Building Foundational AI Skills for Business

Want to improve your generative AI results? Looking for a proven approach to getting higher quality outputs?

In this article, you'll discover how to level up your AI skills.

The Hidden Psychology of Success and Failure With AI Skills

If you're overwhelmed by the rapid evolution of artificial intelligence in marketing, you're not alone. 

While 37% of marketers surveyed for Social Media Examiner's recent study, the Generative AI Marketing Industry Report now use AI tools daily, many are barely scratching the surface of what's possible with this transformative technology.

The journey to AI mastery follows a fascinating psychological pattern that few people discuss. 

Nicole Leffer, an AI advisor who specializes in training marketing teams from Series A startups to Fortune 50 companies and global brands, has repeatedly observed this pattern in her work. 

Understanding this pattern is crucial for avoiding the pitfalls that derail most marketers' AI adoption.

The Initial Honeymoon Phase

Most people begin their AI journey with a mix of skepticism and curiosity. They've heard the hype, seen colleagues posting about large language models (LLMs) like ChatGPT or Claude in their day to day work, and decided to dip their toes in the water. This initial exploration often leads to some impressive early wins. Maybe they generate a compelling email subject line or a social media post that performs well.

These early successes with create a surge of enthusiasm and optimism about AI's potential.

The Crisis of Confidence

What happens next is crucial, and it's where most marketers go wrong.

After those initial successes, results become inconsistent. The AI starts producing content that misses the mark. Prompts that worked before suddenly yield disappointing results. Leffer calls this “the critical valley,” and it's where most people abandon their AI journey.

“Most people are walking away at that point,” Leffer explains. “They have no idea what they're missing.” 

This premature abandonment stems from a fundamental misunderstanding of how AI tools work and how to communicate with them effectively.

The Path to Mastery

Those who push through this valley of disappointment discover something remarkable. With proper training and understanding, AI becomes not just useful but transformative. 

“I don't go more than a day or two without being completely mind-blown with what this technology is capable of,” Leffer shares. 

The key lies in mastering three fundamental areas: communication, capability understanding, and workflow creation.

#1: Mastering AI Communication: The Foundation of Success

The most crucial skill in AI mastery is learning how to communicate effectively with these tools. This skill goes far beyond simple prompt engineering – it's about developing a comprehensive communication strategy that consistently delivers results.

The Power of Role Definition in AI Projects

Every interaction with AI should begin with a clear definition of its role.

The role isn't just a formality – it fundamentally shapes how the AI approaches your request. 

“You should always be starting your conversation with telling the AI who it is in the context of this conversation,” Leffer emphasizes.

The specific language you use matters more than you might think.

Through extensive A/B testing with multiple AI tools, Leffer has discovered that saying “You are” produces consistently better results than “Act as.” The psychology behind this is fascinating. When you tell the AI to act as something, you're essentially asking it to pretend or mimic. But when you tell it that it is something, you establish a deeper framework for the interaction.

Consider these two approaches:

Wrong: Act like a social media expert and help me write a LinkedIn post about artificial intelligence in healthcare.

Right: You are the world's leading social media strategist with specialized expertise in LinkedIn B2B copywriting and deep knowledge of the healthcare technology sector. You have a proven track record of creating engaging content that strictly complies with healthcare regulations while driving meaningful engagement.

The difference might seem subtle, but the impact on output quality is significant. The second approach provides rich context that guides the AI's understanding and shapes its response.

The Surprising Impact of Politeness in AI Prompts

One of the most counterintuitive discoveries in AI communication is the importance of politeness. 

“There has been some really bad viral advice not to say please to the AI,” Leffer reveals. That's awful advice. There are actually studies that have come out that it improves the quality of the response.”

Being polite isn't just about adding pleasantries – it's about treating the AI as you would a knowledgeable colleague. The more human psychology you apply in your interactions with AI, the better your results will be. Examples include:

• Expressing appreciation for the AI's efforts
• Acknowledging the importance of the task
• Providing context about real-world impact
• Using please and thank you consistently
• Giving the AI time to think”through complex problems

The Art of Context Setting

Beyond politeness and role definition, providing rich context is essential for getting optimal results from AI tools. This isn't just about stating your immediate needs – it's about painting a complete picture that helps the AI understand the broader situation and objectives.

“You need to understand that things work in some contexts and not others,” Leffer explains. “It depends what you're doing.”

She's discovered that different psychological approaches work better for different types of tasks. For instance, telling the AI it's well-caffeinated can improve performance on analytical tasks but might hinder creativity.

When setting context, consider including:

Background Information: Our company is a B2B healthcare technology provider that helps hospitals streamline their patient intake processes. We're preparing content for a major product launch targeting hospital administrators and IT directors.

Specific Constraints: All content must comply with HIPAA regulations and maintain a professional, authoritative tone while still being accessible to non-technical decision-makers.

Clear Objectives: The goal is to generate interest in our new platform by highlighting its ROI potential and ease of implementation, ultimately driving demo requests from qualified prospects.

#2: Understanding AI Tool Capabilities: Beyond the Basics

One of marketers' most costly mistakes is underutilizing their existing AI tools while paying for specialized solutions. Modern AI platforms have capabilities that extend far beyond simple text generation, yet many users never explore these advanced features.

Input Capabilities: The Many Ways to Feed Information to AI

Text-based input remains the most common way to interact with AI, but it's just the beginning. Modern AI tools can process a wide variety of inputs, each with its own considerations and best practices.

Document Processing

When working with documents, you can upload PDFs and Word files directly to most AI platforms. However, there's a significant limitation to understand. 

“If you upload a PDF file to ChatGPT or Claude or one of these tools, they cannot see the images in that file,” Leffer explains. “You need to understand that it can read all of the words but not see any of the visual information.” Editor's note: Claude is now able to see images in PDFs. We recommend you test PDFs on any platform you are using.

This limitation requires strategic thinking about how you present information to the AI. You'll need to provide documents containing essential visual elements separately through screenshots or image uploads. The key is understanding how the AI processes different types of information and structuring your inputs accordingly.

Visual Processing

Modern AI tools' visual capabilities are remarkable yet often underutilized. These tools can analyze images with sophisticated understanding, interpreting everything from simple diagrams to complex infographics. They can identify objects, read text within images, understand spatial relationships, and even interpret emotional content in photographs.

For marketers, this opens up powerful possibilities:

• Analyzing competitor visual content for insights
• Evaluating ad creative for potential effectiveness
• Checking brand consistency across various materials
• Extracting data from charts and graphs
• Understanding design trends in your industry

Voice Input and Processing

Voice capabilities represent one of the most exciting frontiers in AI interaction. Many platforms now accept voice commands and can process voice memos, opening up new possibilities for efficient workflow creation. Leffer demonstrates this potential with her innovative travel journaling system, which starts with simple voice memos and ends with structured, formatted content.

“I could just ramble about my day,” she explains. “We woke up this morning and had a really good hotel breakfast…” 

This casual voice input transforms through AI processing into professionally formatted content, complete with organized notes and draft reviews for various platforms.

Output Capabilities: The Full Spectrum of Possibilities

Just as AI tools can accept various input forms, they can produce a wide range of outputs that many users need to explore. Understanding these capabilities is crucial for maximizing the value of your AI tools.

Text Formats and Styles

Beyond basic text generation, AI tools can produce content in various formats and styles:

• Markdown-formatted documents
• HTML-coded content
• Structured data in tables
• Technical documentation
• Formatted reports
• Email sequences
• Social media content threads

The key is understanding how to request specific formats and providing the necessary context for each output type.

Visual Content Generation

While not all AI tools can create images from scratch, many can assist with visual content in other ways:

• Creating charts and graphs from data
• Generating diagrams and flowcharts
• Designing simple infographics
• Suggesting visual layouts
• Providing image optimization recommendations

Code and Technical Outputs

For marketers working with websites or technical content, AI tools can generate:

• HTML and CSS code
• JavaScript snippets
• Meta descriptions
• Schema markup
• API documentation
• Analytics tracking code

Document and Asset Creation

Modern AI tools can help create various types of documents and assets:

• Word documents
• Google Docs
• Spreadsheets
• Presentation slides
• PDF reports
• Email templates
• Social media graphics

#3: Advanced AI Implementation: From Basic Tools to Sophisticated Workflows

Understanding AI capabilities is just the beginning. The real power comes from combining these capabilities into sophisticated workflows that can transform your marketing operations. Leffer's experience with both Fortune 50 companies and startups provides valuable insights into how to build these systems effectively.

Understanding Model Limitations and Strengths

Before diving into advanced implementations, it's crucial to understand some fundamental aspects of how AI models work. This knowledge will help you design more effective workflows and avoid common pitfalls.

Training Data

Every AI model has a training cutoff date, after which it doesn't have comprehensive knowledge of world events. “There is going to be a gap between when it was trained through… and when you're using it,” Leffer explains. This gap exists for important reasons, primarily related to safety and quality control.

When an AI tool searches the internet, it's not updating its core training. Instead, it's more like a human quickly scanning a few articles. 

“It's going to read a page or two or three and incorporate that into its response,” Leffer notes. 

Understanding this limitation helps you structure your requests more effectively and know when to supplement the AI's knowledge with additional context.

Safety Parameters and Capabilities

Another important consideration is that AI models often underestimate their capabilities. 

“Sometimes it'll tell you it can't do something, and all you have to do is say back is, ‘Yes, you can. I've seen you do it before,' and it'll be like, ‘Oh, okay,' and it'll do it,” Leffer shares. 

You shouldn't always take the AI's initial negative response as final.

Building Automated Workflows

The true power of AI emerges when you combine different capabilities into automated workflows. Leffer's travel journaling system provides an excellent example of how this can work.

The Input Phase

The workflow begins with simple voice memos recorded at the end of each day. 

“I would just ramble about my day,” Leffer explains. “I would be looking through my photos so I'd remember what we did. I'd look at my credit card receipts, name whatever of where we were going.”

She would email herself a quick list of specific location names along with the voice memo to ensure accurate spelling. This combination of casual voice input and precise text data provides the foundation for the automated process.

The Processing Phase

Once the initial input is received, the automation takes over:

1. The system automatically transcribes the voice memo
2. It applies the correct spelling from the email
3. AI processes the content to extract critical information
4. The information gets organized into different formats
5. Multiple outputs are generated simultaneously

The Output Phase

The final phase produces several valuable deliverables:

• A detailed journal entry capturing the day's experiences
• Structured travel notes for future reference
• Draft reviews for various travel platforms
• Location recommendations for future travelers

Applying These Principles to Marketing

The same principles that make Leffer's travel journal workflow effective can also be applied to marketing operations. Here's how you might structure similar workflows for different marketing tasks:

Content Creation Workflow

Start with a voice memo outlining your content idea and key points. The workflow could:

1. Transcribe your thoughts into text
2. Organize the information into a content outline
3. Generate a first draft of the content
4. Create variations for different platforms
5. Suggest SEO optimizations
6. Generate social media promotional posts

Data Analysis Workflow

Begin with raw marketing data and let the workflow:

1. Clean and organize the data
2. Perform initial analysis
3. Generate insights and recommendations
4. Create visualizations
5. Produce a formatted report
6. Draft an executive summary
7. Prepare presentation slides

Customer Engagement Workflow

Set up automated processes that:

1. Monitor customer interactions
2. Analyze sentiment and intent
3. Generate personalized responses
4. Create follow-up content
5. Schedule appropriate follow-ups
6. Track engagement metrics

#4: Implementation Strategies for Different Organization Sizes

The beauty of AI workflows is that they can scale to fit any organization's needs and resources.

For Solopreneurs and Small Teams

When resources are limited, focus on workflows that provide the most significant immediate impact:

• Content multiplication (turning one piece of content into many)
• Customer response automation
• Basic data analysis and reporting
• Social media management
• Email marketing automation

For Mid-Sized Organizations

With more resources available, consider implementing:

• More sophisticated content strategies
• Advanced customer segmentation
• Comprehensive marketing analytics
• Multichannel campaign automation
• Personalized customer journeys

For Enterprise Organizations

Large organizations can implement more complex systems:

• Cross-departmental AI integration
• Advanced predictive analytics
• Custom AI model development
• Sophisticated automation networks
• Global market analysis and adaptation

#5: Your Action Plan for Getting Started With AI

The pace of AI development shows no signs of slowing. 

“It's absolutely mind-blowing how fast it is evolving,” Leffer observes. “And the models are just gradually getting smarter over time.” 

This rapid evolution creates opportunities and challenges for marketers seeking to maintain their competitive edge.

One of the most important insights from Leffer's experience is that there's never a point where you've completely figured out AI. 

“There's not a point where you're going to truly have it figured out because it changes so quickly that there's always going to be something to continue learning,” she explains.

This reality requires a shift in how we approach AI skill development. Successful marketers need to develop a learning journey system that allows them to adapt and grow continuously instead of trying to master a fixed set of skills.

Regular Experimentation

Set aside time each week to test new features and capabilities as they emerge. Try different approaches to familiar tasks and document what works best. This systematic experimentation helps you stay current while building a personal knowledge base of effective strategies.

Community Engagement

Follow AI experts and engage with communities focusing on AI in marketing. However, Leffer cautions against accepting every piece of advice you hear: 

“Don't believe every single tip you get out there of like the little prompting hacks. Some of them are phenomenal, but a lot of these people do not actually understand why what they're working on works in the context it works in.”

Strategic Tool Evaluation

Regularly assess your AI toolkit to ensure you use the most effective tools for your needs. 

“So many people are going out and buying purpose-built tools as extra subscriptions of things that they could totally just easily do in their ChatGPT account or their Claude account,” Leffer notes.

With all this information in mind, how should marketers begin their journey toward AI mastery? Leffer recommends a structured approach that builds competence systematically:

Week 1-2: Foundation Building

Start with mastering basic communication with AI tools. Focus on:

• Practicing role definition in your prompts
• Experimenting with different ways of providing context
• Testing the impact of politeness and clear instructions
• Documenting what works best for your specific needs

Week 3-4: Capability Exploration

Systematically explore the full range of capabilities in your chosen AI tools:

• Test different input methods (text, voice, images, documents)
• Experiment with various output formats
• Practice combining different capabilities
• Begin identifying potential workflow opportunities

Week 5-6: Workflow Development

Start building simple automated workflows:

• Begin with a single, simple process
• Test and refine based on results
• Gradually add complexity
• Document your process for future reference

Week 7-8: Integration and Optimization

Focus on integrating AI tools into your daily work:

• Identify repetitive tasks that could be automated
• Create templates for common requests
• Develop standard operating procedures
• Train team members on basic AI usage

Measuring the Success and ROI of AI Implementation

As you implement these strategies, it's important to track their impact. Leffer recommends monitoring several key metrics:

Efficiency Metrics

• Time saved on routine tasks
• Volume of content produced
• Response time to customer inquiries
• Number of projects completed

Quality Metrics

• Content engagement rates
• Customer satisfaction scores
• Error rates in AI-generated content
• Team satisfaction with AI tools

Business Impact

• Cost savings from automation
• Revenue generated from AI-enhanced campaigns
• Lead quality improvement
• Customer retention rates

Looking to the Future: Emerging Trends to Watch For

As AI technology evolves, the gap between power users and casual users will likely widen. Those who invest in developing strong AI skills now will be better positioned to take advantage of future developments. 

“It's opening up things you wouldn't have otherwise been able to do or done,” Leffer emphasizes.

While the future of AI is impossible to predict with certainty, several trends are worth monitoring:

• Increasingly sophisticated visual processing capabilities
• Better integration between different AI tools
• More advanced automation possibilities
• Improved personalization capabilities
• Enhanced natural language processing

Final Thoughts

The journey to AI mastery is ongoing, but the rewards are worth the effort. As Leffer has discovered in her work with marketing teams worldwide, those who push through the initial challenges often achieve results they never thought possible.

Remember that success with AI is about more than finding the perfect prompt or using the most expensive tools. It's about developing a systematic approach to learning and implementation, staying curious about new possibilities, and maintaining a continuous improvement mindset.

Most importantly, don't let perfect be the enemy of good. Start with small steps, celebrate successes, learn from failures, and keep pushing forward. The future of marketing is increasingly intertwined with AI, and the time to begin your mastery journey is now.

With the right approach and persistent effort, you can transform AI from a mysterious black box into a powerful ally in your marketing efforts.

Other Notes From This Episode

• Connect with Michael Stelzner @Stelzner on Facebook and @Mike_Stelzner on X.
• Watch this interview and other exclusive content from Social Media Examiner on YouTube.

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✋🏽 If you enjoyed this episode of the AI Explored podcast, please head over to Apple Podcasts, leave a rating, write a review, and subscribe.

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