Your colleague is intimidated by your AI upskilling. How can you navigate this situation effectively?

So I scanned this with GPT-Zero (the AI detector) and it classifies the whole article as AI with a probability of 100%. Nothing particularly wrong with that, but it kinda feels a little off. Still, let me take this seriously not because intimidation is real but negligence is. I believe every human who consumes information should be regularly updated with the capabilities of narrow-AI tools. Computer systems are hacked with codes, but humans are hacked with emotions. And for the first time, machines have the capability to do so.

If a colleague feels intimidated by your AI upskilling, it’s often rooted in fear of the unknown or being left behind. Address this by showing empathy and initiating an open conversation. Share your learning journey, and highlight how your new skills can benefit the team as a whole. By fostering a supportive environment, you can turn fear into an opportunity for collective growth.

This is a very strange question (generated by AI! 😄). Learning AI skills is much like learning to drive or using the internet when it was first invented. Not everyone needs to become an AI scientist, but learning AI-related skills can benefit anyone in their respective fields.

• Empathize: Try to understand your colleague's perspective. They may feel threatened or insecure about their job security or skills becoming outdated. • Share knowledge: Offer to help your colleague learn about AI and its applications in your field. This can help demystify the technology and reduce their anxiety. • Focus on benefits: Explain how AI upskilling can benefit the team and organization as a whole, potentially leading to new opportunities for everyone. • Advocate for training: Suggest company-wide AI training programs to ensure everyone has equal opportunities to learn and adapt. • Be patient: Understand that adapting to new technologies takes time, and everyone progresses at their own rate.

AI is reality of business today. There will always be people who will feel intimidated, and there would be people who will get inspired. As a colleague, it would be important to take a repetitive task that your friend is doing, and demonstrate the power of AI. This will open him/her to the art of possibilities and hopefully inspire them to the learning journey.

Using AI to upskill is about leveraging available tools to enhance our capabilities, not replacing or undermining anyone’s abilities. Think of it as having an extra set of hands or a team member that helps process information faster and more efficiently. It’s not about being intimidated by the technology or by anyone using it, but rather about using it as a resource to complement what’s already in your “f”;&;; head. The key is to take what’s in your brain, use it to ask the right questions, and direct the AI to help you work through complex problems. The goal here is collaboration, not competition. By using these tools effectively, we can make great s;:t happen and make a better world.

When a colleague feels intimidated by your AI upskilling, it's crucial to foster a supportive environment. Encourage them to view AI as an opportunity rather than a threat. Offer to share your knowledge, suggest resources, and perhaps even learn together. By promoting continuous learning and collaboration, you can help ease their concerns and build a stronger, more future-ready team.

Well it’s important to know that even someone who’s a master at something , once started from 0 . While intimidation is a more common than not feeling in an ever growing tech field , it’s also crucial to not let it be a reason for you to not pursue something , just because someone else is far better at it than you are . All things take time , and while we may be miles behind on a topic others have aced , it’s never too late to start . After all , it’s better to start and see progress in a few months , than to never start in the fear of never catching up :)

One thing I found very useful in AI journey is I was able to allocate time for self to learn and up skill The best learning is self learning try the same

It's natural for team members to feel intimidate about new technology, especially when it seems complex or unfamiliar. To address this situation constructively, it's crucial to adopt a supportive and inclusive approach. - Encourage gradual learning at their own pace. - Offer beginner-friendly materials to get them started. - Ensure they feel comfortable asking questions. - Share your own learning journey and discuss practical benefits. - Actively offer your expertise through discussions and collaborative projects.

Encourage learning by making AI a shared journey with your colleague to reduce intimidation and build camaraderie. Highlight their strengths and show how AI complements their skills, transforming it from a threat into a valuable tool. Offer support by sharing resources or answering questions, demonstrating your investment in their success. Finally, promote a mindshift—encourage them to see AI as a colleague, not a replacement, to make it more approachable and foster a productive working relationship.

Overcoming a fear of any topic, such as AI, comes down to a fear of the unknown be it fear of being replaced, fear of not understanding, etc. The best path through this fear is education & understanding! Firstly, reassure your colleague that AI upskilling is totally within reach & a valuable skill set that anyone can learn Explain to them you don't need to be an expert in computer science or statistics—most of the heavy lifting is done by pre-built libraries The key is understanding when to use AI & how to interpret the results Help them set achievable goals & milestones, showing that you’re in it with them By creating a step-by-step plan, you’ll help turn any fear into excitement showing that AI isn’t a challenge it’s an opportunity!

I for one am grateful for the hard work by the Danish Rights Organisation in bringing down illicit datasets, and any partial victory in the many rights holder lawsuits such as Getty v Stability, Andersen v Stability and Kneschke v Laion! 🎉🥳👏👏

When AI leads to success, it’s not just a personal win—it’s a team celebration. By highlighting how AI has contributed to our collective goals, we can shift the narrative from fear to excitement. It’s important to show that AI isn’t just about individual upskilling, but about creating value for the entire team and organization. When we embrace AI together, the benefits ripple across the board—making our work smarter, faster, and more impactful. Let’s celebrate these wins as a team and recognize AI as a tool for shared success.

AI upskilling can feel overwhelming, but it’s a chance to grow and innovate together. It’s important to foster a supportive culture where learning is encouraged at every step. Pairing up skilled colleagues with those less familiar can promote mentorship and make the learning process less intimidating. Encouraging team-based learning sessions where everyone can share insights and progress helps demystify AI and showcases its practical benefits in our everyday tasks.

A success guided by a professional trained in artificial intelligence should be celebrated by the company and be reason enough to make the reasonable doubt whether to expand its use to other areas of the company, but while it is very good to use it, without a professional instructed and educated in the use the result will be poor and unconvincing.

Importantly, always remember you are on a team! Share your lessons learned with others so they stay on your team too. As AI begins accelerating your own workflow, it can be intimidating to teammates of yours who haven’t had the chance to learn and experiment. Invite them to join you in learning to use AI effectively. Not only will they become a better fan and supporter of your work, but the whole team will become more productive. Your teammates will realize that the AI (and your using it) is not a competitive threat to their job, but an opportunity for all to seize. Productivity, and revenue stand to improve dramatically through shared AI upskilling.

AI quickly became my invaluable coding companion and discussion partner, drastically boosting productivity. I completed a project solo in one month that previously required a team of five over two and a half weeks. While this efficiency might raise job security concerns, it actually expands opportunities. AI-driven productivity lowers the barrier for smaller businesses to invest in custom software, potentially increasing demand for developers across various industries. By embracing AI, we're creating new avenues for growth and innovation in software development, not replacing jobs. Being cheaper and faster allows us to reach broader market.

Inclusion plays a crucial role in learning. When you include your colleagues in success of an AI project, they'll try to associate themselves with the results and will be motivated to deepen their understanding about AI. So when the next time such an opportunity arise, they'll start actively involving instead of feeling left behind.

Start with a game plan to introduce AI into everyday workflow: 1. Start with simple tasks like summarizing 2. Document creation 3. Data manipulation 4. Creating and summarizing meeting notes The possibilities are endless.

I would explain how artificial intelligence works and how to apply it to small uses to make repetitive tasks a thing of the past, but while I can help you get started, it is up to you to continue on the path of artificial intelligence, you must be interested and be consistent.

Setting realistic goals in AI integration is crucial for demystifying the technology and fostering a culture of continuous improvement. By starting with small, manageable tasks, you not only build confidence but also create a framework for measuring success through key performance indicators (KPIs). This iterative approach allows teams to adapt to the dynamic AI landscape, minimizing risks associated with long-term planning. Celebrating small wins reinforces the value of automation and reduces operational toil, ultimately aligning AI initiatives with broader business objectives and driving cost efficiency.

Right now I'm using AI to convert tables into other tables, spellcheck, grammar check, generate code snippets for libraries I'm not familiar with, and getting suggestions on other ways to convey my thoughts in writing. This isn't everything but it's my most commonly used functions. All those things are trivial to look up, or exist in word already, or can be done with a simple python function, but it saves me the headspace when I'm trying to focus on other tasks. I would suggest using and developing AIs in a similar fashion, it's not all about creating a big model to streamline your main task, it's about reducing trivial tasks further into triviality. So make AI's to solve your trivialities, I got mine to track my weight.

When introducing AI concepts to colleagues, I find it helpful to set realistic and achievable goals. This can mean starting with simple projects or learning tasks that build confidence without overwhelming them. Setting small, attainable goals helps make AI more accessible and less intimidating. How do you approach goal-setting when helping colleagues adapt to new technologies?

One way to navigate a colleague's intimidation by your AI upskilling is to shift the focus from comparison to collaboration, especially through joint goal-setting. Instead of positioning AI as something you’ve already mastered, suggest setting shared, achievable goals that both of you can work towards. For example, you could propose learning a specific AI tool together or tackling a small project that incorporates AI.

Start small and avoid trying to boil the ocean with everything AI can do. Begin by integrating AI into daily, mundane tasks that typically burn you out. This allows you to focus on missed opportunities and strategic initiatives. 1. Identify Low-Hanging Fruit: Start with simple, repetitive tasks that consume time and energy. Let AI handle these to free up your schedule. 2. Gradual Integration: Gradually introduce more advanced AI use-cases as your team becomes comfortable and confident with the technology. 3. Focus on Impact: Prioritize AI applications that offer immediate, tangible benefits to your workflow and productivity.

There is no point in trying to eat an elephant whole. It is always a good idea to divide it into pieces. AI projects consist of many stages. Understanding the data, cleaning the data, feature engineering, building models, testing the models, translating the models' answers into business language. And at each of these stages, many approaches can be used and many discussions need to take place. This teaches humility.

As part of my work in Automation CoE, I noticed a colleague growing uneasy about my progress esp. after I did an 1 year Executive Data Science course. Seeing this, during a casual lunch, I shared an example of how I was using AI to streamline a complex task and invited them to collaborate on a Pilot I was working on for an internal team. By working together, we turned a competitive situation into a learning opportunity, blending our skills to enable successful outcomes & meeting desired metrics. An inclusive approach helped win not just his confidence but enabled others to join-in & participate in brainstorming which helped us build new ideas and solution resulting in a cohesive learning and overall growth in the team.

To ease your colleague’s intimidation about your AI upskilling, emphasize how your skills complement theirs. First, identify and acknowledge their unique strengths. Highlight that AI can’t replace essential human qualities like empathy and creativity, which are crucial for decision-making. Explore how AI can enhance their expertise, such as using it to analyze data while they focus on interpreting results. Share examples of AI improving work efficiency and stress that AI can handle routine tasks, freeing them for more strategic and creative work.

Inclusion is key. To facilitate and inclusive environment we need to establish psychological safety so that everyone feels comfortable to voice concerns and fears and asks questions. Sharing mistakes is key as it shows we all struggle and we encourage learning from mistakes. No mistakes without taking risks. Feedback cycles complement the framework and coaching is the management style we need to apply here. Over time, all team members will feel included and part of the journey!

To foster an inclusive environment, collaborate with your colleague by offering to learn AI together, share resources, and position yourself as a supportive mentor. Acknowledge their strengths and how these can complement AI efforts, ensuring they feel valued in the process. Tailor AI discussions to their interests and work, showing how AI can enhance rather than overshadow their role. Encourage them to share their unique perspectives in AI-related decision-making, which promotes diversity and innovation while making them feel like a key contributor to the team's success.

One thing I have found helpful is the consistent research and development in the field of AI. Be it exploring the tools here and there. Or be it just by reading the article and success stories. I feel lucky to be in a place where the learnings are not kept in the documents or in someones mind but is being shared on the open forum so that everyone around can take the benefit of it. While saying this I remember the quote from Albert Einstein "If you can't explain it simply, you don't understand it well enough."

Create a safe space, I make sure everyone feels comfortable asking questions and sharing their thoughts. Encourage peer-to-peer learning, which facilitates knowledge sharing among team members.

I would have to explain to you what are the short, medium and long term objectives of the use of Artificial Intelligence and if the objectives seem adequate to you and if you notice similar, disparate or new objectives, in order to reach a joint agreement.

This is something I write about often and the real benefit in AI solutions is what I call ROE - return on employee. Including the real user in design, in key decisions and in roll out of AI solutions is what makes them really successful. I see this time and time again, where if its built by a user in mind and inclusively then its going to be adopted by their peers.

Convide-o a trabalhar com você em um projeto onde você domina as técnicas de IA utilizadas. Deixe claro que você acredita que ele pode contribuir significativamente para o projeto. Sugira dividir o projeto em etapas onde ele possa liderar uma parte específica. Ofereça-se para mentorar seu colega ao longo do projeto, compartilhando seu conhecimento em IA e explicando conceitos de forma prática. Demonstre que está disponível para ajudar sempre que ele precisar.

Generative AI is still in its infancy, and there is so much to learn. If you’re someone who has taken the initiative to learn this new skill, pay it forward by sharing your knowledge with colleagues. I have been posting my experiments with generative AI tools on LinkedIn daily, offering tips I’ve learned along the way. I also follow like-minded artists who share their experiences. I’ve found that the generative AI community is full of support and is willing to go out of its way to help you succeed. If you find someone doing something you could learn from, don’t hesitate to reach out to them. I’ve found people to be extremely receptive.

Try to offer to your colleagues any kind of support when navigating onto AI upskilling. Make a supportive environment can make a huge difference in transforming your workplace in a meaningful manner. For instance try to manage a small group of people to better understand the impact of emotional intelligence when relying on AI driven thinking.

I cannot believe that you got a second version of the same laughable question within days of each other. Also what the <bleep> does AI upskilling even mean or entail?

Sharing knowledge and support always helpful at every stage i believe. Its boost the moral of learning and by offering support you will learn by many ways. So, in my opinion support with open hands to step ahead.

Instead of positioning yourself as a mentor, collaborative learning environment always works. Set up some zoom sessions with team members and start up with explaining a simple problem. Try to resolve them together. I have even got some surprises from my colleagues during these kind of sessions about their knowledge. In nutshell, per my experience, offering support not as a mentor but a collaborative colleague goes a long way!

Some people have to see to believe. Use the Cognitive Apprenticeship approach. Show your colleagues how you have used AI to make your job easier. Show them real-life work-related examples they can start to use for themselves. Guide them with some gamification using AI prompts and compare the results. Create conversations with them based on contrast and comparison. Use the "desired outcomes" approach when writing prompts to see who can create a prompt that reaches the desired outcome the closest. Make it fun and keep it simple. Working with AI does not have to be complicated - nor is it something someone should fear. It is the future of learning.