Dapo Richards: Why AI Is Making Judgment More Valuable Than Information

As artificial intelligence makes information faster and easier to access, Nigerian-born product leader Dapo Richards believes the biggest advantage for professionals is no longer knowing the most, but knowing what to do with what they know.

Richards, the Immediate Past President of Junior Chamber International (JCI) Aberdeen and a product leader with experience in payments and fintech, shared the perspective while speaking at the Galvanized Leaders Conference ’26.

His message was straightforward: AI may be able to produce answers in seconds, but it cannot take responsibility for deciding whether those answers are right, relevant or worth acting on.

AI Is Changing What Gives Professionals an Edge

For years, having access to information ahead of everyone else was a major advantage in business and leadership.

Richards said that is rapidly changing.

He recalled a time when leaders gained an edge by reading reports, studying data and understanding market developments before their competitors. Today, AI tools can process huge amounts of information almost instantly, making that advantage much less exclusive.

“Information is no longer scarce; judgment is,” Richards said.

He argued that the real challenge is no longer simply finding an answer. Professionals must be able to question the answer, identify gaps, verify its accuracy and decide what should happen next.

That shift could have major implications for how companies train employees and measure productivity as AI becomes increasingly embedded in everyday work.

The Real Value of AI May Be the Time It Gives Back

Richards used an example from his early career in payments to explain how automation has changed his approach to work.

At the time, he spent the first hour of his working day preparing a transaction report. The process involved manually collecting, checking and formatting data before the report could be used.

Much of that work can now be automated.

Rather than seeing automation simply as a way to complete the same task more quickly, Richards said the bigger opportunity is using the time saved to focus on work that requires human thinking.

That includes analysing information, communicating with colleagues, solving problems and making decisions.

For him, being busy is not necessarily the same as creating value.

The arrival of AI, he suggested, gives professionals an opportunity to rethink how they spend their working hours instead of simply filling the extra time with more tasks.

Three Skills Richards Says Professionals Need in the AI Era

Richards highlighted three areas that could become increasingly important as AI takes on more routine work: clarity, evaluation and knowing when not to use AI.

Clarity Starts With Asking the Right Question

The quality of an AI response often depends on how clearly the user defines the problem.

Richards believes professionals need to understand exactly what they are trying to achieve before turning to an AI system.

A poorly defined objective can produce an unhelpful answer even when the technology itself is capable of handling the task.

That makes clear thinking an important part of effective AI use.

Evaluation Matters More Than Impressive Answers

Richards placed particular emphasis on the ability to evaluate AI-generated information.

He encouraged professionals to use AI extensively in areas they already understand. Existing knowledge gives users a better chance of recognising when an AI response is accurate, incomplete or simply wrong.

The danger, he warned, comes when people rely on AI for subjects they do not understand well enough to verify.

“The failure mode is rarely a wrong answer that looks wrong,” he said. “It’s a wrong answer that looks entirely reasonable, arrives quickly, and gets forwarded.”

That risk becomes even greater inside organisations, where an unchecked AI-generated response can move rapidly between employees and potentially influence important decisions.

Knowing When AI Should Stay Out of the Decision

Richards also argued that becoming good at AI does not mean using it for everything.

Certain decisions require greater caution, particularly where sensitive customer information, regulatory requirements or serious consequences are involved.

In payments and fintech, for example, a seemingly small error can have significant financial, regulatory or reputational consequences.

For Richards, responsible AI adoption means understanding where the technology is useful and where human judgment must remain firmly in control.

“Mastery isn’t using AI everywhere; it’s using it well, in the right places,” he said.

AI Can Prepare the Work, But Humans Must Own the Decision

Richards pointed to his experience dealing with a regulatory change that required a technical specification to be communicated to three different audiences.

AI was useful in helping him produce an initial draft quickly. But the important decisions still had to be made by him.

He had to determine what information mattered, what needed to be left out and how strongly timelines should be communicated.

“AI didn’t make the decision,” Richards said. “It cleared the runway so I could spend my energy on the decision.”

That distinction sits at the heart of his argument.

AI can assist with research, preparation and execution, but responsibility cannot simply be handed over to a machine when something goes wrong.

Why Companies Need More Than AI Tools

Richards also addressed one of the biggest challenges facing organisations adopting artificial intelligence: people.

Introducing a new technology does not automatically mean employees will understand it, trust it or use it effectively.

He argued that resistance to AI can often be linked to poor communication, insufficient training and a failure to involve employees in the transition.

Companies, he said, should treat AI adoption as a change-management process rather than simply installing new tools and expecting employees to adapt.

Clear communication, proper training and regular feedback can determine whether AI becomes a useful part of an organisation’s workflow or another technology that struggles to gain acceptance.

Human Accountability Must Remain at the Centre

Richards was also clear about the ethical responsibilities that come with AI, particularly in industries handling financial and personal information.

He stressed that accountability must remain with people.

If AI contributes to a decision, the person or organisation making that decision must still take responsibility for the outcome.

Data protection is another major concern.

Richards warned against feeding customer information into AI systems simply because doing so is convenient. His experience with information-security governance and standards such as ISO 27001, he said, reinforces the need for companies to match technological innovation with strong safeguards.

The faster AI develops, the more important those safeguards could become.

Richards’ Advice to Young Professionals

When asked which AI skill young professionals should prioritise, Richards chose evaluation over prompting.

Rather than trying to master every new AI tool or chasing the latest prompting technique, he recommended starting with a practical problem.

His advice is to identify one repetitive task that takes up time, use AI to assist with it consistently for about two weeks and gradually develop the process into a routine.

The next step is to provide the system with genuine context and learn how to judge the quality of its output.

But experimentation should always be paired with verification.

Richards also encouraged young professionals to find mentors who are more experienced in their field and further ahead in their use of emerging technologies.

The Leaders Who Keep Learning Will Have the Advantage

Richards ultimately framed the AI revolution as a leadership challenge rather than simply a technology story.

The professionals who thrive may not necessarily be those who know the most AI tools today. Instead, they could be those who remain curious, adaptable and willing to keep learning as the technology changes.

“The leaders who do well from here won’t be the ones who know the most today,” Richards said. “They’ll be the ones still learning tomorrow.”

His argument comes at a time when AI is making information increasingly abundant and accessible.

As machines become better at producing answers, the human advantage may increasingly lie in asking better questions, checking what comes back, understanding the consequences and deciding when action is appropriate.