Marketers from all over the world want to be in the artificial intelligence industry, and we don't blame them.
Why wouldn't they? AI has grown to be a fascinating, challenging, fast-paced and innovative industry — all in a little over a year.
Nevertheless, as exciting as it is, there are certain nuances you have to take into account if you decide to pivot and start a career as a marketer in the AI space.
Let's go over them to ensure your future success in this beautiful sector.
In this edition of The AI Navigator, you'll find:
- Marketers: Here are 3 things to consider if you want to work in AI.
- Take the reins of your work with these tips on how to use AI as a powerful decision-making tool.
If You're Marketer Looking to Pivot to AI, You Need to Know This
Everyone wants to ride the AI wave, from tech giants like Google, Microsoft, or Meta — who have invested billions in new AI projects — to professionals looking to take an interesting turn in their careers.
If you're one of the latter, congratulations! You've taken the first step towards an amazing journey. However, it's important to note that the AI industry is unlike any other.
Here are three aspects you need to take into account:
- Standing out in a crowded market: Marketers in the AI industry must be innovative and persistent to differentiate their professional profile amidst fierce competition, emphasizing unique customer stories and out-of-the-box tactics. In other words, the more the industry grows, the more competition you'll have, and the more creative you'll have to be!
- Educating customers on AI: Given the complexity of AI, you'll have to assume that most of your potential customers likely don’t understand AI or what it can really do for them. In this regard, you'll always need to educate them on its capabilities, value, and security measures to build trust and facilitate adoption.
- Embracing Adaptability: Success in the AI industry hinges on the ability to adapt quickly to changing regulations, compliance standards, technological development and customer expectations, requiring marketers to be agile and responsive. This industry is not for the faint of heart! Things can go change or go sideways very quickly. If you enjoy a calm, peaceful work environment, it may not be what you're looking for!
AI may be an exciting industry to work in, but it's also very demanding. Make sure you understand the challenges that come with a career in AI and prepare yourself accordingly!
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7 Steps to Harness AI to Make Better Decisions
Sometimes, the toughest conversations are with ourselves, especially when it's about tough decisions.
It's often cumbersome to have a clear idea of all the possibilities, circumstances, and factors that come into consideration. Some people ask for external opinions, other use pros-and-cons list.
Now, another option has emerged: artificial intelligence. Indeed, new solutions have enabled multiple innovative approaches to decision-making.
Here are some key steps individuals and organizations can take to leverage AI as a decision-making tool provided by Kuang Xu, Associate Professor of Operations, Information, and Technology at Stanford:
- Identify decision points: Begin by pinpointing specific areas where decisions need to be made. Clearly defining decision points provides a framework for integrating AI solutions.
- Data gathering and preparation: AI relies heavily on data, so ensure you have access to relevant and high-quality data sets. This may involve collecting data from various sources, cleaning and organizing it to ensure accuracy and consistency.
- Selecting the right AI tools: There are a plethora of AI tools and algorithms available, each suited to different types of decision-making tasks. Depending on the nature of your decisions, consider whether you need machine learning algorithms for predictive analytics, natural language processing for text analysis, or optimization algorithms for resource allocation.
- Training and implementation: Once you've chosen the appropriate AI tools, it's essential to train them using your prepared data. This step involves feeding the AI system with historical data to enable it to learn patterns and make predictions or recommendations. Implement the trained model into your decision-making process, ensuring it aligns with your objectives and constraints.
- Monitoring and evaluation: Continuously monitor the performance of your AI-driven decision-making system. Evaluate its effectiveness in generating insights or recommendations, and be prepared to fine-tune or update the model as needed to ensure optimal outcomes.
- Human-in-the-loop approach: While AI can provide valuable insights, it's essential to maintain human oversight throughout the decision-making process. Adopt a "human-in-the-loop" approach where human judgment is integrated with AI-generated insights. This ensures that decisions consider both data-driven recommendations and contextual nuances.
- Iterative improvement: Decision-making with AI is an iterative process. Learn from past decisions and their outcomes to refine future strategies. Continuously seek opportunities to improve data quality, algorithm performance, and decision-making frameworks.
Consider one final thing: not everyone's brain works the same way. While this is a general guideline to use AI for decision-making, you should pay close attention to what works for you in particular, and fine-tune the process according to your personal experience.
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Retired. (Mostly harmless).
7 个月An iterative and "human-in-the-loop" approach - great Success Factors!!