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4 min read

4 Machine Economy Trends Disrupting the Energy Sector + How to Adapt

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Over the last decade, the energy sector underwent a great shift: going digital. 

Advancements in energy management software, energy optimization, energy forecasting and planning platforms, energy data analytics, and energy storage technologies brought new players into the market and created an entirely new energy landscape. 

Those who succeeded were able to use these technologies to modernize their operations, improve customer experiences, and make themselves more efficient. 

Now that these technologies are becoming increasingly affordable and mainstream, we’re on the verge of the next great energy shift. 

The Machine Economy will rapidly transform the energy sector 

Just as “going digital” was a game-changer in the last decade, the next great shift will be about “getting smart”. 

To understand the enormity of this shift, here are 3 statistics you need to be aware of:  

  • AI, machine learning, and robotics will drive 70% of GDP growth over the next decade.  

  • By 2030, AI will contribute an estimated $15.7 trillion to the global economy, more than the current output of China and India combined.  

  • 62% of leaders are putting plans in place to succeed in a world filled with connected machines and smart automation – 16% are already investing and performing strongly.  

It’s now clear that decision-making AI and machines will be the primary driver of economic growth over the next decade in what's being referred to as the "Machine Economy".  

This is especially true in the energy sector, where machines and AI can help energy companies increase energy generation, improve energy efficiency, and reduce wastage. These changes will also create new business models with higher margins if energy companies get smart about the opportunities. 

With so much at stake, it's vital to understand the 4 primary Machine Economy trends that are disrupting the energy sector, and how to adapt to each. 

The 4 primary technology trends that are transforming the energy sector in the Machine Economy 

The energy market, with its aging energy infrastructure, is an ideal candidate for the Machine Economy to help modernize systems, reduce wastage, and optimize performance. 

This transformation will be made possible by these 4 primary technological trends: 

  1. AI & Machine Learning

With all the new energy sources, energy trading, IoT devices, and energy management systems that are currently in place, energy companies have an unprecedented amount of energy data at their disposal. 

AI and machine learning are serving as the brains that can constantly analyze all this data and help energy companies make more informed decisions about how they operate energy networks, design energy systems, and maintain day-to-day energy use. 

  1. Robotics 

Robots are being used in energy installations and maintenance, and for monitoring energy generation and energy consumption. Robots can be used for tasks such as repairing pipelines, wind turbines, and other energy infrastructure. 

By automating these tasks, energy companies can further improve efficiency and reduce costs. 

  1. The Internet of Things (IoT)

In the energy industry, energy management platforms have been used for years to create energy efficiency and alleviate energy waste. These programs are now being augmented with machine learning to further increase energy conservation efforts as well as to predict energy use. 

Utilities need data from distributed energy sources and IoT devices to make this happen. These devices provide real-time energy use data that is fed back into the energy management platform to adjust energy usage patterns. 

  1. Blockchain

The energy sector is one of the most obvious markets for blockchain technology because it involves many different parties that use energy, trade energy, and maintain records about energy. 

Blockchain technology can be used to manage energy transactions and energy trading between energy producers and energy consumers, while ensuring security and transparency. 

Energy companies need to adapt quickly in order to remain competitive in the Machine Economy 

It's clear that the energy sector has a lot to gain from these four technologies – but only if they act quickly. 

The energy sector is in the early stages of the Machine Economy, and energy companies need to fully embrace these new technologies as fast as possible to get ahead and remain competitive. 

Data is the lifeblood of the Machine Economy  

The smarter the machines get, the more they can do for us, especially when they start engaging with each other autonomously to carry out production and distribution, without the need for human intervention.  

However, none of this is possible without data.   

Digital-first energy and utilities companies won in the last decade because they had fast access to reliable data. Now, these companies have a head start, as data is the key to unlocking the power of AI and machine learning. 

The more data you have, the smarter your systems will be. 

Data teams face daunting challenges in the Machine Economy 

Data volumes are exploding, but expectations for how fast data should be curated, prepared, and delivered for analysis and AI/machine learning haven’t changed.  

Many data teams are struggling to keep up. 

Traditionally, data management has relied on a highly-complex stack of tools, a growing list of data sources and systems, and months spent hand-coding each piece together to form fragile data “pipelines”.  

Then came data management “platforms” to the rescue. They promised to reduce complexity by combining everything into a single, unified, end-to-end solution.  

In reality, they impose strict controls and lock you into a proprietary ecosystem that won’t allow you to truly own, store, or move your own data.  

It’s clear that the old ways of doing data management simply cannot meet the needs of modern organizations.  

Data teams are in desperate need of a faster, smarter, more flexible way to ingest and prepare their corporate data for analysis and AI/machine learning. 

Goodbye, data management. Hello, data empowerment.  

TimeXtender is a data estate builder that empowers you to implement a modern data estate 10x faster with a simple, drag-and-drop user interface for ingesting and preparing data for analysis.  

TimeXtender seamlessly overlays your data infrastructure, connects to any data source, and provides all the powerful data preparation capabilities you need in a unified, secure, future-proof solution. 

We do this for one simple reason: because time matters.  

Data teams at top-performing organizations such as PandoraKomatsuColliers, the Puerto Rican Government, and the City of Lansing Michigan are already taking this new approach by using TimeXtender, the low-code data estate builder.  

How TimeXtender empowers everyone on your team:  

  • Business leaders can get fast access to reliable data, while reducing build costs by 70%, and maintenance costs by 80%.  
  • Data professionals can be free from tedious, repetitive tasks, and have time to focus on more fulfilling, high-impact analytics projects.  
  • Business users can start creating their own data products – no more bottlenecks.  

With this new approach, a better and stronger energy sector emerges. 

This is what winning looks like in the Machine Economy.  

Learn How to Become Data Empowered with TimeXtender  

Book a demo to learn how we can help you build a modern data estate 10x faster, become data empowered, and win in the Machine Economy. 

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