Data used to live in the basement. It was for the techy and nerdy kids. It spoke in a strange language of zeros and ones. Now? Data is for everyone, and with the huge wave of AI, it’s become the sexiest thing in business, too. Beyond this cultural shift, it’s fast becoming a strategic necessity, one that determines whether organisations can truly compete, transform, and thrive. As data and AI capabilities mature, the focus must now shift from technology to people. This is something Chief Data Officers are grappling with, and if you find yourself at a loss for how to achieve this transformation, stick with us. This article explores the key themes shaping this shift and how organisations can climb the literacy ladder for long-term success, based on a recent LinkedIn Live Event featuring Pete Williams, Director of Data from Penguin Random House and Greg Freeman, CEO & Founder of Data Literacy Academy.
For too long, data literacy has been seen as an add-on, a nice-to-have, but not essential. Almost a check-box style approach, where people treat it as an activity, rather than a way of being. That’s starting to change. A new imperative has become clear, literacy must go beyond the data team. Data, to have the biggest impact, needs to reach into each function of the business and be at the very fingertips of those who need it. Business professionals, marketers, HR leaders, and operations managers alike must understand how to interpret, question, and act on data. Crucially, they should feel confident in doing so. They become part of a culture where data drives business value and decisions, not just visually appealing dashboards.
Despite growing awareness, resistance to data and AI still runs deep. The most common barrier? A persistent belief that “data isn’t my job”, which, in fairness, is true in many organisations. Data hasn’t traditionally been anyone else’s job description, apart from those in the data or IT functions. This means we’re talking about a huge corporate culture shift, not just a data culture shift. One of the key tenets of this shift is understanding that trust is the foundation of adoption. Employees won’t use what they don’t understand, and they won’t trust what they don’t feel safe to question. Creating psychologically safe environments where people can admit confusion, challenge assumptions, and ask “stupid” questions is critical. That requires a culture that celebrates learning, iteration, and even failure, not one that punishes imperfection.
This challenge is compounded by what Greg refers to as ‘taught fear’. “There’s this theory of education called pedagogy, and there is a pedagogical concept called taught fear… It’s the idea that as human beings, there are topics or subjects that we’ve taught ourselves we can’t learn” This concept directly relates to what we’re talking about, as many professionals feel deep discomfort when engaging with data, often rooted in past negative experiences with maths, tech, or statistics. Greg goes on to say that worryingly, this can result in investing in tech platforms to solve the problem and avoid the discomfort, “Technology as a silver bullet.” Yet it’s understood that without addressing human factors, understanding, confidence, and mindset, no platform will deliver its promised ROI. The challenge then becomes how you break down those taught fears and begin to work on the overall cultural transformation.
GenAI tools like ChatGPT and Copilot are helping democratise access to data insights. They’re intuitive, engaging, and instantly useful, making them a powerful Trojan horse for broader literacy adoption. Greg believes “Generative AI… biggest win for business professionals.” But here’s the catch, GenAI is not a substitute for foundational literacy. Without critical thinking skills, ethical awareness, and data governance, even the best AI tools can mislead or amplify poor practice. As Pete urges caution, “you have to be careful how you use them [LLMs] inside the organisation. And I think that creates a great sense of friction and frustration as well. You can’t just do anything you might do in the outside world with business data, which isn’t your own to share.” The future is not about blindly adopting AI, it’s about embedding it safely and intelligently into workflows.
Both comment on how it’s fairly easy to measure tool uptake. It’s harder, and far more important, to measure real business and individual impact. Pete tells us that “36% of the people have been through my training, have been promoted.” Which is a fantastic figure to tie to their data and AI literacy initiatives. It’s about seeing employees grow in confidence, productivity, and influence, which not only benefits them but also the business as well. Measuring promotions, time savings, and decision-making quality paints a much fuller picture of literacy ROI.
We’re on the cusp of a major interface shift. The traditional “slicer and filter” dashboard will soon give way to natural language interactions powered by LLMs. “Conversational analytics… going to be the way forward,” Pete tells us. And this future is closer than many think. When embedded in processes and systems, not siloed as training, literacy becomes second nature. That’s the ultimate goal, isn’t it? a world where every employee, from marketing exec to factory floor manager, can ask a question in plain English and get a useful, trusted, explainable insight in return from the business data.
Data and AI literacy isn’t about teaching everyone to code or build dashboards. It’s about giving people the confidence to challenge assumptions, ask better questions, and trust their tools. It’s about embedding intelligence into the very DNA of how we work, lead, and make decisions. Those who treat literacy as a strategic change programme will gain more than insights. They’ll gain agility, innovation, and a workforce fit for a data-powered future.
Watch the full On-Demand recording here
Author
She is also an award-winning content creator, podcast host, event moderator, and speaker, with multiple honors and recognitions, including the CN 30underThirty in 2022. She leverages her expertise and passion for data and infosec to produce and host industry-leading content, moderate large-scale events, and spearhead communities that foster knowledge sharing and collaboration among professionals and leaders.
In addition, Catherine is an instructor at the University of British Columbia's Sauder Business School, where she teaches the Marketing Intelligence and Performance Optimization module for their Data and Marketing Analytics Course. She enjoys sharing her insights and best practices with the next generation of data and marketing analysts.
Catherine holds a Bachelor of Economic and Social Studies from Cardiff University, with a focus on sociology. She is committed to promoting diversity, inclusion, and accessibility in the industry, and is a vocal ally and advocate. Outside of work, she loves gardening and spending time with her partner and two Pomeranians.
Data Literacy Academy empowers enterprise teams to become data and AI literate. Their tailored education is led by industry experts in a live setting and available via their OnDemand platform.
They take a change management approach to shape best-in-class data cultures. By bridging the gap between business and data teams, they help every department to unlock the value of their data.
