Consider an AI tool that delivers consistently accurate results and demonstrates impressive capabilities. If the people who are expected to rely on it can’t understand how decisions are reached or challenge outcomes that appear wrong, why would they trust it with an important decision? Would an organization be willing to integrate it into a critical system? Would regulators be confident that its risks could be understood and managed?

Technical capability is important, but it’s not sufficient to ensure adoption or scale. The same is true in emerging technologies. Quantum technologies, for example, have the potential to transform computing, communications, and measurement. Yet their broader adoption will depend not only on what they can achieve, but on whether they can be deployed securely, reliably, and with confidence.

For technologies to move from breakthrough to widespread diffusion, people need trust in the systems they use. Businesses need to know that technologies will perform reliably and securely. Governments and regulators need credible ways to understand risks and assess outcomes. Innovation may begin with technical capability, but its ability to scale depends on something broader: Trust.

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