The AI Briefings

How LinkedIn is doing it:
We’re at the forefront of providing innovative AI products and features to our customers, and we’re taking the same care in how we bring AI to our employees. Instead of driving towards launch and then transitioning to business-as-usual, we’re taking a scaled approach to help employees understand how AI impacts their day-to-day work. That means enabling learning, application, and adaptability from the start so employees can evolve their understanding of AI on an ongoing basis.

Example:
We designed our GenAI Upskilling program to give employees a foundational understanding of GenAI tools – and keep us innovative and future-ready as an organization. Since AI is constantly evolving, we realized that the program would need to do the same. By grounding ourselves in a clear goal, we were able to divide our work into phases. We started with a small group of new users, which helped us identify ways to boost the use of GenAI at scale. Most importantly, it uncovered the need for personalized change efforts down the road, unlocking longer-term planning for a sustainment team with AI champions. Today, our champions stay on top of new AI developments and apply learnings to their teams and functions, with a centralized body to maintain a consistent experience across our organization.

How LinkedIn is doing it:
At LinkedIn, a clear change narrative is integral to the way we introduce GenAI tools. By framing our ‘why’ in a human way, we help employees understand how AI can enhance their capabilities and help them use their skills for higher-level problem solving, creativity, and innovation.

Example:
We launched our Coaching for All program to provide one-on-one coaching to employees. Typically, our narrative would have focused on the benefits of the program, like meeting with a certified coach to discuss personalized goals. But this program was designed to empower employees in the age of AI, so we needed to shift our approach. By focusing on the larger why, we connected the program to our long-term vision and built buy-in from the start. Our final why statement: ‘With new tools, technology and ways of working emerging every day (hello, AI), it’s critical for everyone to continuously upskill. And for our company to stay ahead, we need to ensure that all of us have the best training and coaching.’ 

How LinkedIn is doing it:
When it comes to AI, we continue see the value of ongoing learning. Our traditional change management process follows a steady learning curve with a clear definition of success, but AI-driven change is a moving target that requires our employees to learn, apply, and adapt through short but intentional bursts. 

Example:
We created our GenAI Upskilling program to help employees build a foundational understanding of GenAI. Our goal? To give them the skills to innovate with AI in hand and keep our organization ahead of the curve. We quickly realized that the program needed to evolve in line with AI, so we decided to take a phased approach. Our team started with basic training to get employees comfortable with GenAI, using examples of how different tools improve their day-to-day workflows. From there, we identified the need for persona-based, hands-on workshops to familiarize employees with prompt building, bots, apps, and agents, along with experienced SMEs to live-demo their insights. This drove curiosity and engagement along the way, and we continue to see the results through the sustained usage of AI tools.

How LinkedIn is doing it:
At LinkedIn, we’re seeing AI create room for more strategic and meaningful work. Our employees are less siloed and more open for human collaboration. AI-driven change is moving beyond individual teams and tasks with implications on global systems, workflows, and processes. Our change management approach isn’t just based on the immediate impact of AI, but on the broader consequences of an interconnected system. In line with that, our change impact assessment – designed to measure the potential impact of change on key stakeholder groups – has evolved to capture global shifts in workflows, dependencies, and processes.

Example:
We experienced this shift in real time when we redesigned our new-hire onboarding process. Onboarding typically includes a set of local processes, like training on specific tools and access to internal systems. With AI, we knew we had to consider a broader set of variables that come with being a global and interconnected organization. A thorough impact assessment helped us anticipate and accommodate global needs, like ensuring access to systems across multiple time zones, managing security protocols for remote employees, and tailoring our chat bot and training materials to different cultures and legal requirements.