Thanks to Openai’s Chatgpt, almost everyone knows Genai. It can satisfy people’s desire for knowledge through a simple hint. The use of this tool is really impressive. It gained 1 million users in just five days and attracted more than 100 million visitors in its first few months. Individuals and organizations incorporate it into their daily lives and activities.
However, despite Genai’s reputation worldwide, few people go far beyond experiments. Organizations are excited about their potential, but it is often difficult to eventually create a scale of measurable value to adopt it.
In my role, I’m lucky to witness how AI develops how an organization works and the value it can provide to customers. However, businesses need guidance to turn potential into performance. With these challenges in mind, my team conducted experiments with Microsoft’s 350 Copilot to develop valuable insights and practical strategies for companies aiming to achieve successful adoption and meaningful ROI.
Our road to Genei value
When we looked at adopting co-pilot, our approach helped us determine how its functionality could add value.
Our experience may be helpful for any organization that wishes to bring Genai into its workflow.
Here are some actions that helped us along the way:
- Start with a structured adoption framework. To introduce Genai capabilities, we first identify the people in the organization who may benefit, and then have specific and highly targeted use cases for the technology benefit. Finally, we have a personalized training program for each role or role to guide the user carefully so they know exactly how to make the most of their abilities.
- Using experimental verification techniques. For Copilot, we practiced with three groups of users. Group A does not have a Copilot license, and for Group B, we just give these users access to the tool without training or guidance: it is up to them to decide what to do. Group C obtained our complete adoption framework. result? Compared with Group B, we saw a 31% increase in adoption rate in Group C, with registration time of 2.5 hours per week and 1.8 hours per week for Group B. This exercise also provides our baseline data, for example, about how many specific tasks a team can save, such as creating a speech. This is another powerful example and argument that confirms that our adoption framework is working.
- Be closely involved in this process. Exercises like our Copilot experiment help ensure people are more likely to participate in new technologies. We have people closely involved in the use cases of co-pilot selection, which makes it more relevant, driving adoption and ultimately improving ROI. This process also creates missionaries. Since our group C cohort can clearly see the value of the technology to them, they advocate it throughout the company, especially in their team, thus encouraging further adoption.
- Develop a hyper-personalized and continuous training program. We work with project managers and process owners to ensure that Copilot use cases are relevant to their daily tasks, such as making presentations in a very short time. Through this understanding, we have created highly tailored training that demonstrates how technology can help them achieve their goals. Additionally, we found that ongoing training around creating tips is valuable in helping people get the best value from Genai. It’s also fun and helps keep the community united. For example, we created a group that shares useful tips and also had short sharing sessions regularly.
- Utilize partners. We help us by engaging in specific use cases and training offers that help build skills. In a domain as fast as Genai, partnerships and collaboration are essential to achieving good results.
- Actively communicate about the concerns of employees. Questions about ethical AI and whether it will steal people’s work are common. Therefore, it is important to ensure that the adoption framework clearly defines the ethical use of ethical AI and AI. To ensure responsible and secure use of AI, we leverage a responsible AI framework. This framework provides clear guidelines for our employees, aligning with our company’s values and helping them use AI responsibly. To alleviate concerns about Genai’s impact on work, we focus on it taking over unwelcome mundane and time-consuming tasks such as timing, drafting communications, or sifting crowded email inboxes. As their proficiency increases, we introduce more sophisticated techniques, including enhancing their ability to create advanced tips, resulting in more precise and tailored output.
Time, innovation and training
Our experience with Copilot and other Genai projects is that the structured pilot phase is key and people need time to learn innovative technologies. There must also be a framework for AI adoption and change management tailored to the specific needs of your team. Coupled with user training and active participation, this will inspire and clear up concerns about Genai.
Once the technology is embedded in the organization and spreads, it becomes part of the culture and accelerates your path to real value from Genai.
