We are in the midst of a digital and operational technological revolution that dynamically influences productivity, boosting growth and influencing incomes in some sectors. On the other hand, it is also replacing jobs and deepening income inequality.

The rapid advance of artificial intelligence has captivated the world, causing both excitement and alarm. Important questions about its potential impact on the industrial sectors were raised. The full impact is not yet visible and will be difficult to see soon, as OT, AI, ML, and IIoT will ripple through industries in complex ways. We can say with some confidence that we must start now to develop regulations and operational policies to safely leverage the vast potential of AI for the benefit of all.

AI-powered industries are setting ambitious targets: reducing the sector's annual greenhouse gas emissions, energy consumption, and natural water consumption to meet changing regulatory targets. Using technology to help solve humanity's biggest problems, energy, and water, consistently tops the list.
While many other industries are becoming highly automated, many still rely heavily on human decisions. We can leverage technology to assume much of that burden by taking data from control systems and using it to understand your infrastructure and supply chain designs/functions in minute detail. It can then simulate how your operations could run better and make quality-informed decisions and predictions.

AI can send the information from all OT, IIoT, and LDAR devices back to the operations staff in real-time. Just like a coach, it's watching, analyzing all the data, and then giving analytics and insights through web-based platforms. AI and ML can now be trained to do much redundant and predictive analysis work across the operations and avoid spending hours analyzing the information. People's experience, skills, and tacit and explicit knowledge must be key in digital Ecosystem design and configurations.

"You can't fix or change what you don't measure,"

What Will You Learn?

Considerations for your operational roadmap for getting there: Your plan tenets, watchlists, etc. For example, partnering with facility owners, operators, and solution providers.

• Enable rapid deployment with low barriers to adoption— "a low-touch, low-risk model that allows facilities to quickly get started and provide strong realized benefits within a set timeframe.
• Understand the role of Business vs IT – how to invest in operational AI continuously. This includes automating operations intelligence at all locations. Business management must oversee and help them retrofit and make larger capital decisions that reduce their cost and greenhouse gas profile. This is not an IT management issue. Accountability and responsibilities are directly under business management.
• Look at operations differently and define a new category of facility operations that supports relevance through an economic, environmental, social, and business lens.
• Measuring what matters most, optimizing those metrics, deploying AI to accelerate retrofits, and using offsets to make retrofits more attractive to operators.
• Long-term AI strategies are here to stay. However, many software providers claim to use AI and machine learning, only to discover that their products simply do linear regression, a statistical method that aims to predict the future based on the past. We need to make our decisions that adapt to changing condition.

Caveat: You are NOT a software development company. Do not allow yourself to lose focus of your core business; do not expect quantum leaps or take vendor-influenced "quick fix" shortcuts to archive short-term "artificial" results. 

Who Should Attend?

Senior executives, Management, and those who want to understand the impact of integrating emerging Operational, IIoT, and Digital technologies and their ecosystem, incorporating automation, trust, and new accountabilities across their operations. 
Business Leaders who wish to:

• Leverage technology to change behaviours and culture, mentor/coach their business leaders to adopt and use emerging and adaptive technologies.
• Develop their roadmap to take advantage of an integrated ecosystem of exponential technologies to enable this current era of dynamic change and support the organizations' ability to react to change in near real-time, with trusted data and quality-informed decisions. 

Why Choose Our Workshop?

• Bringing the right mix of on-the-ground "cross-industry experiences" on what works Vs what is failing. 
• Applying proven functionalities of integrated technologies aligned with current skills, capabilities, capacities, and interactions, providing maximum benefit to the attendees. 
• Led by a hands-on practical advisor with over 35 years of experience in Oil and Gas, Energy, Mining, Transportation, Agriculture, Forestry, HHS, and Government optimizing operations, integrating OT, IT, DT, ML, and other emerging technologies.
• To understand the practical union and importance of cross-jurisdiction Integration, transition, effective consumption, emissions, and growth management

Workshop Agenda:

09:00 to 10:30 am Overview of AI Vs. Gen AI operating environment for Oil and Gas and Energy 

• The Key modalities of GenAI and ML, opportunities, and constraints 
• Preparing AI and ML to transform and enhance your organization while avoiding negative impacts on participants
• Identifying biases and creating trusting foundations of people, data, and knowledge.
• Leveraging AI to help industries curb their thirst for energy and water

10:30 to 10:50     Networking break

10:50 to 12:30 Using AI to solve problems, enhance products, improve customer experiences, and mitigate emissions

• Cutting through the hype - Technology leaders need to cut through the hype and comprehend what GenAI can – and cannot yet – achieve today Vs what it may enable in the future.
• Leveraging AI and ML to support automated workflows, Business functional processes, Compliance, Resource optimization to compliance and reporting 
• Developing AI-enabled support and enabling mechanisms, Managing for performance 

Group exercise – 15 mins 

12:30 to 13.30 Lunch

13.30 to 15:00 AI organizational readiness – Cultural and change barriers 

• Skills, capacity, capabilities and constraints, lessons from the Aircraft industry
• Configure, implement, operate, and maintain – What should be the role of Management, staff contracted resources, and vendors 
• Applying transformative technologies judiciously and building a more tech-savvy workforce of the future.
• Enabling GenAI, ML, IIoT, and OT for project success, decarbonization, and energy management
• Governance, analysis, reporting, and data optimization 

15:00 to 15:15 Wrap up and review of questions for follow-up