The Agentic Workforce: How embedded AI is transforming utility operations
maart 23, 2026
Events
During the recent IDC event, our Product Manager Mar Jorba got the honor of hosting a roundtable discussion bringing together industry leaders to explore how AI is reshaping utility operations. The conversation surfaced valuable perspectives on the rise of agentic AI, the challenges utilities face in operationalizing it, and the opportunities ahead.
In this blog post, we take a closer look at the key insights shared during the discussion and what they mean for utilities navigating the next phase of AI adoption.
Over the past two years, most organizations have experimented with generative AI: piloting copilots, deploying chatbots, and exploring productivity tools. Yet a more consequential shift is now underway. AI is moving beyond assisting humans to executing work.
This evolution is giving rise to what many are beginning to call the agentic workforce: intelligent AI agents embedded directly into operational systems, capable of reasoning, planning actions, and orchestrating workflows alongside human teams.
For the utility industry, this shift may prove particularly significant.
Utilities operate in one of the most complex operational environments of any sector, balancing infrastructure reliability, regulatory scrutiny, customer expectations, and the accelerating energy transition. As workforce pressures and operational complexity continue to increase, the ability to embed intelligence directly into operational processes could become a defining competitive capability.
According to IDC’s 2025 global research, artificial intelligence is projected to contribute $22.3 trillion to the global economy by 2030.
Adoption is accelerating rapidly: 68% of organizations are already using generative AI, while 37% are deploying agentic AI solutions, with another 25% actively experimenting.
The return on investment is equally notable. Organizations report an average 2.8× ROI from generative AI initiatives and 2.3× ROI from agentic AI, with most seeing measurable value within 13 to 15 months.
Source: What every company can learn from Frontier firms leading the AI revolution.pdf
Yet averages obscure an increasingly important divide. IDC identifies a group of organizations it calls “Frontier Firms.” These organizations have moved beyond experimentation to operationalization. They deploy AI across multiple functions, monetize its value, and build governance structures that allow them to scale AI responsibly.
The results are striking. Frontier firms achieve an average 2.84× return on AI investments, while organizations still in early experimentation see less than 1× return. Despite the momentum around AI, only 22% of organizations globally currently qualify as Frontier Firms.
In other words, an AI capability gap is emerging, one that may reshape competitive dynamics across industries.
“At Ferranti, we also observe varying speeds across our customers. While demand for AI adoption to drive operational efficiency has clearly accelerated in recent months, not all organizations are equally prepared, nor are they committing the resources and leadership required to become true frontier firms.” said Mar Jorba, MECOMS Product Manager and driver of the AI innovation team
Few industries face the same combination of structural pressures as utilities. Leaders must simultaneously navigate:
In this environment, productivity tools alone are unlikely to deliver the operational transformation utilities require. AI must operate within the core systems that run the business,
However, the next phase is emerging quickly: industry-specific AI embedded directly into operational workflows.
Today only 25% of organizations deploy AI for industry-specific use cases. Within the next 24 months, that figure is expected to reach 57%.*
For utilities, this distinction is crucial. Competitive advantage in the utility sector has never been about generic productivity improvements. It has always been about operational orchestration, regulatory precision, and system reliability.
AI that simply assists individuals will deliver incremental gains. AI embedded into operational processes has the potential to reshape how utilities function.
Source: What every company can learn from Frontier firms leading the AI revolution.pdf
Understanding this transformation requires distinguishing between two fundamentally different categories of artificial intelligence.
It produces text, insights, and recommendations, augmenting human decision-making and accelerating information work.
Agentic systems can reason about complex tasks, plan sequences of actions, trigger system operations, and execute workflows autonomously while collaborating with human teams.
In effect, the role of AI shifts from a productivity tool to a digital operational participant.
IDC’s research suggests organizations increasingly recognize this potential. Nearly 60% of organizations plan to deploy agentic AI for productivity use cases that directly generate revenue, while 61% expect agentic systems to contribute significantly to cost reduction initiatives.
At the same time, organizations recognize that scaling operational AI requires strong foundations. Security, governance, legacy system integration, and talent capabilities remain among the most frequently cited barriers to adoption. These challenges are particularly relevant in the utility sector, where operational reliability and regulatory accountability are paramount.
What does an agentic workforce look like in practice? Rather than introducing isolated AI tools, organizations embed intelligent agents into operational workflows where they can manage specific tasks and coordinate activities across systems.
In this model, AI does not replace utility professionals. Instead, it augments their capabilities, enabling teams to focus on higher-value problem solving and strategic decision-making.
Here, we are also seeing a shift in Ferranti’s customer conversations from a purely cost-reduction focus toward enhancing the employee experience and prioritizing employee satisfaction, making the work of internal teams more meaningful, hand in hand with AI.
Utilities may be better positioned for operational AI than many other industries. Unlike sectors where processes remain fragmented or loosely structured, utilities typically operate within highly standardized workflows supported by large volumes of operational data and well-established compliance frameworks.
Most utilities also rely on enterprise platforms, including ERP systems, billing platforms, and Microsoft-based ecosystems, that provide a foundation for embedding AI capabilities directly within existing operations.
The strategic opportunity, therefore, is not to build entirely new AI infrastructures. It is to embed intelligence into the systems that already run the business.
When AI remains disconnected from operational platforms, organizations produce experiments. When AI becomes embedded within enterprise workflows, organizations unlock transformation. That distinction may ultimately define which utilities emerge as AI leaders in the coming decade.
This is where Ferranti’s MECOMS 365 stands apart: embedding Microsoft Copilot and agentic AI natively into operational platforms, so AI moves beyond experimentation and becomes a driver of real, enterprise-wide transformation.
As utilities explore the next phase of AI adoption, several questions increasingly dominate executive discussions.
Organizations must determine whether they are still experimenting with AI or beginning to operationalize it across core processes. They must identify which workflows offer the greatest opportunity for automation and augmentation. They must establish governance frameworks that enable innovation without compromising trust or accountability.
Yet, around the IDC table, a recurring tension emerged: when does experimentation end and real operationalization begin? Many participants questioned how to move beyond pilots without losing momentum. At the same time, CFOs are increasingly demanding clear business cases and short-term returns, pressure that, while necessary, can prematurely shut down experimentation before its full value is understood.
Perhaps most importantly, leaders must consider the human dimension of AI transformation. AI will inevitably reshape roles across the utility workforce. The challenge is not simply technological implementation but ensuring that employees are equipped with the skills, trust, and confidence to work alongside intelligent systems.
As several energy leaders shared during the IDC roundtable, the technology is already here, the real question is whether people can keep up. Many teams are still catching up with the previous wave of IT-driven digitalization, let alone preparing for the next wave of AI, with all the ethical and moral challenges it still entails.
Artificial intelligence is no longer an emerging technology. It is becoming an operational capability. The next phase of AI adoption will not be defined by standalone tools or isolated pilots. It will be defined by how deeply AI becomes embedded within the systems, workflows, and decision processes that power organizations.
For utilities navigating unprecedented operational complexity, the emergence of the agentic workforce may represent one of the most consequential shifts in decades. The organizations that move beyond experimentation and begin embedding AI into the fabric of their operations will not simply automate tasks.
They will redefine how work gets done.
At Ferranti, we are already enabling this next phase, helping utilities embed AI into the core of their operations and turn the promise of an agentic workforce into a practical reality.
Mar Jorba
Talk the talk
Stay informed about current events and stay on top of the latest trends for energy suppliers, grid operators, heat-and-water providers.
