Government organizations are as eager as any business sector to harness the power of generative AI to transform their operations and improve service delivery. But as more and more of them initiate early exploration, experimentation, and eventual implementation, the unique challenges of successful adoption in governments are emerging. And—no surprise—it’s not just about the technology.
This is of particular interest to our Microsoft for Government team, where our mission is to help governments solve society’s biggest challenges. With the accelerated pace of innovation surrounding generative AI in the past 18 months, we’ve taken a special interest in understanding the full range of factors that either promote or hinder adoption in government organizations. One concern we invariably hear is about skilling—that is, how to provide the training and support required to help employees not just understand the technology but embrace it. Without this, even the best implementations are at risk of failure.
The growing interest in generative AI has already produced dramatic results in businesses globally, including many noteworthy impacts on governments. Gartner predicts that nearly 25% of governments plan to deploy generative AI solutions by March 2025, with an additional 25% projected the following year.1 While impressive, this is a bit less than projected global adoption, which is not surprising given that government organizations face an especially high bar in terms of trust, risk, and community expectations.
The promise of generative AI is prompting many governments to complete their cloud migrations and upgrade their data strategies, gradually retiring costly and increasingly inadequate legacy systems. These upgrades will deliver multiple benefits and are essential prerequisites to enabling generative AI innovation.
As it turns out, however, technology alone is not enough. According to a recent IDC study, the number one barrier to implementing and scaling AI is a lack of skilled workers. Nearly 52% of global business leaders named skilling as their top challenge—more than cost (28%), concerns about data or IP loss (28%), or concerns about governance and risk.2
To help fully understand the challenges of skilling that governments face, we commissioned our own research, Public Sector Insights on Skilling. We learned that the obstacles include limited training budgets and a lack of employee time and resources dedicated to learning.
Governments who want to be successful with AI should recognize that people are as important as technology in delivering a strong return on investment (ROI). That’s why upskilling is essential, both in terms of funding and employee time.
To help their workforce take advantage of major investments in digital transformation, the Bank of Canada developed an ongoing learning experience platform that provides targeted learning journeys and skills pathways for staff of many specializations. The goal is to free workers from many time-consuming administrative tasks and encourage them to focus on more meaningful work.
Effective practices can be integrated seamlessly into everyday activities, becoming an integral part of the government culture. To help ensure effective upskilling and successful AI adoption, we recommend three important strategies:
Embracing generative AI is often as much a cultural challenge as a technical one. It starts at the top. Committed, consistent leadership that aligns organizational goals with skilling, and demonstrates learning as a priority, are important factors in creating lasting change. Agencies and organizations need to allocate appropriate resources and understand the gaps in learning, with tactics to fill them. Build a learning culture by allocating time for employee training, identifying opportunities for applying new skills in problem-solving and innovation, and celebrating their success. A long-term mindset is key, as upskilling must be an ongoing employee priority, with opportunities for continuous learning.
An effective upskilling program is always specific to the government organization. Skilling programs should be developed in the context of their workforces, their local and national requirements, and the unique demands of their agencies and roles. But that doesn’t mean governments need to do it alone. To build a comprehensive approach to embracing AI, you can incorporate upskilling as part of the process from the start. Microsoft, our partners, and other technology providers can help develop skilling strategies. Microsoft offers effective training resources, such as our Public Sector Center for Digital Skills, which offers guidance and resources for public sector organizations in areas such as AI, cloud migration, and cybersecurity.
There’s an old Confucian adage that says, “I hear and I forget. I see and I remember. I do and I understand.” Wise words, which in the context of upskilling mean ensuring employees have adequate opportunity to hone their skills. It’s one thing to promise someone that generative AI will save them time. It’s profoundly more impactful when they click on Copilot and generate a document in a fraction of the time it previously required. Such experiences win people over, but they require time. The global head of an IT workplace, interviewed for a Forrester study, estimated that it took employees between four and eight hours of experimenting with Microsoft Copilot for Microsoft 365 before they could use it effectively in their work.3
We invite you to engage with Microsoft and your local technology partner to develop a skilling strategy as a key part of a holistic approach to AI adoption. For more resources and to learn more about skilling and other training opportunities, please visit:
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Source: Microsoft Industry Blog