Answers
Why trust must accompany emerging-technology adoption
Quick answer
Trust, transparency and governance help turn emerging-technology promise into durable capability. As AI increasingly connects with technologies such as blockchain, leaders need to understand what a system does, how decisions are governed and what assurance supports its use. Rohan Hall’s view is that trust, transparency, governance, assurance and standards are strategic requirements for lasting adoption, not extras to address later.
Convergence makes trust a shared concern
AI is increasingly an integrative force across emerging technologies rather than a technology evolving in isolation. Hall explores its convergence with blockchain, robotics, quantum technology, edge and IoT, connectivity, digital twins and neuromorphic computing. For leaders assessing these combinations, the question is not only whether each component works. It is also whether the combined approach can be understood, governed and trusted.
Transparency and assurance make adoption easier to assess
A promising demonstration is not the same as a durable enterprise capability. Transparency helps leaders examine how an approach works; governance clarifies how its use is directed; and assurance and standards provide a basis for evaluating trust. In blockchain adoption, assurance, governance, standards and best practices are part of that evaluation, not separate from it.
Build trust into the adoption plan
When moving from experimentation toward enterprise use, assess the technology alongside the architecture, operating model, education and workflows needed to support it. Identify where transparency is needed, who will govern use and which assurance or standards apply. This keeps the trust discussion connected to implementation decisions rather than leaving it until after a technology has been chosen.
Frequently asked questions
- Does this concern apply only to AI?
- No. The same trust questions matter when assessing blockchain and other emerging technologies, especially where they are used together.
- Where can I explore the blockchain side in more detail?
- Start with blockchain assurance, governance and standards for a closer look at trusted blockchain adoption.
- How does this relate to enterprise AI transformation?
- Enterprise AI adoption includes architecture, operating models, education and workflow transformation, alongside the move from experimentation to durable capability.
If you are evaluating an emerging technology, begin with the trust questions its proposed enterprise use raises, then examine the relevant architecture and governance work.