AI Adoption in Energy Should Focus on Agility, Not Algorithms By Thayer Adsit, Rohit Nalgirkar, Sylvain Santamarta, Ramya Sethurathinam, and Henning Streubel December 2024 Key Takeaways With AI and GenAI applications poised to revolutionize the oil and gas industry, companies must develop the capabilities to quickly and flexibly adopt these new technologies. This requires strong change-management efforts to reshape a company’s DNA around its people, processes, and culture—a significant shift for companies traditionally centered on physical assets. Many energy companies have adopted AI tools to support tasks like corporate report writing and to improve the quality and productivity of oil field operations and petro-tech disciplines. Future benefits will include using AI to promote major innovations. Deploying GenAI in everyday tasks, implementing AI and GenAI to improve critical processes, and inventing new business models focused on agility can help companies unlock the value of the technology. To realize sustained competitive advantage through AI applications, companies must provide access to quality data, foster a culture of experimentation that encourages innovation and risk-taking, and rapidly upskill workers. https://lnkd.in/dgpmrUpd
Khalid AL-Khateeb Strategist,Academic Advisor,AI,Business Strategist’s Post
More Relevant Posts
-
From transforming field operations to altering electricity demand, #AI offers vast opportunities for efficiency and innovation. But success depends on agility over algorithms. A new Boston Consulting Group (BCG) post highlights the need for energy companies to focus on people, processes, and culture to unlock AI's full potential. Read more here and let me know in the comments how you think AI is reshaping the energy sector: https://lnkd.in/gjz8QwDF via Thayer Adsit, Rohit Nalgirkar, Sylvain Santamarta, Ramya Sethurathinam, and Henning Streubel, PhD
AI Adoption in Energy Should Focus on Agility, Not Algorithms
bcg.com
To view or add a comment, sign in
-
Did you know AI-driven improvements could lower production costs and carbon intensity while transforming operations in oil fields? But here's the catch: Only 26% of companies are equipped to scale AI beyond the proof-of-concept stage. What’s the path forward? Start small: Deploy AI in everyday tasks to improve productivity. Think big: Reshape workflows for frontline efficiency. Act boldly: Invent new models to optimize cost and emissions. Transforming AI potential into real-world impact requires bold moves and a focus on agility. https://lnkd.in/g6jsYSqF #OilAndGas #AIinEnergy #DigitalTransformation
AI Adoption in Energy Should Focus on Agility, Not Algorithms
bcg.com
To view or add a comment, sign in
-
To launch an AI product successfully, you need a well-defined roadmap that aligns with your business objectives and customer needs. Here's a roadmap with key steps 🚀 : Define Your AI Vision and Objectives Clearly articulate the problems you want to solve with AI and the expected outcomes. Identify the specific areas where AI can drive value, such as improving operational efficiency, enhancing customer experiences, or enabling new business models. Establish measurable goals and success metrics to track progress. Assess Data Readiness and Maturity AI systems heavily rely on data, so assess the quality, availability, and accessibility of your data sources. Establish robust data governance practices and ensure compliance with relevant regulations. Invest in data infrastructure and pipelines to enable seamless data flow and integration.[1] Prioritize Use Cases and Develop AI Solutions Identify and prioritize the most promising AI use cases based on their potential impact, feasibility, and alignment with your objectives. Collaborate with cross-functional teams, including data scientists, engineers, and subject matter experts, to design, build, and test AI solutions. Leverage appropriate tools, technologies, and frameworks for model development, training, and deployment.[1][5] It's crucial to remember that AI is a powerful tool, but it should be used responsibly and ethically. Ensure transparency, fairness, and accountability in your AI solutions, and continuously monitor their performance and impact.[1] The success of an AI product heavily depends on the quality and connectivity of the data it's trained on. Establishing a strong data strategy and infrastructure is essential for enabling AI to deliver accurate and reliable results. This includes integrating diverse data sources, implementing robust data governance practices, and fostering collaboration between cross-functional teams.[1][4] Ultimately, AI should augment and enhance human intelligence, not replace it. Involve stakeholders, gather feedback, and iterate continuously to ensure your AI product aligns with user needs and ethical principles. How do you think AI could help in launching your next big product? #AI #ProductLaunch #TechInnovation #MarketSuccess #EnjoyTheJourney Citations: [1] https://lnkd.in/eemNTx4j [2] https://lnkd.in/eCyr2nAi [3] https://lnkd.in/ePVVdDD9 [4] https://lnkd.in/eEwv7Tcv [5] https://lnkd.in/ewhBtmpY
The AI revolution: How a strong data strategy is giving energy leaders an advantage
mnpdigital.ca
To view or add a comment, sign in
-
The era of AI dominance in energy is here. From powering operations to driving the energy transition, AI offers immense potential—but only for organizations willing to adapt. The secret? Agility beats technology. Move from assets to innovation. Adopt a people-first approach with 70% of resources focused on culture and processes. Break down data silos to accelerate AI's impact. Companies that master these will lead the charge into a sustainable, AI-powered future. What steps is your company taking to prepare? #OilAndGas #AIinEnergy #DigitalTransformation
AI Adoption in Energy Should Focus on Agility, Not Algorithms
bcg.smh.re
To view or add a comment, sign in
-
The era of AI dominance in energy is here. From powering operations to driving the energy transition, AI offers immense potential—but only for organizations willing to adapt. The secret? Agility beats technology. Move from assets to innovation. Adopt a people-first approach with 70% of resources focused on culture and processes. Break down data silos to accelerate AI's impact. Companies that master these will lead the charge into a sustainable, AI-powered future. What steps is your company taking to prepare? #OilAndGas #AIinEnergy #DigitalTransformation
AI Adoption in Energy Should Focus on Agility, Not Algorithms
bcg.smh.re
To view or add a comment, sign in
-
The era of AI dominance in energy is here. From powering operations to driving the energy transition, AI offers immense potential—but only for organizations willing to adapt. The secret? Agility beats technology. Move from assets to innovation. Adopt a people-first approach with 70% of resources focused on culture and processes. Break down data silos to accelerate AI's impact. Companies that master these will lead the charge into a sustainable, AI-powered future. What steps is your company taking to prepare? #OilAndGas #AIinEnergy #DigitalTransformation
AI Adoption in Energy Should Focus on Agility, Not Algorithms
bcg.smh.re
To view or add a comment, sign in
-
Have you been keeping up with how AI is transforming the energy industry? MNP has surfaced some of the most impactful AI use cases, how they’re changing the energy landscape, and what you need to do to catch up. Check out this great read to learn more: https://lnkd.in/gu2i9u-6 #AI #energyindustry #datapower #MNPinsights
The AI revolution: How a strong data strategy is giving energy leaders an advantage
mnpdigital.ca
To view or add a comment, sign in
-
Energy companies are increasingly leveraging AI to boost productivity, safety and advance sustainability. Under pressure to adapt quickly to changing demands, regulations and technologies, AI is emerging as a key tool to accelerate this pivotal moment-in-time to create efficient, safe and sustainable operations. https://hubs.la/Q02TQ2z-0 #AI #SafetyBoost #EnergyIndustry #canda #EnergyOptimizer #technology #operations
Transforming the energy industry with the power of AI - Source Canada
news.microsoft.com
To view or add a comment, sign in
-
Can AI be used to transform the energy industry? Yes, but while it holds great promise, solutions will only be as good as the data you feed them with. Here are some potential applications to get inspired by.
Using AI to supercharge operations in the energy sector
cognizant.com
To view or add a comment, sign in
-
AI and energy have a deeply symbiotic relationship. AI adoption is causing energy demand to surge globally. And, AI can drive innovation in sustainable solutions to this energy demand and smart data center solutions development. As AI continues to evolve and permeate various aspects of our lives, finding sustainable solutions to its escalating energy demands is imperative. Embracing innovation, prioritizing energy efficiency, and strategically harnessing AI's capabilities can pave the way for a future where technological advancement and environmental sustainability go hand in hand. I look forward to seeing concrete progress by World Economic Forum Artifical Intelligence Governance Alliance. #ai #energy #datacenters #wef #aihouse
The rapid global adoption of Artificial Intelligence is fueling a substantial increase in energy demand, largely driven by the need for expanding data centers to train and operate sophisticated AI models. While AI offers tremendous potential for innovation and societal progress, its burgeoning energy appetite poses a significant hurdle in the pursuit of a sustainable and decarbonized future. Let's have a look at AI's Energy Consumption by the Numbers: (1) AI is projected to trigger a 160% surge in data center power demand between 2022 and 2030, contributing considerably to the overall 2.4% increase in US power demand during that period. (2) By 2030, AI-driven data centers are expected to account for 8% of US power consumption, a significant jump from 3% in 2022. (3) The computational power required for AI is doubling roughly every 100 days, indicating an accelerating demand for energy. Training advanced models like GPT-4 already consumes an estimated 50 times more electricity than its predecessor, GPT-3. (4) Projections suggest that by 2028, AI's energy consumption could surpass that of entire countries, highlighting the scale of its impact on the energy landscape. The increasing energy demands of AI, coupled with population growth and electrification trends, are placing immense strain on the electrical grid. Ensuring grid stability and resilience in the face of this growing demand is a complex challenge requiring a multifaceted approach. While AI's energy consumption is a cause for concern, it also presents significant opportunities to optimize energy use and accelerate the transition to a clean energy future. AI's ability to analyze vast datasets and forecast energy production can be leveraged to enhance grid stability, optimize energy consumption, and integrate renewable energy sources more effectively. However, benefits should be probably be limited vs required energy demand. Addressing the intricate relationship between AI's energy use, its environmental impact, and its societal benefits requires a collaborative effort across industries and sectors. The World Economic Forum Artificial Intelligence Governance Alliance is actively working to establish a cross-industry framework to harness AI's potential for positive transformation while mitigating its energy footprint. As AI continues to evolve and permeate various aspects of our lives, finding sustainable solutions to its escalating energy demands is imperative. Embracing innovation, prioritizing energy efficiency, and strategically harnessing AI's capabilities can pave the way for a future where technological advancement and environmental sustainability go hand in hand.
To view or add a comment, sign in