The fast-moving target of artificial intelligence literacy is rapidly cementing itself as a top priority for chief information officers worldwide. As the sheer availability of advanced tools outpaces the everyday workforce’s capability to use them effectively, organizations are facing a critical bottleneck.
Across industries, an enterprise skills gap is actively derailing artificial intelligence ambitions, bringing promising projects to a halt long before they ever reach the adoption stage. This widespread deficiency is forcing enterprises to look outward for desperate rescue, racking up substantial bills in external consultants to complete stalled projects, and frequently adding unnecessary ongoing costs for unused or underutilized services. Furthermore, internal training initiatives designed to teach employees how to leverage these brand-new tools are lagging far behind the technological rollout, leaving workers feeling unequipped and overwhelmed, according to recent workforce feedback.
Part of the underlying issue is that artificial intelligence remains a relatively immature enterprise technology, according to Philippe Rambach, senior vice president and chief artificial intelligence officer at Schneider Electric, a major energy technology company headquartered in France.
"It was never easy to deploy any new technology," said Rambach, who first joined the company in 2010, drawing on over a decade of enterprise transformation experience. "When I look at the time it took for companies to successfully deploy things which are relatively simple, like a CRM, it often took years."
Even after an organization successfully navigates the complex deployment phase, companies still face an uphill battle when trying to drive genuine employee adoption across diverse departments. When it comes to artificial intelligence, enterprises simply cannot afford to take a one-size-fits-all approach to training and education, Rambach noted. Recognizing this hurdle early on, Schneider Electric collaborated with prominent online learning platform Coursera to create a specialized, four-tiered curriculum carefully designed to match the unique roles, responsibilities, and functions of specific employees throughout the global organization.
The first tier of this comprehensive initiative consists of fundamental artificial intelligence training, which became a mandatory program rolled out to all of Schneider’s 160,000 employees globally. Beyond basic literacy, an additional specialized training program targeted directly at the senior management team focuses heavily on the intricate art of blending artificial intelligence capabilities with high-level corporate strategy.
"They need to lead by example, so these teams need special attention with specific trainings that have been deployed to them," Rambach explained, emphasizing the critical role that executive leadership plays in setting the cultural and operational tone for technology adoption.
The third group within the educational framework is made up of technical experts actively involved in writing artificial intelligence software, Rambach said, pointing out that this specialized team reports directly to him to ensure alignment with corporate goals. Finally, a fourth distinct group—those individuals in charge of broad organizational transformation—also receives access to highly tailored training modules.
"Those groups who are either in charge of building the customer roadmap or driving the internal transformation need a special focus," Rambach said, highlighting why generic educational programs fail to move the needle in complex corporate environments.
Scaling Knowledge Through Cross-Functional Collaboration
Running corporate training programs in an isolated vacuum is unlikely to yield meaningful results, as modern workers need to be able to draw a clear, undeniable line between the abstract information they gain in courses and how it can tangibly affect the day-to-day work they do.
To bridge this gap, Schneider Electric relies heavily on cross-functional teams for both the deployment and development of artificial intelligence use cases. These collaborative units operate not just internally across departmental silos, but also externally for its customers, effectively banding together business acumen, IT infrastructure knowledge, and deep artificial intelligence expertise to thread the needle on complex projects.
"Never underestimate the importance of these multidisciplinary teams," Rambach said. "They learn by doing the project, they learn by working together."
Schneider, a company that manufactures critical electric equipment for data centers, has naturally leaned into the explosive, rapid buildout of global infrastructure capacity and the ensuing, unprecedented demand for power. Capitalizing on these macro trends, the company partnered with Nvidia earlier this year to develop validated blueprints and deploy advanced testing and simulation capabilities specifically designed to help design, simulate, build, operate, and maintain gigawatt-scale artificial intelligence factories.
The strategic focus is paying off financially. The company posted record revenues of 21.2 billion euro, which translates to around $23.7 billion, for the first half of 2026. This figure represents a robust 14% increase in organic growth year over year, with its booming data center segment serving as a primary, lead driver of overall corporate growth.
"Data centers need energy, energy needs data centers," said CEO Olivier Blum during a May earnings call discussing the company’s financial trajectory. "What’s important is that we are present in both sides of the equation. We provide the infrastructure, but we can also leverage AI to make our solutions smarter for our customers, both in the world of energy and in the industrial process."
With the invaluable help of cross-functional teams, the company is actively using artificial intelligence to help address pressing operational challenges across the business, Rambach said. Notable real-world use cases include the deployment of an advanced artificial intelligence-based tool designed to dispatch field technicians much more effectively, a customer-focused service aimed at helping industrial clients significantly reduce their energy consumption, and an internal tool built to rapidly tailor sales pitches for incoming clients.
Reflecting on these initiatives, Rambach strongly recommended that corporate executives continue to iterate on their artificial intelligence playbooks, making the absolute most of the positive friction that naturally occurs when domain experts are brought closer together to solve hard problems.
"There is no easy and 100% path," Rambach concluded. "We are all learning."
