Energy & Utilities AI Use Case Ranking

Fastagger, an African deep-tech startup, has developed a mobile AI business assistant to empower small and medium businesses (SMBs) in Africa. Addressing the challenge of unreliable internet and limited digital infrastructure, Fastagger’s solution runs AI models efficiently on affordable smartphones without requiring a continuous connection. The AUNI system is embedded into Safaricom’s M-PESA Business App, supporting over 2,500 MSMEs in Kenya. This on-device agent enables customer engagement automation, loyalty management, and business coaching.,The AI assistant reduces previously manual processes from eight steps to just two, driving operational efficiency and customer retention. Microsoft’s Africa Transformation Office and NVIDIA have supported Fastagger with mentorship and resources, accelerating the deployment of this mobile-based AI. Key partnerships and the integration with tools like Azure AI, Azure IoT, and GitHub enable robust on-device machine learning. Real-world results underscore substantial improvements in SMB engagement, financial tracking, and growth opportunities, enhancing digital access for underserved populations.,By decentralizing access to AI, Fastagger brings business intelligence and automation to bandwidth-constrained and rural environments—making it easier for SMBs to track customer data, streamline marketing, and make data-driven decisions. The SaaS product costs just $1 to $5 per month, making advanced technologies affordable for local entrepreneurs.,The project illustrates how Microsoft technologies and strategic partnership can close Africa’s digital divide, offering repeatable digital business models to other regions. Fastagger’s infrastructure is available globally via Azure, expanding its impact beyond Africa. Participant feedback validates the significant value of democratized, mobile-first AI for emerging markets.

Axpo, Switzerland’s leading renewable energy producer, undertook a digital transformation to enhance power grid operational efficiency. Facing challenges with decentralized, slow asset information retrieval over a 2,400 km high-voltage grid with 90,000+ assets, Axpo developed the web-based 'Insights' platform. Leveraging Microsoft Azure Cognitive Search, Azure Maps, Power BI, Azure IoT Edge/Hub, and Azure Data Factory, the platform provides real-time asset data, AI-based drone image analysis, SCADA integration, and incident management, enabling faster and safer asset monitoring and predictive maintenance.,Key integrations enabled engineers and maintenance teams to visualize assets geographically, rapidly locate faults, and streamline both manual and drone inspection processes. The Incident Management Module improved crew response and communication. Results include a 99% reduction in asset information search times, safer line inspections via drones, and stepwise progress toward predictive maintenance, supporting grid reliability for Switzerland and Liechtenstein.

Ainwater builds Poseidón, an AI-based predictive management solution for drinking water, wastewater, and desalination.,The company moved the pilot into a scalable multi-tenant SaaS architecture on AWS, embedded machine learning and generative AI into the product, and expanded the service across plants in Chile, Mexico, and Brazil.,The solution provides operational recommendations and predictive insights to help water treatment operators shift from reactive to predictive management.

Quantum Capital Group supports a portfolio company operating in the Piceance Basin of western Colorado, where energy exploration and field development planning are constrained by difficult terrain, land restrictions, and existing infrastructure.,The company replaced a manual geospatial planning workflow that took about three weeks for a single development scenario and about six weeks to compare scenarios with an automated AI-driven tool built on Microsoft Azure. The tool uses an embedded Copilot Studio agent as a conversational interface for engineers and business stakeholders.

Ningbo Deye Technology Co., Ltd. built a multilingual AI customer service system on AWS to support users across more than 110 countries and regions.,The article says the company also deployed an AI assistant for power-trading optimization and broader global cloud operations.,With help from AWS partner Goclouds, Deye implemented an omnichannel customer contact center using ConnectNow and Amazon Bedrock.

MeanderX is a Germany-based renewable energy intelligence company that uses Google Cloud AI to turn fragmented public grid and permitting documents into actionable insights for developers.,The company built an automated data processing agent with Agent Development Kit (ADK) that scrapes thousands of public documents, stores them in Cloud Storage, searches them with Vertex AI Search, and uses Gemini OCR and Gemini models to extract text and identify grid-relevant entities.,The structured output is stored in Cloud SQL and used to help customers find optimal land and secure leases and permits earlier in the development cycle.

ENGIE Digital built the Robin Analytics and Agathe predictive maintenance platforms for thermal power plants and B2B customer equipment.,The platforms use AWS services including Amazon SageMaker, Amazon S3, AWS Glue, and Amazon Athena to develop, train, and deploy predictive maintenance models at scale.,The architecture supports a large number of assets and models while emphasizing scalability, security boundaries, and controlled costs.

Amazon Logistics Sustainability Engineering leads deployment of Electric Vehicle Charging Points across delivery station network.,Region-specific regulations and internal technical specs required manual cross-referencing of engineering parameters before proposals could be assessed.,The team built a generative AI-assisted design review portal using Amazon Bedrock Automated Reasoning checks and Claude in Amazon Bedrock to extract proposal data, translate specifications into formal policy rules, and verify compliance.

rSTAR Technologies delivers intelligent, enterprise-grade solutions across the Microsoft ecosystem, integrating Azure, Dynamics 365, Entra ID, Key Vault, and Copilot to accelerate innovation in AI, customer experience, cybersecurity, and IT modernization.,rSTAR empowers organizations to unlock new value, streamline operations, and scale transformation through Microsoft technologies.,They provide AI-powered chatbots and virtual assistants that reduce call volumes, automated email response systems, on-screen AI feedback tools, and centralized knowledge bases to improve customer service.,Their Agentic AI systems automate workflows across platforms such as ServiceNow, Oracle CC&B, and SAP, built on Azure AI Foundry with multi-agent architectures designed for regulated industries.,The solutions integrate ERP, CRM, and legacy systems using Azure services enabling seamless data flow and operational efficiency.

Abu Dhabi National Oil Company (ADNOC) undertook a digital transformation to address the demanding challenges of global energy supply, decarbonization, and minimizing operational downtime. By deploying AI-powered platforms, including ENERGYai and Neuron 5, ADNOC capitalized on Microsoft Azure technologies and autonomous AI agents to modernize its operations. These platforms were developed through collaboration with Microsoft and AIQ, focusing on seismic analysis, predictive asset maintenance, and optimization of energy usage.,The new AI-driven processes enabled real-time insights and actionable analytics. Predictive maintenance capabilities led to rapid identification and resolution of issues, while autonomous agents continuously monitored and optimized energy use. Workflows that previously took months were accelerated to days or minutes, boosting efficiency.,The company saw a significant reduction in unplanned downtime—up to 50% at one plant, more sustainable and reliable operations, and enhanced workforce empowerment using the unified OneTalent platform. Streamlining over 16 legacy HR processes, the company aligned talent and strategic goals, nurturing innovation and capacity. AIQ served as the consulting and implementation partner.,Broad use of Azure OpenAI and Azure Machine Learning put ADNOC at the forefront of energy sector digitalization. The intelligent platforms not only improved plant reliability and productivity but also made substantial progress in sustainability.

PGS is an integrated marine geophysics company based in Norway, with offices in 14 countries. It maps the ocean subsurface to support offshore renewables and carbon storage.,The company expanded its high-performance compute environment on Google Cloud, moving seismic imaging workloads from an initial lift-and-shift approach to a cloud-native architecture centered on Google Kubernetes Engine.

Copel, a leading Brazilian energy company, transformed its data access strategy with Google Cloud generative AI technologies and large language models.,The company built a virtual agent that connects to its on-premises SAP ERP system and lets employees ask natural-language questions to retrieve timely insights from enterprise data.,The solution replaced manual processes involving RPA tools and Excel exports, improving speed, consistency, productivity, and decision-making.

Orica modernized its SAP and analytics environment on Google Cloud to improve performance, resilience, and data-driven planning across its global operations.,The company migrated SAP workloads with Google Cloud Professional Services Organization support, used BigQuery and Cortex Framework for data transformation, and used Vertex AI for proprietary machine-learning-based demand planning and sales forecasting.,Orica reported faster SAP response times, shorter backup windows, and improved monthly planning and forecast accuracy.

Carrier Global Corporation is using generative AI to scale its Abound Net Zero Management product for a global audience.,Customers upload utility bills in local languages, which are extracted and processed to generate actionable energy-saving and emissions insights.,The solution is in pilot and is intended to help customers manage energy consumption and reduce carbon footprints.

Epilot, based in Cologne, Germany, provides an XRM solution for the energy industry that helps energy suppliers, municipal utilities, grid operators, and solution providers simplify, digitize, and scale operations.,The company built a serverless AWS architecture to summarize long email threads, helping sales and service teams quickly identify needed actions in complex customer communications.

So Energy is a UK-based renewable electricity supplier serving around 300,000 homes.,The company implemented Amazon Connect email-to-case to manage customer issues from initial contact through resolution, with a unified view of each customer's journey across billing queries, service disruptions, and solar and EV charging support.

Tata Power Center of Technology Excellence (CoE), with Oneture Technologies as AI analytics partner, built an AI-powered inspection platform for solar rooftop installation operations.,The solution automates end-to-end inspection workflows that were previously manual, error-prone, and inconsistent across teams as installation volume scaled.

Iberdrola, a global utility company, applied agentic AI to IT operations to improve change request validation, incident enrichment, and change model selection.,The solution uses Amazon Bedrock AgentCore with LangGraph-based agents, MCP-style tool gateways, identity, memory, observability, Amazon ECR, Amazon S3, Amazon RDS with pgvector, Amazon Bedrock models, Amazon Bedrock Guardrails, ServiceNow integration, and Amazon EKS-based tracing.,The implementation runs production-ready agents inside Iberdrola’s enterprise security and VPC environment to support multi-step workflows across departments.

Schneider Electric is transforming its energy management and industrial automation processes by deeply integrating generative AI through Microsoft Azure OpenAI Service. Key initiatives include Resource Advisor Copilot for comprehensive data analysis and decision support, Jo-Chat GPT as an internal assistant, Finance Advisor for financial teams, Knowledge Bot for customer support, and conversational search for product discovery. These use cases improve analysis, streamline operational workflows, automate customer care, and foster innovation. By embedding AI capabilities directly into its tools and processes, Schneider Electric supports sustainability, increases operational efficiency, and empowers both customers and employees. Early adoption of generative AI and the establishment of an AI hub have positioned Schneider Electric as a technology leader in the sector. The company also leverages the scalability and security of Azure cloud and is exploring further Copilot integration for offer development and frontline empowerment.

Uniper, a major player in the energy sector, collaborated with Celonis and Microsoft to undertake a comprehensive digital transformation of its business processes. The project aimed to achieve operational excellence, transparency, and streamlined workflows using advanced AI and automation technologies. By integrating Microsoft Copilot Studio, Power Automate, and Microsoft Fabric with the Celonis Process Intelligence platform, Uniper deployed AI-driven process orchestration across 27 mission-critical business functions. Over 350 users interact with the system, connecting to multiple enterprise data sources.,The project involved end-to-end process improvements, from plant maintenance and HR to IT service management and financial reporting. Uniper realized tangible results, including increased workplace safety, shortened recruiting cycles, faster IT response, and enhanced reporting. The approach also set a blueprint for AI adoption in the broader energy industry.,This collaboration demonstrates how the interplay of Celonis workflow intelligence and Microsoft AI technologies enables scalable, intelligent automation tailored for complex environments like energy production and distribution. The article details real-world outcomes, positioning Uniper as a leader in leveraging AI for large-scale operations.