Why It Matters: Data and AI Literacy Is Now a Business-Critical Skill

One thing has become increasingly clear to me: the businesses that thrive in the AI era won't be the ones with the most data, they'll be the ones where every employee knows how to use it.

The World Economic Forum's 2025 Future of Jobs Report names analytical thinking as the top core skill companies need today, and a 2024 Gartner survey found poor data literacy to be one of the top five obstacles to analytics success.

I've seen firsthand that when employees don't feel confident interpreting reports or questioning dashboards, bottlenecks form, valuable insights get missed, and AI tools often go underutilized. On the other hand, when data literacy runs deep across every role, teams innovate faster, plan more effectively, and make better decisions with greater confidence.

Redefining Data and AI Literacy for a New Era

When I think about data literacy today, it's far more than the ability to read charts or analyze numbers. It has evolved into a broader understanding of data, analytics, AI systems, and behavioral concepts. AI literacy isn't a separate discipline; it's woven into data literacy itself. Organizations that embrace both will be better equipped for what's ahead.

Building a Strategy Around Four Pillars

One of the biggest mistakes I see organizations make is jumping straight into training without first establishing a clear strategy. Successful data and AI literacy programs don't happen by accident; they require thoughtful planning and long-term commitment.

In my view, that strategy should rest on four key pillars:

1. Developing people's skills over time

2. Governing data so it's trusted and accessible

3. Equipping teams with the right analytics tools

4. Designing education that reflects the needs of different roles

From there, organizations can build a practical roadmap: define the vision, communicate it clearly, provide the right resources, create opportunities for learning, measure progress, and celebrate success along the way.

Developing Data and AI Skills Through Learning

I've never believed that effective learning is one-size-fits-all. Every employee starts from a different place, which is why the strongest programs combine role-based learning, self-service resources, and opportunities for peer mentoring.

A good first step is understanding where people are today and creating learning paths that help them grow from there.

I've also seen the incredible impact that communities can have on learning. Communities such as Women Who Qlik reinforce this approach by creating spaces where members share real-world experiences, learn from one another, and build confidence together. Those peer connections often become just as valuable as formal training.

Visual analytics remains one of the most accessible entry points. When data is presented through charts and dashboards, employees begin to see the stories hidden within the numbers. As confidence grows, curiosity naturally follows, leading individuals from reporting and analysis toward predictive analytics and AI-powered decision-making.

Fostering Collaboration and Continuous Growth

Start building data and AI literacy as a core business capability today because in the AI era, the organizations that learn fastest will be the ones that lead.

If there's one lesson I've learned, it's that data and AI literacy grow fastest through culture, not just curriculum.

Show-and-tell sessions where employees share how data helped them solve a real problem create enthusiasm that spreads far faster than any top-down mandate. When leadership makes decisions visibly grounded in data, they reinforce the behaviors they want to see across the organization.

Just as importantly, organizations should measure what matters. Track participation, monitor adoption, and recognize progress. Celebrating wins both, big and small, helps sustain momentum and encourages others to continue building their skills. Data and AI literacy isn't a project with a finish line it's a compounding advantage that grows with every person who learns to trust the data in front of them.

Finally, the organizations that start building data and AI literacy as a core business capability today will be the ones best positioned to lead tomorrow.