Wouter Neef
5 min read
The field of data and AI literacy is evolving rapidly. For experts, this presents a dual challenge: keeping data literacy programs up to date while simultaneously developing effective AI literacy initiatives. For more and more leaders it's getting clear: Generative AI investments will only pay off if employees adopt the technology and learn how to use it effectively. A one-off workshop or short video to get employees on board is clearly not enough.
And it's not only about skills, but like Wharton professor Stefano Puntoni is arguing: feelings of psychological threats are common and they are going to be a major obstacle. Organizations need to recognize and address these potential psychological threats and build human-centered workplaces that balance the benefits and risks of Generative AI.
That's where the work of Ayşegül Güzel can come in handy for Data & AI Literacy experts: with her comprehensive, guided template, every expert can create an impactful AI literacy program tailored for their organization.
A team that already took the lead here is the award-winning Lloyds Bank data & AI literacy team under the lead of Josh Cunningham. The team created a bespoke 80-hour upskilling program to improve AI capabilities across 200 senior leaders in the organization. Lloyds' group chief operating officer Ron van Kemenade (ex-ING) said: "AI is a game-changer for financial services, and we're investing to enhance our services with cutting-edge technology."
Meanwhile, organizations should not forget about data literacy. IDC research shows that out of more than 500 researched data & AI leaders, they answered the question "How has AI adoption and implementation changed, or will it change, the data and analytics landscape in your organization?" most often with the conclusion that AI underscores the importance of data literacy.
However, data literacy should evolve. Fredrik Hjelm (CEO of electric scooter company Voi) is arguing that if organizations want to make better decisions every day, they should move away from clunky legacy BI tools. Instead, they should provide metrics that decision-makers can trust and deliver visually appealing and easy-to-use dashboards that people can actually use for decision-making.
Finally, organizations must not overlook data governance. That's exactly why Salesforce spent $8 billion to take over Informatica. Whether it's about data-driven decision-making or enabling AI agents to operate safely, responsibly, and at scale, organizations need rigorous data governance.
However, as data strategist Dylan Anderson argues in his LinkedIn post, don't force it on the people. Make data (and AI) literacy fun, relevant, and ongoing. It is a journey, not a one-time thing. It's your job as a data and AI literacy leader to make your academy or program attractive enough that you can succeed. The organizations that will thrive are those that embed data and AI literacy deeply, not as a tick-box exercise, but as a cultural shift.
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