging asset issues earlier, improves maintenance planning and strengthens reliability.
12:00 pm - 1:30 pm
Workshop I: From Data Chaos to AI-Ready: Connecting & Contextualizing Industrial Data
Industrial data is often fragmented across operational systems, engineering documents, time series, maintenance records and enterprise platforms, making it difficult for AI to understand the full context of an asset or operation. This workshop explores how organizations can connect, contextualize and enrich industrial data to create a trusted, reusable data foundation capable of supporting analytics, AI and increasingly agentic workflows.
TAKEAWAY:
Build a clearer roadmap for turning siloed industrial data into connected, contextualized and AI-ready intelligence that can be reused across operational use cases, applications and AI agents.
1:30 pm - 1:45 pm
Networking Break
1:45 pm - 3:15 pm
Workshop J: Building an AI Strategy That Delivers: A Roadmap That Adapts as Technology, Regulation, and Business Priorities Evolve
Matthew Alberts -
Manager, Innovation and Emerging Technologies,
Southern Company
As AI capabilities evolve at unprecedented speed, organizations face a growing challenge: how do you build an AI strategy that remains relevant amid changing business priorities, regulatory requirements, cybersecurity constraints, and emerging technologies?
Drawing on Southern Company's experience deploying hundreds of AI initiatives across generation, transmission, distribution, customer operations, and corporate functions, Matthew shares a practical framework for identifying high-value opportunities, prioritizing investments, and building an innovation roadmap that delivers measurable operational impact.
• Develop a structured approach to evaluating and prioritizing AI investments based on operational value, business need, and organizational readiness.
• Learn how to balance innovation with governance, cybersecurity, regulatory requirements, and business constraints while maintaining momentum.
• Build an adaptable AI roadmap that can evolve alongside emerging technologies, workforce challenges, and changing business priorities.
TAKEAWAY:
Leave with a practical roadmap for building an AI strategy that can adapt as technologies, regulations and business priorities change, without losing sight of measurable operational value.
1:45 pm - 3:15 pm
Workshop K: Prioritizing High-Value AI Use Cases
Jonathan Alexander -
Global Manufacturing AI & Advanced Analytics Manager,
Albemarle
As AI capabilities continue to evolve at unprecedented speed, organizations face a growing challenge: deciding what to invest in, what to scale, and what to wait for. Technologies that appear highly differentiated today can quickly become embedded platform capabilities tomorrow, making it increasingly difficult to identify where long-term value will be created.
Drawing on lessons learned from scaling AI initiatives beyond the pilot phase, Jonathan explores how organizations can identify high-value opportunities, invest in the right foundations, and build an AI strategy that remains relevant as technologies, business priorities, and market expectations continue to evolve.
• Build a framework for identifying and prioritizing AI opportunities with the greatest business value.
• Understand how to distinguish between short-term technology trends and long-term strategic investments.
• Learn how to balance experimentation, innovation, and execution while creating the foundations required for AI at scale.
TAKEAWAY:
Build a clear framework for comparing AI opportunities, identifying where the greatest long-term value lies, and making more confident decisions about what to invest in now, scale next or wait for.
1:45 pm - 3:15 pm
Workshop L: AI Enablement 2.0: Building an Enterprise-Wide Workforce Transformation Program
Taylor Witt -
Vice President, Digital and PMO,
energyRe
As AI adoption matures, many organizations are discovering that technology is no longer the primary challenge. The real barrier is enabling employees to understand, adopt, and apply AI in ways that are meaningful to their role. In this interactive workshop, Taylor shares energyRe's AI Enablement 2.0 framework, including how the company is measuring adoption, developing AI fluency, and creating personalized pathways to move employees from experimentation to transformation.
• Build an AI enablement program that drives behaviour change, not just tool adoption, including practical approaches to AI fluency, hands-on training, and department-specific use cases
• Learn how to identify, measure, and accelerate AI adoption across the workforce, using maturity models, engagement metrics, and targeted interventions for both non-adopters and power users
• Discover how to uncover high-impact AI use cases at scale, moving beyond surveys and generic training to role-specific coaching, workflow analysis, and employee-led innovation
TAKEAWAY:
Develop a practical approach for measuring AI readiness and adoption, building role-specific AI capabilities, and moving employees from initial experimentation to meaningful changes in how work gets done.
