4 steps to building real AI skills
Leadership may expect AI adoption without a roadmap. Here’s a four-step framework to build practical AI skills and scale impact.
Many marketing leaders expect their teams to embrace AI but offer little direction on where to begin, which areas to prioritize or what outcomes to pursue. While AI is clearly transforming the workplace, applying it meaningfully in a work context is far more nuanced than using ChatGPT to find the perfect recipe.
If your organization is discussing AI without providing a clear plan, change management resources or specific learning tools, this approach will help you take ownership of your upskilling journey.
Step 1: Learn how AI is being used in your discipline
AI is not a one-size-fits-all solution. Its applications vary widely across marketing, sales, product development and operations. By exploring how AI is adopted in your field, you can separate hype from genuine value and prioritize skills that align with your role and business goals.
Follow updates from major players like Microsoft, Google, Adobe, Salesforce and ServiceNow. Pay attention to emerging AI-native companies that push boundaries in personalization and automation.
Engaging with thought leadership from sources such as MarTech.org, Gartner and Forrester will keep you informed about trends and best practices. Subscribe and skim weekly. As you research, bookmark use cases that resonate with your work. They’ll serve as a roadmap for experimentation.
Step 2: Create time in your schedule to use and practice with AI
Upskilling is an active process that requires hands-on experience rather than passive reading. Blocking regular calendar time — such as 30 minutes twice a week — signals commitment to yourself and your team.
To get started, explore courses on LinkedIn Learning, Coursera and Udemy, and consider joining AI-focused communities on LinkedIn or Slack for real-world tips. Focus on proven use cases that deliver immediate value, such as drafting copy, summarizing reports or generating audience insights.
Experiment with tools like ChatGPT, Runway, Midjourney, Synthesia and GrammarlyGO to broaden your hands-on experience. Compare outputs and document what works best. Over time, this practice will help you build a playbook tailored to your team’s needs.
Step 3: Identify one to two small process improvements and implement AI there
Big transformations start small. To build momentum, identify one or two process improvements where AI can deliver quick wins. Instead of overhauling entire workflows, audit your tasks for repetitive, time-consuming steps and match them to relevant AI capabilities.
For example, you might automate A/B test analysis or deploy chatbots for initial customer queries. Measure impact by tracking time saved, accuracy improved, engagement lifted and more, then share the results internally. Simple “before versus after” snapshots can help spark broader adoption across the organization.
Step 4: Scale and reimagine entire processes
Once you’ve established a few small wins, continue protecting calendar time to explore larger opportunities. Ask how processes could be reimagined if AI were at the center. This might include:
Shifting campaign planning to AI-driven predictive modeling.
Moving content production into dynamic, AI-assisted workflows.
Using AI to personalize customer journeys.
Remember, scaling AI is as much about change management as it is about technology. Bring stakeholders along, document workflows and set clear KPIs.
AI upskilling is a responsibility
Success in AI upskilling requires a mindset shift. Embrace curiosity over fear. AI won’t replace you if you learn to use it — it will replace tasks, not talent. Value iteration over perfection, recognizing that early attempts may be clunky but progress is what matters. Foster collaboration by sharing learnings with peers, since adoption accelerates when teams learn together.
Ultimately, AI is not a passing trend but a tectonic shift. Waiting for a perfect roadmap from leadership is a gamble, so take ownership of your learning journey instead. Start small, stay curious and scale thoughtfully. The marketers who thrive in the age of AI will be those who embrace change with intention.
Also published here: 4 steps to building real AI skills without waiting on leadership
