How Energy and Utilities Companies Can Get AI Ready

For years, experts have discussed the advancement of artificial intelligence (AI), including its significant role in utilities and the development of utility-based agents. Once emerging technologies, machine learning and automation have reached a pivotal moment, they have become mainstream and are being widely implemented in businesses, particularly in the utility sector. Integrating AI in utilities and deploying utility-based agents marks a transformative phase in how businesses leverage technology for operational efficiency and customer service.

The turning point for the industry was the release of tools like ChatGPT that put AI in the hands of almost anyone. Companies like OpenAI, thanks to the use of ChatGPT, are gaining access to a proliferation of training data. AI is getting smarter and faster simply because more people are training it. That’s why you’re hearing about AI so much in the news.

For energy and utility companies in particular, AI has the potential to help businesses run better.

“AI has the potential to cut energy waste, lower energy costs, and facilitate and accelerate the use of clean renewable energy sources in power grids worldwide,” explains a report from Deloitte. “It can also improve the planning, operation, and control of power systems and can be used to improve interactions with customers and field workers.”

To reach its potential, the humans behind AI implementation in an energy company need to be smart about executing. This process begins with an organization’s digital transformation strategy, which should specifically enable utilities to adapt to new technologies efficiently.

Why digital transformation is a necessity

“By 2025, 40% of energy and utilities companies will face a 50% increase in capital demands triggered by resource scarcity and soaring demands,” explains a Gartner article.

Meanwhile, the energy and utilities sector is experiencing the combination of heightened customer demands in addition to talent turnover. Gartner analyst Rich McAvey elaborates:

“Energy companies are expanding the scale and scope of digital innovations to drive efficiency, transform operations, and diversify revenue. CIOs and digital leaders need to understand how to align technology investments with strategic business goals.

Informed and intelligent decisions, particularly in the energy sector, are critical for every step in the digital transformation journey. In today’s resource-constrained economy, with the utility of AI becoming increasingly evident, there’s simply no wiggle room for error.

Every organization will need its unique strategy for digital transformation and getting AI ready. Consider AI in the utility industry as an example.

Importance of Digital Transformation

Digital transformation is crucial for energy and utility companies, enabling them to become more competitive and autonomous in a constantly evolving market. To meet the growing demand for clean energy and greater efficiency, digital tools can facilitate this transition in the following ways:

Operational Efficiency

Technology and automation tools allow companies to streamline their operations, reduce service costs, and enhance performance. Advanced analytics and Internet of Things (IoT) devices enable real-time monitoring of utility usage and status, predictive maintenance, and asset longevity.

Customer Experience

Modern energy and utility companies leverage advanced digital interfaces and intelligent tools to improve customer experience and satisfaction. AI is instrumental in delivering accurate billing, resolving issues more swiftly, and providing continuous status updates. Additionally, AI facilitates more cohesive and tailored communication for electronic device users.

Data-Driven Decision Making

Energy and utility companies generate vast amounts of data that can be used for optimizing resource allocation. Sophisticated analysis tools enhance the ability to forecast future market conditions, aiding strategic planning and execution.

Sustainability

Digital tools are essential for harnessing renewable energy sources and developing intelligent, efficient smart grids. This not only mitigates environmental impact but also aligns with increasingly stringent regulations and environmentally conscious consumers. AI advancements, particularly in solar energy, drive significant progress in this area.

Challenges of Digital Transformation

Despite the numerous advantages, digital transformation in the energy and utilities sector faces several challenges:

Legacy Systems Integration

Many utilities rely on outdated infrastructure and legacy systems that struggle to connect with modern digital solutions. Integrating these systems requires substantial investment and technological expertise to ensure functionality and data flow.

Cybersecurity Risks

Increased connectivity and data exchange heighten the risk of cybersecurity threats. AI in utilities must prioritize developing robust cybersecurity policies to protect sensitive data and critical infrastructure.

Cultural Resistance

Change management poses a significant challenge, as employees often resist new methods. Effective training and ongoing communication about the benefits of digital transformation are crucial for overcoming this resistance.

Cost and ROI

The initial investment in digital transformation is substantial and must be evaluated in terms of return on investment. Ensuring that short-term costs are manageable to reap long-term benefits is essential for successful implementation.

Data Management

Managing large volumes of data from various sources requires advanced data management strategies. Ensuring data quality, accuracy, and accessibility is vital for leveraging data-driven insights.

Regulatory and Compliance Issues

Navigating regulatory complexities is crucial, as companies must stay informed of changes and ensure that digitalization efforts comply with industry standards and regulations.

Skill Gaps

Successful digital transformation depends on having a qualified team. As AI in utilities is a relatively new field, it requires specific skills and qualifications that may not be readily available, necessitating targeted training and development programs.

Practical tips for getting AI ready in the energy and utilities sector

1. Ensure that your customers are the focal point of your strategy 

With customers at the core of your strategy, integrating AI for utilities positions you well for business growth. Optimizing energy management through AI helps in gaining a deeper understanding of your customers’ needs and behaviors. This customer-centric approach, enhanced by AI, enables you to identify pain points, discover patterns in energy usage, respond effectively during emergencies, and recognize problems in energy distribution that require immediate attention.

Your software can help with ensuring that your field service organization is taking a customer centric approach. Consider the case of CHEMET GLI, a European company that specializes in installing, removing, and exchanging liquefied petroleum gas (LPG) tanks, in addition to providing emergency services.

“There came a point where we needed to improve our operations,” explains Adrien Wicker from the IT services team at CHEMET GLI. “We decided to look for a field service management software that would allow us to optimize our technicians’ routes and track our customer contacts, including work order history and comments.”

“Our previous process was way too cumbersome and hindered our ability to develop our business and grow. We had little to no visibility into our short and long term operations. The catalyst came when 2 large customers of ours wanted us to interface with their data exchange system.”

Before choosing software to begin automating your own operations, it may be helpful to research your customers’ roadmap for data infrastructure.

2. Know exactly how and where it makes sense to implement AI

Leading field service companies turn to AI because they understand that it’s the only way to efficiently utilize the data being collected by their customers’ equipment, and to optimize their technicians’ travel schedules. Incorporating a utility-based agent in AI enhances this process by evaluating and acting upon data in a way that maximizes utility or performance. This data is only as valuable to the extent to which it gets put to work. In the realm of asset management, the effective use of AI-driven insights is crucial for managing assets more efficiently, predicting maintenance needs, and optimizing resource allocation.

When leveraging data, it’s important to focus on precise use cases. As an example, you can use artificial intelligence to optimize your field service management practices in real time. AI makes it possible to consider a range of parameters when planning service calls, including the type of service needed, predictive maintenance, and technician locations/skills.

With artificial intelligence in utilities industry, you have the information needed to get the right technician to the right location at the right time to maximize the chances of resolving the customer issue on the first visit. The software itself uses machine learning to adapt based on work order histories, previous technician scheduling strategies, and information that systems continue to harness.

3. Be prepared to leverage 5G

In the energy and utility space, real-time communication networks are crucial. Especially in the event of an outage, natural disaster, or stressful situation, instantaneous communication is what helps projects go smoother.

With faster mobile internet speeds, field service providers can deliver more real-time services and improve communications as a result. With this foundational infrastructure, a utility based agent in AI will be especially useful for developing models, accessing data, and supporting human decision making.

Across the United States, funding is becoming increasingly available to support the energy industry, including initiatives for energy efficiency and renewable energy. As energy and utilities companies embrace AI, understanding the utility function in AI example becomes crucial, particularly in the context of 5G rollout plans in your service area. This advancement means potentially partnering with telecommunications companies, enhancing the value and importance of energy and utilities companies in an evolving technological landscape.

5G will be crucial for the future of AI and for energy and utility companies to meet the rising demands of energy consumption.

Training and Skill Development

With the increased integration of artificial intelligence in energy and utilities, the importance of a skilled workforce becomes even more critical. Therefore, ongoing training and skill development are essential for effectively using AI applications in the energy sector and empowering employees to contribute meaningfully to the company’s digital transformation.

Without proper training, employees’ skills and knowledge can go to waste. In contrast, well-designed training programs ensure that staff can fully leverage AI tools, maximizing return on investment. Skilled employees can use AI utilities to automate repetitive tasks, enhancing productivity and efficiency. Moreover, staff training contributes to informed decision-making, leading to overall improvements in operational performance.

Advanced training does more than just equip your team with new skills; it fosters a culture of continuous learning. This culture serves as the foundation for innovation, enabling your company to adapt and thrive amidst evolving technologies.

Furthermore, staff training is not only about skill enhancement; it also plays a crucial role in improving security. Well-trained employees are more likely to recognize privacy and security threats, providing a strong defense against one of the most significant risk factors.

The Future of AI in the Energy Sector

The future of AI in the energy sector is not just promising—it is transformative. AI will revolutionize how energy is generated, maintained, and consumed. These technologies will enable smarter grid management, improve supply-demand balancing, and facilitate more efficient integration of renewable energy sources.

AI-based tools will also enhance predictive maintenance, leading to fewer downtimes and reduced operational costs. The adoption of artificial intelligence techniques in solar energy applications will significantly boost the efficiency of solar power generation.

In addition, AI in the energy sector will drive advancements in energy storage, ensuring a more reliable and stable power supply. Ultimately, AI will become an invaluable asset for creating more sustainable and disaster-resilient energy infrastructures. The potential of AI in the energy industry is virtually limitless, paving the way for cleaner, more efficient, and economically viable energy solutions.

Final thoughts

The best implementations of AI technologies and goal based agents will focus on helping empower people rather than replacing jobs. Automation is valuable for systematizing difficult tasks so that human minds can work more efficiently. The key is to focus on relieving business bottlenecks and to help people work smarter rather than harder throughout the organization. As jobs get harder and more complex, AI can take on more of the lift.

To learn more, download our latest whitepaper “Digital transformation blueprint for Energy & Utilities companies: Bringing operational efficiency to work orders and maintenance”

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