Here's how you can emphasize the value of continuous AI training and upskilling to your team.

Understanding the basics of AI is essential. Make sure your team has a solid grasp of fundamental concepts like machine learning, neural networks, and data analysis. This foundational knowledge ensures everyone is on the same page and can contribute meaningfully to AI projects. Encourage your team to engage with learning resources and workshops that reinforce these core principles. A well-grounded understanding paves the way for more advanced learning and application. To foster this foundational knowledge, provide access to online courses, webinars, and hands-on workshops tailored to different learning styles and experience levels. Promote a culture of continuous learning by setting aside dedicated time for study and discussion.

Continuous AI training and upskilling are crucial for any team working with technology. It ensures that team members are always aware of the latest advancements and techniques in AI. This knowledge is vital because AI is an area that evolves rapidly, and staying updated means the team can apply the most current and effective methods to their work. Upskilling also allows team members to handle more complex tasks and challenges, keeping the team dynamic and adaptable. In essence, continuous AI training and upskilling are about maintaining a high level of proficiency and expertise, which is essential for achieving excellence and driving innovation in any field.

As an AI and data student, I find it very important to actively engage with a variety of learning resources DAILY to stay current with AI advancements. Dive into free online courses, workshops, and industry articles to reinforce your foundational knowledge. Join AI communities and forums to exchange ideas and learn from peers and experts. Follow influential AI researchers and organisations on social media to help you catch the latest breakthroughs and trends. By immersing yourself in these activities on a regular basis, you'll solidify your foundational understanding but also stay ahead with the latest techniques and innovations. AI changes fast! The key is to continuously learn.

Recognizing that a strong foundation is key to successful AI implementation, I prioritized AI fundamentals for my team. We engaged in workshops covering machine learning basics, from regression to classification, and delved into neural networks, exploring their architecture and applications and most importantly understanding the data that the team is working with and are able to apply the above techniques. To solidify understanding, we applied these concepts to real-world data, analyzing datasets and even building simple models. This foundational knowledge fostered a common language and empowered everyone to contribute meaningfully to our AI initiatives.

Make part of the studies group like financ.ia Understanding the fundamentals of AI is essential. Ensure that your team has a solid grasp of core concepts such as machine learning, neural networks, and data analysis. This foundational knowledge guarantees that everyone is on the same page and can contribute significantly to AI projects. Encourage your team to engage with learning resources and workshops that reinforce these basic principles. A well-grounded understanding paves the way for more advanced learning and application.

Highlight Industry Trends: Share insights on AI advancements, new techniques, and emerging tools. Illustrate how staying updated enhances productivity and innovation. Showcase Success Stories: Present case studies where upskilling led to improved project outcomes or career growth. Real-world examples resonate with team members. Organize Workshops and Webinars: Arrange sessions on AI topics, certifications, or best practices. Encourage participation and provide learning resources. Set Learning Goals: Discuss individual development plans. Encourage team members to allocate time for learning and attend relevant courses. Remember, investing in skills pays off in the long run! 🌟🚀

🤖 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗮 𝗦𝘁𝗿𝗼𝗻𝗴 𝗙𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻 🤖 Understanding the basics of AI is essential. Make sure your team has a solid grasp of fundamental concepts like machine learning, neural networks, and data analysis. This foundational knowledge ensures everyone is on the same page and can contribute meaningfully to AI projects. Encourage your team to engage with learning resources and workshops that reinforce these core principles. A well-grounded understanding paves the way for more advanced learning and application. In market research, mastering AI fundamentals is like laying the groundwork for a skyscraper. 🏗️📈

AI is constantly evolving, and to stay ahead, we need to keep learning. Here’s why continuous AI training and upskilling are crucial: 1. Stay Updated: AI tech changes fast. Regular training keeps us on top of new trends and tools. 2. Boost Efficiency: The more we know, the better we can streamline our work. 3. Enhance Creativity: Learning new AI techniques sparks fresh ideas. 4. Stay Competitive: Upskilling helps us outperform the competition. Commit to ongoing learning and make the most of AI!

Explain how the AI field is constantly evolving with new techniques, tools, and research. Highlight that advanced learning equips the team with the latest knowledge, enabling them to tackle complex problems more efficiently and creatively. Show how mastery of advanced AI concepts, such as deep learning, natural language processing, and reinforcement learning, can lead to innovative solutions and maintain your competitive edge. Share success stories from the industry where advanced skills led to significant improvements and breakthroughs. Encourage a culture of lifelong learning by offering access to advanced courses, workshops, and conferences.

By fostering a culture of continuous learning in advanced AI topics like deep learning, natural language processing, and computer vision, your team can enhance their capabilities to tackle sophisticated projects and offer innovative solutions. Encourage hands-on experience and experimentation in applying these concepts to real-world scenarios for practical skill development.

Once your team is well-versed in AI fundamentals, advancing their knowledge in specialized areas becomes crucial for fostering innovation and tackling sophisticated projects. In my role, I encourage my team to explore deeper into areas like deep learning, natural language processing (NLP), and computer vision—fields that are pivotal for enhancing our marketing strategies and creating cutting-edge solutions. To support this advanced learning, I make sure to provide access to specialized courses, often through platforms like Coursera and Udacity. Additionally, I encourage participation in relevant industry conferences, which not only offer deep dives into these subjects but also provide networking opportunities with other AI professional.

Investing in your team members is the best investment for any organization. Create an environment where your team feels comfortable talking about AI, sharing what they know and what they don’t. Encourage them to express what they want to learn, how they want to learn, and how they can contribute to the organization’s AI journey. Whether it’s deep learning, natural language processing, or any other AI topic, support their interests and foster a culture of continuous learning.

Emphasizing the importance of ongoing AI education requires framing it as a catalyst for innovation and career growth. Showcase real-world examples of how advanced AI skills directly correlate with groundbreaking projects and industry leadership. Implement a "learning leaderboard" that gamifies the pursuit of new AI knowledge, recognizing top learners. Organize regular "AI Deep Dive" sessions where team members present on cutting-edge topics they've mastered. Create personalized learning paths that align individual interests with organizational goals.

Encourage your team to delve into complex AI topics like deep learning, natural language processing, and computer vision. By mastering these advanced concepts, your team can handle sophisticated projects and offer innovative solutions. Provide access to specialized courses and encourage participation in industry conferences to facilitate this higher-level learning.

Once beyond the basics, and your team is ready to dig in deeper, it may be more useful to build out internal learning pathways and opportunities, or to bring in subject experts to help lead hands-on workshops. While many specialized courses can help add perspective, the quality or the specific focus on application may not neatly fit your needs. Providing access and encouragement is one thing, but bringing learning directly to your team and being an example of higher-level learning both internally and at conferences, can have a much bigger impact on your team's growth. When it comes to AI or any new technology, adoption is mostly driven by motivation, which is driven by top-down examples more often that not.

To emphasize continuous AI training, foster a culture of learning and innovation. Encourage your team to explore advanced AI topics like deep learning, natural language processing, and computer vision. Provide access to specialized courses and industry conferences. In my career, updating my skills in marketing automation and data analytics led to innovative solutions, such as a 30% increase in conversion rates at AirGarage. Inspired by "Deep Work" by Cal Newport, I prioritize focused learning sessions to master complex topics, driving personal growth and team success. This approach ensures your team stays ahead in the tech landscape.

Showcasing actual value with AI will encourage people to want to learn to make meaningful contributions. Otherwise, if there's no obvious utility in using an AI function or tool, there's little point to do anything more with bring it to your team's attention. Setting up presentations, quick demos, and hackathons are great ways to showcase applicable value.

We like to get our hands dirty! We hold regular hackathons, like friendly competitions you see, where the team gets to play around with new AI tech. Think of it like training on the range – you gotta put your knowledge to the test before it counts. These hackathons are a blast – they get the creative juices flowing something fierce. Folks experiment, come up with new ideas, and then share their findings with the whole tribe. It's all about learning from each other, see? You teach me something new about AI, and I'll do the same for you. That's how we grow stronger, together.

Hackathons can be a great way to get your team to think creatively in a fun collaborative environment. It allows them to expand out of the normal scopes of work and try out new innovative ideas as well as gives them room to make mistakes without negatively impacting a job. constant R&D really is the best way to come up with new practical use cases for implementing AI

I emphasize hands-on learning by holding regular hackathons, where our team can experiment with new AI technologies in a fun, competitive environment. This approach allows us to test our knowledge and generate creative ideas, which are then shared among team members, fostering a collaborative learning culture. Additionally, organizations need an experimentation strategy for continuous innovation. AI innovation shouldn't be limited to technical teams; subject matter experts should have a safe space to prototype and share ideas, receiving feedback for refinement. The best use cases come from democratized experimentation, with validated ideas receiving investment to scale into production.

Highlight how ongoing training directly translates into enhanced problem-solving abilities and the capacity to implement AI solutions effectively in real-world scenarios. Explain that learning new AI techniques and tools is not just theoretical but essential for improving project outcomes and operational efficiency. Provide examples of past projects where newly acquired skills led to innovative solutions or streamlined processes. Encourage hands-on workshops, hackathons, and real-time project applications to solidify learning. Show how practical application of AI skills can drive the team's success, foster innovation, and keep the organization competitive.

Organizations need an experimentation strategy not just for learning, but for continuous innovation. AI innovation shouldn’t be confined to technical teams. It’s crucial to have a safe environment where subject matter experts can create and share prototypes of their ideas with team members, and receive feedback for refinement without significant investment. The best use cases arise from democratized experimentation, and only validated ideas should receive the necessary investment to scale into production.

To truly emphasize the value of continuous AI training, integrate practical application into your team's routine. Implement 'AI Fridays' where team members dedicate time to working on personal AI projects or exploring new AI tools. This hands-on approach not only reinforces theoretical knowledge but also fosters innovation and creativity. Encourage sharing these projects in monthly showcases, fostering a culture of collaboration and continuous improvement. By doing so, you transform learning into a tangible, engaging, and regular part of the team's workflow, driving both personal and organizational growth.

By providing a platform for hands-on experimentation with AI technologies through regular hackathons and project days, teams can cultivate a collaborative and creative environment. This practical application solidifies learning, fosters creativity, and encourages knowledge-sharing among team members, ultimately strengthening the collective expertise in AI.

Continuous AI training and upskilling are super important, but the real magic happens when we put theory into practice. That’s why, in my Beginner’s AI Masterclass, I let the audience pick the topic. Every class is unique, which keeps everyone engaged and excited. This hands-on approach solidifies learning and sparks creativity. In my Prompting 101 class, we do something similar. Students work on different prompt styles tailored to their businesses, all from their own laptops. This makes the learning super relevant and practical. Let’s keep pushing the boundaries of what we can do with AI by focusing on continuous learning and practical application. Empower your team, and watch the magic happen!

Practical application of AI through hackathons and project days solidifies theoretical knowledge and drives innovation and creativity within your team. By fostering a collaborative environment where team members share their projects and results, you cultivate a culture of continuous learning and peer-to-peer mentorship. This approach aligns with entrepreneurial principles, encouraging calculated risk-taking and resourcefulness, ultimately propelling your venture toward market disruption and success.

Peer learning is a powerful tool for reinforcing and expanding AI knowledge. After my first group training session, students asked for monthly meet-ups to discuss their projects, share hints and tips, and get feedback. This approach not only spreads knowledge but also builds a supportive community where members feel comfortable seeking help and sharing insights. Let's encourage study groups and mentoring sessions to enhance our overall AI expertise. It's a great way to network and support each other as we explore AI.

The truth is, some of the best learnings come from right here, within our own tribe. That's where peer learning shines brighter than a midday sun. Imagine this: study groups where our team huddles up, sharing knowledge like seasoned warriors. One's an expert in natural language processing? They can teach others. Another's a whiz at computer vision? They become the guide. By learning from each other, we not only build a stronger team, but also a supportive village where everyone feels comfortable asking questions and sharing ideas. This teamwork spirit, this open exchange – that's what makes CIZO's AI expertise truly powerful.

Look, keeping your AI skills sharp isn't just a nice-to-have, it's like the secret sauce in a killer dish. Here's the breakdown: - Think of AI as a fast car, and continuous training is the high-octane fuel that keeps it zipping ahead. Stay in the know, or you'll be eating dust. - Upskilling? It's the gym membership for your brain. The more you train, the stronger your AI muscles get. - It's not about chasing every new trend—it's grabbing onto the tools that'll get your job done better and faster. Makes sense, right?

Continuous AI training and upskilling are crucial in such a dynamic field, where technology evolves every month. Some things that were cutting-edge last semester may become obsolete in a matter of months. This is why hiring experts in the same manner as for traditional software development does not work here. Experts of today may become outdated extremely fast, so they will need to constantly learn. The key is in knowledge sharing as part of this upskilling effort. Being part of a community ensures everyone has access to the highest quality, curated content, increasing the efficiency of learning.

Peer learning democratizes AI knowledge within your team and fosters a culture of innovation and resilience, which is essential for navigating the fast-paced tech landscape. By encouraging collaborative study groups and mentoring sessions, you empower your team to tackle complex AI challenges collectively, leveraging diverse perspectives for more robust solutions. This approach aligns with entrepreneurial principles, driving both individual growth and collective success.

Encouraging continuous AI training through peer learning can transform your team's expertise. At Google, engineers often participate in internal study groups and mentoring sessions to share their latest findings in AI research. Similarly, at Facebook, peer-led workshops are a common practice to stay updated with the latest AI developments. These initiatives align with the principles outlined in "Team of Teams" by General Stanley McChrystal, which emphasizes the power of collective problem-solving and shared knowledge. By fostering a collaborative learning environment, you build a team that is not only skilled but also supportive and innovative.

Encouraging peer learning in AI training fosters a knowledge-sharing culture within the team. By organizing study groups and mentoring sessions, team members can collaborate, teach, and learn from each other, building a supportive community. This collaborative atmosphere not only enhances overall AI expertise but also boosts team morale and engagement.

As someone studying AI & ML in BTech, I've found peer learning incredibly valuable. Each of us has our own strengths and ways of understanding concepts. Personally, I find discussing with peers more enriching than learning from online sources alone. Whether you're a student or a professional, engaging in group discussions allows you to connect with others who understand your challenges and can offer different perspectives. It's a great way to strengthen your AI skills and foster a supportive team environment where everyone benefits from shared knowledge and experiences.

Peer learning is a powerful tool for reinforcing and expanding AI knowledge. Promote the organization of study groups or mentoring sessions where team members can teach and learn from each other. This builds a supportive community, making members comfortable seeking help and sharing insights. Such a collaborative atmosphere significantly enhances the team’s overall AI expertise.

Peer learning is indeed a powerful tool! By encouraging study groups and mentoring sessions, we create an environment where team members can teach and learn from each other. This not only spreads knowledge effectively but also fosters a supportive community. In such a collaborative atmosphere, everyone feels comfortable seeking help and sharing insights. This approach significantly enhances the team's overall AI expertise and drives continuous growth.

Continuous feedback loops are the lifeblood of AI innovation, enabling teams to swiftly identify and address knowledge gaps, thereby accelerating learning and improvement. By fostering an environment of regular testing and open discussions on recent advancements, you ensure your team remains at the cutting edge of AI technology. This iterative process aligns your team with industry trends and cultivates a culture of perpetual growth and adaptability, essential for entrepreneurial success.

Think of it this way. You ever learn a new recipe? You have to keep practicing, right? Gotta tweak it here and there to get it just perfect. Same goes for AI. We gotta keep training those AI models, just like practicing a recipe. But how? That's where my team comes in. Here at CIZO, we all gotta be learning together. We gotta give each other feedback. We have to be testing out those AI models all the time. And if something isn't working right, we must talk about it. Share what we learned, where we hit a snag. That way, the whole team learns and grows smarter together. That's how we stay ahead of the curve in this ever-changing world of AI.

Junior members learn from senior experience, and everyone benefits from diverse perspectives. Feedback helps pinpoint areas where training materials or the AI itself needs improvement. This allows to address weaknesses before they become major roadblocks.

Emphasize the importance of creating a culture where feedback is welcomed and valued. Encourage team members to actively engage in discussions about recent AI advancements and challenges faced during projects to foster collaboration and continuous learning. Acknowledge the significance of sharing insights and lessons learned to promote collective growth and excellence in AI development.

Embed Feedback into the Workflow: Integrate regular testing checkpoints throughout the development process. This allows for early detection and correction of issues, preventing them from snowballing later. Utilize Multiple Feedback Sources: Don't rely solely on internal testing. Consider incorporating user testing, A/B testing, and data analysis to gain a well-rounded perspective on the AI's performance.

Feedback loops are critical in AI development and learning. Encourage your team to continuously test their AI models and share feedback on training courses or materials. This helps identify knowledge gaps and areas for improvement. Regular discussions about recent AI advancements or challenges faced during projects provide valuable insights and keep everyone aligned with industry trends.

Feedback loops are indeed essential in AI development and learning. By continuously testing AI models and sharing feedback on training courses or materials, we can identify knowledge gaps and areas for improvement. Regular discussions about recent AI advancements and project challenges provide valuable insights and help keep the team aligned with the fast-paced industry. This iterative process not only refines our skills but also enhances our ability to tackle complex AI projects effectively.

Mejora del rendimiento: Utiliza la IA para recopilar y analizar datos de retroalimentación sobre el rendimiento de los empleados en los cursos de formación. Personalización del aprendizaje: Ajusta los programas de formación en función de las áreas de mejora identificadas y las preferencias individuales. Motivación y compromiso: Proporciona retroalimentación positiva y constructiva para mantener alto el nivel de motivación y compromiso del equipo con el aprendizaje continuo.

Continuous feedback is essential for effective AI training and upskilling. Encourage an open dialogue where team members can provide and receive constructive feedback on their AI learning journey Regularly solicit input on training programs to understand what works well and where improvements are needed Use surveys, one-on-one meetings, and group discussions to gather insights This feedback loop ensures that training remains relevant, addressing the evolving needs and concerns of your team By fostering an environment of continuous improvement, you can enhance the effectiveness of AI training, keeping your team engaged, motivated, and better equipped to leverage AI technologies

Our world is changing faster than ever, and AI is at the forefront! Here's how I keep my team ahead of the curve: 1. Growth Mindset: We learn from each other, just like the Prophet Muhammad (ﷺ) encouraged with his companions (رضي الله عنهم). 2. Bite-Sized Learning: Short, focused training keeps everyone engaged and avoids information overload. 3. Future Focus: We explore how AI can revolutionize our field, just like Vision 2030's focus on innovation! Investing in our team's AI skills empowers us all to create a brighter future!

Showcase New Roles and Responsibilities: With AI rapidly transforming industries, entirely new job roles are emerging. Explain how AI upskilling can position them for these exciting opportunities, like AI specialists, data analysts, or AI ethicists. Focus on Increased Responsibilities: AI can elevate existing roles. Demonstrate how AI skills can equip them to handle more complex tasks, manage AI-powered tools, and make data-driven decisions, leading to increased responsibility and influence. Highlight Career Path Options: AI expertise opens doors to diverse career paths. Outline how AI skills can be applied across various departments, allowing them to explore new areas within the organization and potentially transition to leadership roles.

I emphasize career growth to highlight the value of continuous AI training and upskilling to my team. I show how acquiring new skills opens up advanced career opportunities. I explain that staying updated with AI trends keeps their expertise relevant. I demonstrate how upskilling leads to greater job satisfaction and professional fulfillment. I share success stories of colleagues who have advanced through continuous learning. I encourage the team to view AI training as an investment in their future.

Highlight the career benefits of AI upskilling. Discuss how mastering AI can lead to new roles, responsibilities, and career paths within the organization. Show that learning and development efforts are recognized and can lead to professional growth. This recognition motivates individuals and aligns their personal development goals with the strategic objectives of the organization.

I've found it easiest to draw parallels between learning 'AI Skills' for one's career growth now as skill sets for "Microsoft Office" were once a differentiator, then necessity, and finally an expected skill set. While not everyone was (or is) expected to be an MS "power user" a certain level of knowledge and skills has become a standard and default. AI skill sets are following that same path, but at an even faster pace due to the increased access to tech hardware, AI software, and online learning. Right now, though, we all are at the forefront of this technology, so reminding your team how rare that opportunity is might best align personal growth opportunities with business objectives.

Highlighting the career benefits of AI upskilling can motivate your team. Show how mastering AI opens new roles and responsibilities within the organization, linking personal growth to strategic objectives. Recognizing their efforts fosters a culture of continuous improvement and innovation.

Desarrollo de carrera personalizado: Diseña trayectorias de carrera que incluyan oportunidades específicas de formación en IA para cada miembro del equipo. Certificaciones y reconocimiento: Apoya la obtención de certificaciones reconocidas en IA que validen las habilidades adquiridas y promuevan el crecimiento profesional. Retención de talento: Aumenta la retención de empleados al demostrar un compromiso continuo con su desarrollo profesional y personal.

Highlight how gaining AI skills can open new career opportunities, enhance their professional value, and position them for leadership roles in the evolving job market Showcase success stories of employees who have advanced their careers through AI proficiency Provide clear pathways for career development that include AI training and certification, showing how these qualifications can lead to promotions, higher salaries, and more exciting job responsibilities By linking AI upskilling to tangible career growth, you inspire your team to embrace continuous learning, benefiting both individuals and the organization by building a more skilled and motivated workforce

As a software engineer with years of industry experience, I think it's time to align my personal and career development with the upcoming changes. Using AI as a tool, we can create more automated workflows, reach our goals faster, and achieve better performance with less effort. AI is going to redefine current roles in the market, especially in engineering—just consider the rise of prompt engineering. I also believe that everyone, whether they're engineers or not, will adapt to AI just like they did with smartphones. I'm really excited to see how each person will use AI to their advantage.

Emphasize the competitive edge AI skills provide in job market. Showcase how AI proficiency can set team members apart from peers. Discuss potential for increased salary and job security with AI upskilling. Illustrate the market demand for AI expertise in various industries. Highlight the transferability of AI skills to different roles within organization.

Prepare your workforce for the AI-driven future with a proactive L&D approach. Stay agile, embrace continuous learning, and provide hands-on experiences to empower your team and thrive in the AI-powered era. Explore our latest insights to shape upskilling and reskilling in your organisation and prepare for future of work today.

In order to interest others, you first need to be interested in the topic yourself. A team will never start moving in the right direction if the leader is not a role model. Showing exactly how AI affects the business, improved key performance indicators (KPIs) or business goals, as well as examples of specific projects where AI, which is constantly learning, has brought significant benefits is the entire task of the manager. Constant communication and cooperation should be the basis, followed by training, work on the database and analytics, assessment of benefits and risks.

In addition to highlighting career growth and implementing strong feedback loops, here are some other ways to emphasize the value of continuous AI training and upskilling to your team: Focus on Future-Proofing Skills: The AI landscape is constantly evolving. Emphasize how continuous learning keeps their skillset relevant and in-demand, future-proofing their careers in a rapidly changing technological environment.

Consider highlighting the importance of fostering a culture of curiosity and innovation within your team, encouraging them to actively seek opportunities for learning and growth. Additionally, showcasing success stories of individuals who have benefitted from upskilling can serve as powerful motivation for others to invest in continuous AI training.

Finding suitable AI use cases and deciding when to start or stop can be challenging. Begin by understanding your company's goals and identifying key problems AI can solve. Involve various teams in brainstorming and study industry benchmarks. Evaluate the feasibility, benefits, and risks of each use case, prioritizing those with high impact. Start with a small pilot project, set clear KPIs, and measure results. Learn from outcomes and iteratively develop and scale successful projects. Regularly review progress, involve stakeholders, and set timelines for evaluating success. Be ready to pivot or terminate projects that do not show significant progress and therefore: generate significant amount of AI use cases and not only one!

Compromiso de liderazgo: La formación en IA debe contar con el respaldo y el compromiso visible de los líderes de la organización. Inversión estratégica: La inversión en la formación en IA no solo mejora las habilidades técnicas, sino que también fortalece la posición competitiva de la empresa en un mercado globalizado. Evaluación continua: Evalúa regularmente el impacto de los programas de formación en IA para ajustar y mejorar las estrategias de desarrollo profesional.

If your current job or team isn’t focused on AI, make learning it your hobby. Yes, you can go the formal education route but depending on your goals, it may not be necessary. Look for clubs, workshops (hackathons), and other ways to gain skills.

Encourage your team to stay updated with the latest AI advancements through continuous learning. Share real-life success stories and examples of how continuous learning has benefited AI professionals. This can inspire and motivate your team to pursue upskilling actively and consistently.

One thing I'm really excited about is how we use AI in the health industry. I've already seen some amazing initiatives and know what's possible in the future - like finding cures for existing diseases, which makes me very happy. I'm also thrilled about using AI as a tool for better education, especially for kids. They’ll use AI to bring so much excitement and creativity to their learning experiences.