4 steps to building real AI skills without waiting on leadership

Leadership may expect AI adoption without a roadmap. Here’s a four-step framework for marketers 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.

Dig deeper: Why AI proficiency is today’s must-have marketing skill

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.

Dig deeper: How to get the AI training you need to succeed

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.

Dig deeper: How to level up your AI maturity from tools to transformation

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.

Dig deeper: How to speed up AI adoption and turn hype into results

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.

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Contributing authors are invited to create content for MarTech and are chosen for their expertise and contribution to the martech community. Our contributors work under the oversight of the editorial staff and contributions are checked for quality and relevance to our readers. MarTech is owned by Semrush. Contributor was not asked to make any direct or indirect mentions of Semrush. The opinions they express are their own.


About the author

Talisha Padgett
Contributor
Talisha began her career in traditional marketing roles but has spent the last half focusing on leveraging technology & processes to improve Marketing effectiveness and the Consumer experience. She has led Martech in both IT and Marketing and understands both sides. She joined Microsoft in 2022 to led B2B Martech Platforms and AI. Previously at Comcast, she revamped the MarTech & Campaign Optimization team by re-defining roles, changing the relationship with Engineering, establishing new processes with the Marketing teams, and pushing vendors to be more accountable. At Under Armour, she joined teammates from IT, Engineering, and Marketing into a dedicated MarTech function and consolidated duplicative systems for a more effective tech stack. Having also worked at Marriott International, MarketBridge, and ServiceMaster, Talisha understands the nuance of how technology can be applied to solve business problems at scale. When she is not working, she enjoys traveling, hiking, meditating, and spending time with her family and close friends.