Why buying an AI solution is the smart choice for utilities

With rising demand for reliability, efficiency, and cleaner energy, Artificial Intelligence (AI) is a powerful tool in meeting these challenges. AI can optimize grid management, predict equipment failures, and support customer engagement. It does come with its own set of challenges in terms of development, deployment, and maintenance. For many utilities, the choice comes down to whether to build AI solutions in-house or buy an external AI system. Here's why purchasing an AI solution is often the right choice for utilities.

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Reduce time to value with ready-made software

Building an AI system from the ground up requires a significant investment in time, human resources, and capital resources. Utilities that choose to build in-house need to source or train specialized AI talent, design custom algorithms, and refine them through extensive testing and deployment phases. With an external partner, however, utilities can take advantage of pre-built solutions that are tested and ready to implement. This shortens the timeline from years to just weeks, allowing utilities to see benefits quickly.

Access AI systems at a fraction of the cost

Keeping pace with the rapid advancements in AI requires significant R&D investments, making it challenging for utilities to stay competitive with an in-house approach. Buying an AI solution from a vendor allows utilities to leverage cutting-edge capabilities without incurring the full costs of innovation. Vendors typically maintain large teams of data scientists, engineers, and researchers, meaning utilities can benefit from advanced solutions, such as predictive analytics, natural language processing, or computer vision, without having to make these investments themselves.

Benefit from industry-specific expertise

Many AI solution providers focus on the utility sector, giving them deep insights into the specific challenges that utilities face. These companies often bring a wealth of experience with utility-specific use cases along with AI-specific engineering teams. By partnering with an industry-experienced vendor, utilities have access to solutions tailored to their needs rather than generic AI tools. This results in solutions that deliver more relevant insights and improvements, increasing the overall effectiveness of the AI initiatives.

Improve scalability and flexibility

Utility needs are constantly evolving. As more renewable energy sources come online, grid management demands may increase, requiring more sophisticated analytics and optimization. Building an in-house AI solution often leads to rigid, single-purpose applications, making it challenging to scale or adapt to new requirements. Partnering with a vendor typically allows utilities to select from a suite of solutions or scale up as their needs grow, providing flexibility that a single in-house project may not offer. Vendors often offer modular, cloud-based solutions, which allow for easy scaling and upgrading as business needs shift.

Reduce risk with proven security measures

Data security and regulatory compliance are critical across all sectors, particularly in utilities. Customer data and grid stability are highly sensitive. Building an AI solution internally will require custom security protocols and compliance measures, which can be both costly and challenging to execute effectively. AI vendors have proven security protocols in place that reduce the risk of data breaches and ensure regulatory standards are met. This reduces both operational risk and the potential for costly compliance violations.

Choosing the right AI partner

When selecting an AI partner, utilities should consider the provider's experience with the energy sector, scalability options, security protocols, and level of customer support. A strong partnership is built on alignment with the utility's goals and a shared vision of the AI's potential impact.

‍Partnering is key for a future with AI

AI solutions are unlocking infinite use cases at utilities. The choice to build or buy is critical in unlocking these use cases. While building internally offers control, partnering with an AI vendor delivers faster, more cost-effective, and higher-quality results. Partnering can also enable advanced AI capabilities without taking on the full burden of development, focusing instead on delivering reliable, sustainable, and efficient services to their customers.

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