The new role of energy consultants among big data, AI, and Energy Management Systems

How is the work of energy consultants and Energy Service Companies (ESCOs) changing? What characteristics should an Energy Management System have to effectively support modern energy consulting? And what role will Energy Management Systems and Artificial Intelligence play in the coming years?

These questions are becoming increasingly important in a rapidly evolving sector. While just a few years ago an energy consultant's work was often tied to energy audits and one-off interventions, today companies require continuous support based on performance monitoring, verification of results, and the ability to turn data into operational decisions.

In this context, technology does not replace the professional's expertise; it expands their capabilities. The goal is not to automate consulting, but to provide tools that enable experts to analyze increasingly complex scenarios, monitor performance over time, and make faster, more informed decisions.

We discussed these questions with Stefano Gambarè, COO of Veil Energy, to explore how the needs of energy consultants are evolving and how new technologies can contribute to the future of energy consulting.

In recent years, you have collaborated with numerous Energy Management Experts and Energy Service Companies. What changes have you observed in their way of working and in the needs they bring to you today?

In recent years, their roles have changed profoundly. Where their involvement was once often tied to an audit or a specific project, companies today are asking for much more continuous support. They want to monitor energy performance over time, verify that interventions produce the expected results, and make data-driven decisions.

This means the professional is no longer called upon solely to identify inefficiencies, but also to ensure continuity, measurability, and strategic support. Consequently, there is a growing need for tools that make it easier to manage increasingly complex information without increasing the operational burden.

From your experience, what are the main operational bottlenecks that these professionals face in their daily management of clients today?

The challenge today is no longer collecting data, but making it truly usable. In most projects, the data already exists: it comes from monitoring systems, PLCs, BMS, SCADA, billing meters, or simply from files exported by clients. The problem is that it is scattered across different platforms, with varying levels of granularity, non-uniform naming conventions, and highly variable quality.

For energy consultants and energy service companies, this means dedicating a significant portion of their time to verifying data consistency, reconstructing historical series, normalizing information, and making it comparable—all before even starting any energy analysis.

There is another challenge as well: consulting does not end with the energy audit. More and more often, clients ask to verify over time that performance remains consistent with expectations, measure the actual impact of implemented improvement measures, and promptly identify any deviations.

Consequently, the professional's value is shifting from report generation to the ability to transform heterogeneous data into reliable information on which to base technical and economic decisions.

Many Energy Service Companies simultaneously manage dozens of plants and clients. Where do you see the greatest opportunities for efficiency gains through technology today?

I believe the primary margin for efficiency is the opportunity to make consulting scalable. Many consultants simultaneously oversee dozens of production sites, each with different processes, energy carriers, and monitoring systems. If every analysis has to be rebuilt manually, every report produced from scratch, and every KPI recalculated separately, growth inevitably becomes proportional to the number of available working hours.

Technology should instead enable the standardization of working methods, leaving more time for consulting where the professional's expertise can generate real added value. This means being able to define reusable analysis models, compare different sites using homogeneous indicators, automate recurring checks, and receive alerts only when a real anomaly or improvement opportunity emerges.

In this way, the professional no longer spends time producing information, but interpreting it. And that is precisely where they continue to generate the greatest value.

There is a lot of talk about artificial intelligence lately. From your perspective, which tasks can genuinely be automated and which will continue to require expert input?

There are high expectations around Artificial Intelligence today, but also a certain degree of uncertainty. In our sector, AI will not replace the consultant's technical expertise; rather, it will amplify their capabilities. Its true value lies in processing large volumes of heterogeneous data at scale, identifying patterns that are difficult to detect manually, and promptly flagging anomalies that require deep analysis. However, avoiding AI "hallucinations" requires well-trained models, well-structured data, appropriate data segmentation, and domain-specific tools. But even with the most advanced technologies, expert supervision remains the essential safeguard for interpreting and validating results.

Consider, for example, continuous energy performance monitoring. An algorithm can automatically compare thousands of measuring points against their baseline, highlight anomalous deviations, check the consistency of performance indicators, or spot progressive consumption drifts long before they become obvious. But understanding whether that deviation stems from a production process change, a shift in operating conditions, an equipment failure, or a deliberate business choice remains the professional's responsibility.

That is why we prefer to speak of Artificial Intelligence as an accelerator for consulting, not a replacement. The goal is not to automate decisions, but to enable consultants to make better decisions, faster, and on a much stronger information base.

When designing new features for E‑BOOST, how important is feedback from consultants and Energy Service Companies to product development?

It is an integral part of our development process. Most of E‑BOOST's features grew out of the daily experience of our own energy consultants, who for years faced the same operational challenges as the professionals we collaborate with today.

Several tools in E‑BOOST—such as PV sizing simulations, the CUSUM analysis tool, customizable EnPI creation, and automated report generation, to name a few—were originally developed as internal tools to speed up energy audits and simplify analysis. In other words, we built tools we wished we had available in our own daily work.

Since then, every evolution of the product has been guided by a co-creation process. On one hand, we continuously gather feedback from the field by working side by side with energy consultants, energy service companies, and industrial clients; on the other, we involve partners in User Acceptance Testing (UAT) phases to validate new features in real-world scenarios before release.

It is an ongoing collaboration between those who live the daily challenges of energy consulting and our software development team. We believe this dialogue makes all the difference: we don't develop features simply because they are technologically possible, but because they solve concrete operational needs.

What features do you consider essential in a modern Energy Management System designed to support Energy professionals?

In recent years, we have seen EMS platforms mature significantly. While in the past their primary task was collecting and visualizing data, today that is no longer sufficient.

A modern EMS should therefore start from a fundamental premise: energy data alone rarely tells the whole story. It must be contextualized using operational variables, operating conditions, energy costs, production data, and asset information. Only then is it possible to understand why consumption increases, whether a deviation is normal, or if it represents a genuine opportunity for improvement.

From a consultant’s perspective, a platform should also enable the construction of a replicable working methodology: defining consistent performance indicators, comparing different production sites, continuously tracking the impact of implemented actions, and documenting results over time.

How does E‑BOOST translate this vision into concrete tools for these professionals?

From the beginning, we designed E‑BOOST as a working tool for energy professionals, not merely as monitoring software.

The philosophy is to support the entire energy consulting lifecycle: from data acquisition and validation to its interpretation and transformation into concrete action. For this reason, we developed modules that address very different yet complementary needs—such as advanced energy performance and asset management, energy cost tracking, prosumer system optimization, and intelligent BESS (Battery Energy Storage System) management.

Rather than simply adding features, our goal is to provide tools that enable greater analytical depth and operational continuity. Consider, for instance, having a prioritized list of identified inefficiencies across the most energy-intensive assets, making it easier to focus on the highest-impact improvement actions; or the ability to monitor intervention effectiveness over time and compare energy performance across different sites; or correlating consumption with operational variables and evaluating increasingly dynamic energy management strategies.

Looking ahead over the next five years, how do you see the relationship between energy consulting and technology evolving?

I believe we will witness a shift far deeper than simple digitization. Energy consulting will become increasingly continuous rather than being based primarily on periodic analysis. Growing data availability, the spread of advanced monitoring systems, the increasing adoption of ISO 50001-compliant Energy Management Systems, and the rising complexity of industrial plants will make manual analysis and periodic audits increasingly unsustainable.

Professionals will be called upon to continuously monitor performance, verify that energy savings are sustained over time, support demand flexibility strategies, integrate renewable energy sources and storage systems, and navigate increasingly complex regulatory requirements. In this scenario, technology's role will be to manage complexity, not replace technical judgment.

Systems will become increasingly capable of identifying anomalies, simulating scenarios, proposing optimization strategies, and supporting operational decisions. But the responsibility of interpreting these results within a company's specific production context will remain with the energy experts.

The consultant's role will thus evolve further: from consumption analyst to strategic advisor. And this will require platforms that are increasingly intelligent, but above all, designed to empower human expertise, not replace it.