Executives are increasingly treating AI literacy as a core workforce capability rather than a niche technical skill.
McKinsey & Company defines AI literacy as “building a shared baseline of fluency across the organisation, reducing fear, increasing transparency, and giving employees the confidence to experiment.”
As AI capabilities expand beyond software engineering into other organisational functions, Red Hat executives emphasised that AI literacy must become organisation-wide to ensure comprehensive adoption and impact.
Gains of an AI-literate organisation
Organisation-wide AI literacy can support faster AI adoption, better decision-making, safer deployment, and stronger collaboration. It can also enable employees to identify where AI can improve workflows, evaluate outputs critically, and use the technology responsibly within their own roles.
Studies and industry literature suggest that AI-literate teams are more likely to balance trust with critical thinking; they value AI while critically evaluating its accuracy, limitations, and risks. Moreover, literacy also advances compliance and collaboration within teams.
Vincent Caldeira, chief technology officer for APAC at Red Hat, framed AI literacy as practical understanding: “I measure literacy as the ability for people to conceptually understand where AI would fit into their own role and process.”
Brian Stevens, senior vice president and AI chief technology officer at Red Hat, echoed this broader organisational view.
“AI is going to be useful for everybody in every role that they have,” Stevens said.
Albert Chai, general manager for RoSEA at Red Hat, described AI as “a leveller of skill, knowledge, and expertise,” warning that the consequences of AI illiteracy could be disruptive for organisations.
“Whether it’s advancing one’s career or coming up with a better strategy, I’m using AI for my strategy and planning,” Chai said. “All these are the foundation for our success as professionals and for the company. The impact is personal, and it’s company-wide.”
Stevens agreed, saying AI’s impact on productivity could surpass previous technological shifts.
“I’ve never seen anything in my time in tech that was going to have as big an impact on the productivity and capability of an organisation as what this will be,” he said.
Raising AI literacy across the enterprise
Yet organisations continue to face challenges in scaling AI literacy, including limited training time, uneven adoption across departments, and governance concerns.
Rather than forcing employees to adopt AI through quotas or metrics, Stevens said Red Hat has taken an educational approach to improving AI literacy across departments.
“We’ve made it more educational than requirement-driven,” he said. “We’ve made it available to all departments and not just a select few because we think it applies to everybody.”
Framing AI literacy as a competitive necessity, Stevens highlighted that organisations must intentionally allocate time for learning to integrate AI at every level effectively.
“Literacy only comes from carving out time.” Brian Stevens
“Literacy only comes from carving out time,” Stevens said. “People think they don’t have enough time and keep putting learning off. But learning AI is less scary and far less technical than many people assume.”
Leading by example
Stevens argued that leaders themselves must become AI practitioners rather than delegating AI understanding entirely to their teams.
“I’ve seen two types of leaders,” he said. “Some clearly don’t really understand it and push their staff to figure it out, and others who have taken the time to become hands-on practitioners.”
He added that he is particularly impressed by leaders who manage large organisations while still taking the time to experiment with AI tools themselves.
Chai likewise emphasised the importance of “show, don’t tell” leadership in raising AI literacy.
“Leading by example inspired me to inspire my next line of leaders on the benefit and impact of AI,” Chai said.
For Caldeira, kindness and open-mindedness are essential leadership traits in encouraging AI adoption.
Leaders need to let people work things out and test by themselves. Vincent Caldeira
“Leaders need to let people work things out and test by themselves,” he said.
Building trust
Beyond adoption, executives said trust remains central to scaling AI responsibly across the enterprise.
Stevens said one reason AI adoption has accelerated within the company is because of efforts to harmonise data and improve trustworthiness.
“Often it’s not because the models themselves are bad,” he said. “It’s because the data the model needs is bad, or the query is bad.”
He clarified that the company is not yet implementing fully autonomous AI systems.
“Developers are using the tools to write code or test scripts, and it’s making them more productive,” Stevens said. “But they’re still the overseer.”
Caldeira pointed to the growing trend of evaluation-driven development as a way to better understand AI system behaviour.
“The only way we have to understand what they are doing is essentially to understand the trajectory of a system,” he said.
He also reframed the concept of “human-in-the-loop” as one centred on alignment rather than constant interruption.
“If I know that I run one million paths for this agent and 99.99% of the time I have an outcome aligned with human values, that makes me pretty comfortable that the system can be trusted,” Caldeira said.
Chai discussed the company’s approach to responsible AI through open-source governance frameworks.
“We believe in not just the transparency of the model, but the auditability of the AI model,” he said, adding that the company is building “policy as code” into its platform to enforce governance standards.
The goal, according to Chai, is to ensure AI systems remain aligned with organisational ethics, privacy, and compliance requirements.
Augmentation, not human replacement
It’s not that AI will replace us. It’s those of us who use AI who will displace peers and competitors who don’t. Albert Chai
Despite enthusiasm around AI, the executives repeatedly argued that AI should expand organisational capability rather than simply reduce headcount.
“It’s not that AI will replace us,” Chai said. “It’s those of us who use AI who will displace peers and competitors who don’t.”
Stevens also rejected the idea that AI’s primary value lies in reducing the workforce.
“I’m kind of a naysayer in the world where these AIs are going to be replacing people,” he said.
Instead, Stevens said that AI enables companies to innovate faster, enter new markets, build new products and services, and create broader organisational impact.
Caldeira, meanwhile, warned organisations not to lose human connection amid digital transformation.
“Why do I travel so much?” he said. “Because I like talking to customers and partners in person and seeing how they use the technology. I don’t get that in a 30-minute call once in a blue moon.”
While he described himself as someone who loves technology, Caldeira stressed that human relationships remain central.
“I’m still a big believer in talking to a human,” he said. “It’s not the most discussed part of AI: What does it mean for the human?”
Building an AI-literate mindset
For Red Hat executives, the future of AI adoption will depend less on whether organisations deploy AI and more on whether employees and leaders understand how to use it responsibly, critically, and at scale. In that sense, AI literacy is no longer simply a workforce initiative, but a business survival strategy.
