Seus concorrentes estão à frente na adaptação da IA. Como você pode acompanhar as mudanças do setor?
Você está pronto para preencher a lacuna da IA? Compartilhe suas estratégias para ficar a par das inovações do setor.
Seus concorrentes estão à frente na adaptação da IA. Como você pode acompanhar as mudanças do setor?
Você está pronto para preencher a lacuna da IA? Compartilhe suas estratégias para ficar a par das inovações do setor.
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Be very cautious with adopting an attitude of "we need to do AI to keep up with our competitors!". You rarely have an "AI challenge" - you have business challenges; for example : the need to protect and increase your share of market and share of wallet by running your business more efficiently, the requirements for better acquisition, servicing and retention of your customers, and needing to improve / sustain product and services innovation, production and pricing of your products and services. These are BUSINESS CHALLENGES, not AI challenges! Focus on the business challenge, then ask "How can AI help with solving this"? Uplift AI value through addressing business challenges, not the other way around!
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To bridge the AI gap, focus on integrating AI tools into your existing processes. Begin with small, scalable projects that meet immediate business needs. From my experience with machine learning and Generative AI, collaboration between tech and business teams is crucial. Use cloud platforms like Azure, AWS, or Databricks for quick prototyping and scaling. Also, invest in upskilling your team and foster a data-driven culture to stay competitive.
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This is my 50 cents on catching up in AI adaptation: To close the AI gap, it’s essential to focus on integrating AI tools into your current processes. Start with small, scalable projects that address immediate business needs. In my experience working with machine learning and applying Generative AI, collaboration between tech team and business teams is key. Leverage cloud platforms like Azure, AWS or Databricks for rapid prototyping and scaling. Also, invest in upskilling your team and ensure a data-driven culture to stay competitive.
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Invest in ongoing training programs for your team to keep up with the latest AI technologies and methodologies. Encourage participation in AI conferences, workshops, and online courses to stay updated on emerging trends and best practices. Adopt agile methodologies to quickly integrate new AI tools and techniques. Regularly review and update your AI strategies based on feedback and performance metrics, ensuring your approach remains flexible and responsive to industry changes. Encourage a mindset of continuous improvement and experimentation within your organization. Create an environment where employees feel empowered to propose and test new AI ideas. Recognize and reward innovative contributions to maintain momentum.
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One of the best ways to start learning in AI is to get it into your daily algorithm and routine. Comment on the article and follow the Artificial Intelligence topic here. Search for AI on YouTube, and do a search for industry newsletters on AI. Usually, I recommend reading the top 5 book on Amazon, but AI is moving so fast that it is probably better to subscribe to some podcasts instead.
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