Managing Director & Partner
How best to start a generative AI transformation when the future is simultaneously so promising, unknown, and potentially risky? Schneider Electric and BCG partnered to make the most of this exciting opportunity.
While many organizations see generative AI mainly as a technical and data challenge, Schneider Electric’s leadership recognized that the technology requires transformation of business processes and people development along with enhanced risk management. And that is how Schneider Electric is treating this moment as it decides which generative AI opportunities to pursue.
Founded in 1836 as a steel and heavy equipment manufacturer, Schneider Electric has a history of keeping up with the times. The €34 billion company is now a global leader in the digital transformation of energy management and industrial automation. Back in 2009, before the Internet of Things was a household phrase, Schneider Electric launched EcoStruxure, an open, interoperable platform that delivers digital solutions in energy management, building automation, and data centers. In November 2021, the company created a global AI organization staffed with 300 professionals to pursue high-value use cases alongside internal functions and business units. It also named a chief AI officer.
The recently completed review of the value chain to identify promising uses of GenAI is the most recent chapter in Schneider Electric’s rich history of reinvention. In line with earlier AI efforts, the review examined potential productivity gains, revenue opportunities, talent upskilling, and people development.
This effort has yielded some early lessons.
Generative AI will likely enhance how work gets done, create demand for new skills, and eliminate the need for other skills. It will accelerate the clock speed of organizations, creating the need for agile leadership, diverse perspectives, and better soft skills in addition to ongoing change management capabilities. And it will likely change how organizations are configured. Many routine tasks performed by humans will be executed by AI, and creative and experience-based skills will take on greater value.
In recognition of the human-centric nature of a GenAI transformation, Schneider Electric decided to involve stakeholders from across the company from the start. The company held 56 workshops attended by more than 200 internal stakeholders from 15 functions over four weeks. The workshops brought AI and technology experts together with business executives to build awareness of generative AI capabilities, co-create high-value opportunities, and identify ways to excite employees.
这个前期包容和动员的人signaled to the organization that leaders view the adoption of generative AI as a company-wide effort rather than a top-down or bottom-up initiative. In the workshops, employees were encouraged to flag potential barriers to various approaches and recommend ways to overcome implementation challenges.
The workshops also identified training as a critical success factor, an area that emerged in a recent BCG survey of 13,000 employees, in which86%的人说他们觉得upskilling的必要性to stay relevant in an AI world.
In a traditional AI implementation, BCG follows a 10-20-70 rule. Organizations should devote 10% of their effort to algorithms, 20% to data and the technological backbone, and 70% to business and people transformation. Since many generative AI solutions are off the shelf, the technology effort will likely be less than 20%. But the effort devoted to business and people transformation—especially business process redesign, change management, upskilling, and leadership development—will likely be greater. To this end, Schneider Electric has recruited its digital talent steering committee, comprising its top HR and talent leaders, to help facilitate a systematic rollout.
The pre-work that Schneider Electric has put into its generative AI journey has paid off in thoughtful decisions about which use cases to pursue. There are opportunities for quick productivity gains with off-the-shelf generative AI solutions. Those gains can help fund more ambitious initiatives, but eventually they will be duplicated by competitors and provide only a temporary advantage.
The bigger bets, such as developing specific GenAI use cases integral to Schneider Electric’s business, will initially be more exploratory and uncertain, but the potential payoff is greater gains and a competitive edge. Leaders understand the business transformation challenges these bets will require. It will be critical to find a balance between high-ROI, short-term wins and medium-term, higher-stake bets.
Equipped with the insights generated through the workshops and employee engagement, Schneider Electric now has a stronger sense of the actual cost and degree of difficulty in pursuing generative AI use cases. It is able to budget more accurately how productivity gains from early projects can fund more ambitious, longer-term projects.
Generative AI is here to stay. Just like AI, it comes with risks.
Schneider Electric has long been managing these risks. During the review, executives saw the need to increase the focus on critical capabilities such as responsible AI, cybersecurity, legal and compliance, and data risk management. Schneider Electric views these investments as enabling capabilities that will pay dividends in a world in whichtrust, integrity, and transparencyare likely to play larger roles.
The opportunity cost of not moving fast in a generative AI world is high. Time to deployment and especially time to value are critical. So is responsibility. Schneider Electric’s developing roadmap puts the company on the fast path to profitability in sync with responsibility.
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