Getting lost in the AI hype is easy. I want to offer you something different: a practical way to become indispensable in 2025.
We're not just talking about keeping up; we're talking about developing skills that can help make you essential, regardless of how the technology evolves.
Many of these skills don't directly involve using AI tools. They're about cultivating a strategic mindset, a commitment to ethical and responsible practices, and elevating your analytical abilities.
In this post, I'm sharing the skills you can learn quickly or call upon right now. I share a cheat sheet you can download at the end of the post.
Set It in Motion
Mark March 14th on your calendar—not as your starting point, but as the day you'll notice new skills integrated into your weekly routines. Start right now.
Please note: While referencing common frontier models below, many standalone AI tools deliver similar outcomes. Use what's approved by your organization.
Let's go!
No. 1 Enhanced Idea Curation & Refinement
The Fear: "AI will replace my creativity."
The Reality: Your creativity isn't a finite resource. Think of the times your ideas were copied or imitated. Did you give up? No. You came up with something even better. AI is no different. Embrace it. Use it to enhance your creative potential, not diminish it.
The Skill: Treat AI as a brainstorming partner. Use it to refine your ideas, uncover hidden connections, and identify market opportunities you might have missed.
The Tools: Gemini, Claude, and ChatGPT are excellent for idea refinement. Their ability to handle multimodal inputs is really helpful.
Actions:
Explore Related Concepts: "What are some related themes I could explore based on this core idea?"
Gain New Perspectives: "How could I approach this concept from a completely different angle?"
Spar with the AI: "Is specialization or diversification the key to thriving in today’s market?"
Identify Market Trends: "What are the emerging trends in [your industry] that relate to this idea?"
Analyze Competitors: Upload competitor content and ask: "What are their strengths and weaknesses? Where is the opportunity for us to stand out?"
Develop Detailed Outlines: Break down your refined idea into a comprehensive outline with key points, supporting arguments, and compelling examples.
No. 2 Custom AI Model Building
The Fear: "Building custom AI models is too technical for me. I'm not a developer."
The Reality: Creating tailored versions of AI models like GPTs or Gems is accessible. Each platform offers user-friendly tools to customize these models to your specific needs, even without a coding background.
The Skill: Become a custom AI model builder. Learn how to leverage the customization capabilities of ChatGPT or Gemini to create AI tools that are aligned with your goals. Although the specific steps might vary slightly between platforms, the core principles remain the same. This skill allows you to create bespoke solutions, making you a highly valuable asset in any organization. Bonus: Paul Roetzer has built a fantastic custom GPT here: SmarterX's JobsGPT Tool. It's a gold standard example.
The Tools: ChatGPT and Gemini.
Actions:
Define Use Cases for Customization: Identify specific business scenarios or repetitive tasks where a custom AI model could improve efficiency or solve a pressing problem. Examples might include automating FAQs, generating tailored content, or streamlining workflows.
Focus on Clear Instructions: Refine your ability to provide detailed and specific instructions to guide the AI's behavior. This skill, similar to prompt engineering, ensures your model aligns with your goals and produces high-quality outputs. Get some help here.
Test, Iterate, and Refine: Experiment with different configurations and prompts. Continuously evaluate your custom AI model’s performance, gather feedback, and refine it to improve accuracy and relevance.
Explore Available Templates: Start with pre-built templates or starter kits provided by platforms like ChatGPT or Gemini. Customize these incrementally to learn the process and build confidence.
No. 3 Data-Driven Emotional Intelligence
The Fear: "AI will make my content generic and devoid of empathy."
The Reality: Every interaction involves real people with real emotions. Data-driven emotional intelligence is about understanding patterns in emotional responses and using those insights to make better decisions and build stronger relationships. This is about augmenting human empathy, not replacing it.
The Skill: Use AI to gauge the emotional impact of your content before you publish or present it. Analyze how different elements resonate with your audience. Experiment. This skill allows you to fine-tune your message for maximum impact, making you a more effective communicator.
The Tools: ChatGPT, Claude, Gemini, Microsoft Copilot
Actions:
Predict Emotional Reactions: Share your draft content and ask: "How might this content make someone feel?" or "What emotions does this evoke?" Follow up: "Give me specific examples of how to make this piece more impactful."
Break Down Sentiment by Section: Analyze your content piece by piece, asking the AI, "What emotional tone does this paragraph convey compared to the overall message?"
Map Emotions to Outcomes: Request, "Match each section of this content to a desired emotional outcome and suggest edits to strengthen the connection."
Experiment with Tone: Ask the AI to rewrite sections of your content in different tones (e.g., "Rewrite this paragraph to be more empathetic" or "Make this section sound more authoritative").
Create A/B Testing Variants: Use the AI to generate multiple versions of your content with slight emotional tweaks, then test their effectiveness with your target audience.
No. 4 Immersive Storytelling
The Fear: "AI-generated content will be bland and lack emotional depth."
The Reality: The quality of content depends on the creator, not just the tool. AI amplifies creativity—it doesn’t replace it. With talent, vision, and a willingness to take risks, you can use AI to create truly unique and emotionally resonant content.
The Skill: Immersive storytelling with AI is about putting people in the story—not just telling it. Use AI to create multi-sensory experiences with dynamic visuals, adaptive soundscapes, and interactive narratives that inspire action and connection. This is just the beginning—these tools are evolving fast. Start now to grow with them and shape the future of storytelling.
The Tools: Gemini- Gemini's multimodal capabilities allow for the generation of text and images, enabling the creation of interactive narratives. Claude- Claude is great at crafting engaging text-based narratives and assisting in developing compelling storylines.
Actions:
Generate Images from Text: Use Gemini to create visuals that match the tone and message of your content. 10 best text-to-image AI tools
Curate Soundscapes: While Gemini and Claude do not generate audio, you can use them to suggest existing music and sound effects that match your narrative's mood. For instance, ask, "What sounds would amplify the suspense here?" or "How can I make this moment more uplifting?"
Develop Interactive Narratives: Gemini can prototype and develop interactive narratives by generating branching paths and dynamic text-based content based on audience choices. While full interactivity and audio production require advanced tools, Gemini empowers creators to explore 'what if' scenarios and craft personalized experiences tailored to individual preferences.
Refine Writing Style: Use Claude to craft sensory-rich language for your scripts, copy, or narratives. Ask for refinements like, "Make this paragraph evoke nostalgia" or "Enhance the emotional impact of this section."
Test Emotional Resonance: Share your content with the AI and ask, "What emotions does this evoke? How can I amplify the impact?" Use its feedback to fine-tune for stronger connections.
Analyze Visual and Written Synergy: Use the AI to review how visuals and text work together. For instance, "Does this image enhance the message in this paragraph? If not, suggest changes."
No. 5 Benchmark ROI
The Fear: "I won't be able to prove the value of AI, and it'll be seen as a waste of resources."
The Reality: Every investment needs to be justified, especially in the B2B world. Without clear metrics, any initiative (AI or otherwise) can quickly become an expensive experiment.
The Skill: Tie AI initiatives to outcomes the organization cares about. Learn how to define, measure, and articulate the value of your AI projects. This skill allows you to demonstrate the tangible impact of your work, securing buy-in and resources for future projects.
Actions:
Define Clear Metrics: Before you start any AI project, identify the key performance indicators (KPIs) that will demonstrate success. These might include increased efficiency, reduced costs, improved customer satisfaction, or new revenue streams.
Establish a Baseline: Measure your current performance before implementing AI. This gives you a benchmark against which to compare.
Track and Analyze: Monitor your KPIs closely throughout the project lifecycle. Use data to understand what's working, what's not, and where adjustments are needed.
Articulate the Value: Be able to communicate the ROI of your AI initiatives to stakeholders. Focus on tangible business outcomes, not just technical achievements. Quantify the impact.
Implement the 30-60-90-Day Model: Conduct a pilot AI workflow for 30 days and check the metrics at 60 days. At 90 days, review and benchmark. Take what you learned and pivot or expand.ROI
No 6 AI Pilot Projects
The Fear: "I'll launch an AI project that fails, and it'll reflect poorly on me."
The Reality: Not every AI initiative will be a success. Approach projects strategically, learn from failures, and make data-driven decisions.
The Skill: Raise your hand to become a leader of AI pilot projects. Design, execute, and evaluate small-scale AI deployments to determine their feasibility for larger rollouts. If your org has an AI Council, find a way to become part of it. More on councils here.
Actions:
Start Small, Think Strategically: Choose a well-defined project for your pilot. First, decide your approach. Here are two ways to frame it:
Use Case Model: Enhance an Existing Workflow
Focus: Automate, optimize, or improve a specific task or process.
How: Identify a repetitive, time-consuming, or error-prone task within your current workflow.
Example: Automate customer feedback summarization, streamline sales lead data entry, or enhance a specific step in your content creation process.
Problem-Based Model: Address a Complex Business Challenge
Focus: Leverage AI to find solutions to a broader, more strategic business problem.
How: Identify a significant challenge that impacts key business objectives and requires deeper analysis, prediction, or a novel solution. Often, this includes multiple workflows.
Example: Predict and reduce customer churn, optimize pricing strategies, or personalize customer experiences at scale.
Set Clear Goals and Metrics: Define what success looks like upfront and how you'll measure it.
Implement the 30-60-90-Day Model: Conduct a pilot AI workflow for 30 days and check the metrics at 60 days. At 90 days, review and benchmark. Take what you learned and pivot or expand.
Gather Data and Feedback: Track performance and collect user feedback.
Be Decisive: Based on findings, continue, pivot, or abandon the project. Document results.
No. 7 Critical Thinking and the Courage to Question
The Fear: "If I challenge AI, I'll look like I don't know what I'm doing, or I'll slow things down."
The Reality: Blindly trusting AI output is a recipe for disaster. AI can be wrong, biased, or not aligned with your goals. The cost of uncritical acceptance can be costly. Your ability to think critically will be even more valuable.
The Skill: Become the ultimate AI fact-checker and challenger. Develop the confidence to question everything. This skill is not about being contrarian; it's about ensuring accuracy, validity, and ethical soundness. This makes you an essential safeguard against AI's potential pitfalls.
Actions:
Scrutinize the Data: Don't just accept AI's conclusions. Ask: Where did this data come from? Is it representative? Could it be biased?
Challenge the Logic: AI can sometimes produce outputs that seem logical on the surface but fall apart under scrutiny. Ask: Does this make sense in the real world? Are there any hidden assumptions or flaws in the reasoning?
Demand Transparency: If you don't understand how an AI arrived at a particular conclusion, ask for clarification. If the "black box" nature of the AI prevents this, consider whether it's the right tool for the job.
Cultivate Constructive Skepticism: Don't be afraid to voice your doubts, even if you're the only one in the room doing so. Encourage your team to do the same. Use phrases like "what if" or "how else" to examine the situation from all angles.
No 8 Ethical AI Framework Development
The Fear:
"We might unintentionally use AI in biased, unfair, or harmful ways."
The Reality:
The rush to adopt AI often comes without clear ethical guidance, leaving organizations to figure it out alone and increasing the risk of missteps. For individuals, this can mean uncertainty about how to act responsibly. For leaders, it can lead to oversight failures that damage trust and reputation.
The Skill:
Become a go-to ethical leader by anticipating and preventing ethical challenges rather than reacting to them. Whether leading a team or contributing individually, proactively identifying and addressing ethical risks shows your commitment to responsible AI use and builds trust within your organization.
Actions:
Go Beyond the Obvious:
Don’t rely on AI tools for ethical decision-making—they are advisory, not definitive. Seek out human expert insights and resources. Start with the IEEE Global Initiative, which offers respected resources for developing practical approaches to ethical AI.
For individuals: Take the initiative to educate yourself on ethical AI principles. This equips you to make informed decisions in your day-to-day work.
For leaders: Encourage your team to explore expert resources and integrate these insights into your organization’s ethical policies and practices.
Build a Human-Centered Framework:
Tailor practical guidelines to your team’s specific AI use cases. Start with established frameworks, such as the EU Guidelines for Trustworthy AI, but adapt them to meet your context and workflows. Involve multiple perspectives, including legal, social, and diverse voices, to ensure equity and inclusivity.
For individuals: Contribute to conversations about ethical practices by sharing observations and experiences that could improve your team’s guidelines.
For leaders: Actively seek input from team members, external experts, and marginalized voices to create frameworks that reflect real-world complexity.
Pressure-Test with Real-World Scenarios:
Challenge your framework with realistic scenarios to uncover weaknesses. For example, simulate how your AI system would handle biased training data or ambiguous outputs.
For individuals: Suggest or participate in scenario-testing exercises based on your work experience to help identify blind spots.
For leaders: Lead scenario-testing sessions that involve cross-functional teams, using realistic use cases to stress-test your ethical framework.
Make Ethics Part of Your Workflow:
Integrate ethical considerations into every stage of your AI projects. This includes regular updates to guidelines and mechanisms for reporting concerns or receiving feedback, such as anonymous reporting tools or ethics review boards.
For individuals: Familiarize yourself with your organization’s reporting mechanisms and use them responsibly to flag potential risks.
For leaders: Establish clear, safe channels for reporting concerns and regularly review feedback to improve your organization’s ethical practices.
No 9 Security Awareness & Threat Hunter Mindset
The Fear: "We might mishandle sensitive information, cause legal issues, risk our jobs, and damage clients' trust by using AI."
The Reality: AI introduces new security challenges. We need to be more vigilant than ever. Yet, the foundational security hygiene principles still apply. Don't try to tackle this alone. Remember, your org likely has a team focused on this – inquire. Leverage their expertise.
The Skill: Adopt a proactive, security-conscious approach. Think like a threat hunter – actively seek out and mitigate potential risks before they cause damage. This skill protects your organization and builds client trust, making you an invaluable asset.
Actions:
Embrace Skepticism: Approach AI tools with a healthy dose of skepticism. Don't blindly trust them. Question their data sources, algorithms, and potential vulnerabilities. Seek guidance from security professionals.
Practice Data Diligence: Be meticulous about the data you feed into AI models. Ensure it's accurate, unbiased, ethically obtained, and compliant with regulations. Consult with legal experts.
Develop and Refine Internal Frameworks: Create organization-wide guidelines for responsible and secure AI use. Collaborate with industry peers to share knowledge and best practices.
Commit to Continuous Learning: The AI security landscape is constantly evolving. Stay up-to-date on the latest threats and best practices. Engage with your network, attend industry events, and seek insights from security and legal professionals.
Dive Deeper: To better understand the threat hunter mindset, read my blog post, For Creators: How to Think Like a Threat Hunter When Using AI
No 10 AI Learning Path Design
The Fear: "There's too much to learn about AI; I'll never keep up."
The Reality: Nobody has fully mastered AI, not even the people who created it. Experts embrace continuous learning, apply their subject matter expertise in new ways, and aren't afraid to experiment. This is your chance to level up, regardless of your starting point.
The Skill: Become a strategic learner. Use AI to design personalized learning paths that focus on your specific needs and goals. Stop passively consuming information and start actively curating your AI knowledge. This skill ensures that your learning is efficient, targeted, and adaptable—key traits for staying ahead in a rapidly evolving field.
The Tool: NotebookLM is your AI-powered learning companion, working directly with your chosen data sources. Upload articles, research papers, transcripts, or videos to create a personalized, centralized learning library with features like audio overviews and detailed summaries. Pro tip: Focus on the areas of AI that genuinely interest you or solve your current challenges, not what you think you "should" be learning about.
Actions:
Gather & Organize Materials: Collect and upload AI-related resources in accessible formats (PDFs, Google Docs, shareable links). Organize into focused categories like "AI for Marketing" or "Ethical AI."
Create Your Learning Framework:
Generate custom learning plans aligned with your career goals
Identify industry-specific skill gaps
Build an AI glossary with practical applications
Set up collaborative learning spaces with colleagues
Maximize Learning Efficiency:
Request simplified explanations of complex concepts
Use audio features for learning during commutes
Get tailored analogies for technical topics
Break down complex subjects into manageable steps
Engage Actively:
Ask strategic questions about your materials
Request specific summaries and explanations
Create step-by-step learning plans
Track progress and adjust goals
Go For It!
You're a creator. You're already driven by talent, fueled by hope, and no stranger to taking risks. These are the very qualities that will make you thrive in 2025.
Consider the first quarter of 2025 as your launchpad. March 14th is your target date to have integrated at least one of these skills into your workflow on your path to becoming indispensable.
I'm serious about that target date. Reach out to me on March 14th – I want to hear about your progress using AI.
Need structured guidance and a personalized strategy? I can help. Through our AI consulting company, Expera Consulting, we provide tailored strategies to succeed.
Connect with me:
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Download the 2025 AI Skills Cheat Sheet
Curated Resources
Each resource aligns with a key skill area we've discussed. I've curated these specifically for their practical, actionable insights.
No. 1: Enhanced Idea Curation & Refinement
Harvard Business Review, Tojin T. Eapen, Daniel J. Finkenstadt, Josh Folk and Lokesh Venkataswamy
No. 2: Custom AI Model Building (GPTs, Gems)
No. 3: Data-Driven Emotional Intelligence
Michal Kolomaznik, Vladimir Petrik, Michal Slama, Vojtech Jurik
No. 4: Immersive Storytelling
No. 5: Benchmark ROI
PWC, Anand Rao
No. 6: AI Pilot Projects
@oneusefulthing, Ethan Mollick
No. 7: Critical Thinking and the Courage to Question
Ethical Systems Ron Carucci
No. 8: Ethical AI Framework Development
Eyes Off My Data, Sarah Villeneuve, Tina M. Park, Eliza McCullough
No. 9: Security Awareness & Threat Hunter Mindset
The Strategist Blog, Catherine Richards
No. 10: Personalized Learning Path Design
Amberle McKee
About Me
I'm Catherine Richards, author of "Making GenAI Work for Work" and editor of this blog. With a background in showcasing growth outcomes for technology portfolios at Adobe, Dell, and VMware, I now guide leaders and creators on AI strategy through Expera Consulting and Ragan Communications. I focus on translating AI into actionable insights that drive growth and help organizations responsibly achieve their goals.