By Nikita Sachdev
For most of my career, I’ve worked with technologies that moved faster than people’s ability to understand them.
Blockchain was perhaps the clearest example. The technology evolved quickly, with new products, protocols and financial models emerging almost overnight. But public understanding, regulation and institutional trust moved much more slowly.
We know what happened when that gap became too wide. Hype filled the space where understanding should have been. Bad actors benefited from confusion, legitimate companies were painted with the same brush, and an industry building transformative technology found itself fighting for credibility.
AI is approaching a similar moment, but the speed and stakes are considerably higher.
Dario Amodei, CEO of Anthropic, recently argued that frontier AI development should be deliberately paced. His reasoning is important: AI is increasingly being used to build the next generation of AI, creating a feedback loop in which technological progress accelerates itself.
His question is essentially: can our ability to understand, test and safeguard AI keep pace with its growing capabilities?
As someone who has spent years communicating emerging technologies, I think we should also ask:
Can our ability to explain AI, build trust in it and help society understand its implications keep pace with its development?
And perhaps more importantly: whose responsibility is that?
Responsibility cannot sit with the developers alone
The people building AI clearly have an enormous responsibility. They are closest to the technology and understand its capabilities and risks better than anyone.
But something this transformative cannot be the responsibility of one group alone.
Governments have a responsibility to understand what they are regulating. Researchers and independent evaluators have a responsibility to test the claims being made. Journalists have a responsibility to interrogate them. Investors have a responsibility to understand what they are funding. Business leaders have a responsibility to think carefully about how these systems are deployed.
And those of us responsible for communicating the technology have a responsibility too.
At Luna PR, we often sit between the people building emerging technologies and the people trying to understand them.
That position carries more influence than our industry sometimes acknowledges.
We help decide which stories are told, how complicated technologies are described, which executives become authoritative voices and which narratives eventually reach journalists, investors, policymakers and the public.
Our job cannot simply be to make innovation sound exciting. We have a responsibility to make it understandable.
We have seen what happens when hype moves faster than understanding
Blockchain taught our industry an important lesson.
For years, communications often rewarded the loudest story.
Launch the token. Announce the partnership. Talk about disruption. Get the headline. Build the community.
PR became very good at amplifying innovation, but the industry wasn’t always as good at explaining it.
When the market eventually corrected and companies failed, the public often struggled to distinguish between a bad company, a bad product and a bad technology.
That distinction matters.
Communications didn’t cause crypto’s trust problem, but I do think our industry has to acknowledge that we sometimes contributed to the environment around it.
We amplified claims that deserved more scrutiny. We celebrated numbers without always providing context. And sometimes the pressure to create a bigger story overtook the responsibility to tell the clearest one.
AI gives us an opportunity to do things differently.
Our job is not just to tell the story
If an AI system behaves unexpectedly, the role of communications cannot simply be to minimise the story.
If a model achieves something extraordinary, our job should not be to exaggerate what that means either.
Our responsibility is to help explain what happened, why it matters, what we know, what we don’t know and what happens next.
That requires communications teams to get much closer to the technology.
We need to understand the product before we explain it. We need relationships with technical teams, not only marketing teams. We need to understand the risks alongside the benefits. And we need to know enough to challenge the companies we represent when necessary.
Sometimes our job will be to make something complicated understandable.
Sometimes it will be to tell a company that it needs to explain more.
And sometimes good communications may mean saying:
You shouldn’t make that claim yet.
That isn’t being less effective at PR.
I think it is becoming part of doing PR responsibly.
Because communications shapes perception before most people experience the technology
This is particularly important with AI because most people will form opinions about new developments before they ever experience them themselves.
They will encounter them through a headline, an interview, a social post, a founder’s comment or a story that spreads online.
That means the language used to describe AI matters enormously.
Calling something “autonomous” when significant human intervention is involved matters.
Calling something “intelligent” versus “automated” matters.
Describing an experiment as a breakthrough matters.
And presenting a theoretical risk as either an inevitability or an impossibility matters.
Words influence expectations. Expectations influence trust. And trust eventually influences adoption, investment and regulation.
For communications agencies operating at the frontier of technology, that gives us a very real responsibility.
Building understanding at the speed of innovation
I remain optimistic about AI.
But optimism shouldn’t require us to pretend that every consequence of a technology this powerful will be predictable.
For years, I have believed that great ideas don’t change the world if nobody understands them, trusts them or knows they exist.
AI adds a new dimension to that belief.
When technology advances faster than people can understand it, visibility alone isn’t enough.
The people building AI have a responsibility to develop it carefully. Governments have a responsibility to govern it thoughtfully. Journalists have a responsibility to scrutinise it. And those of us communicating it have a responsibility to make sure that in the race to tell the story, we don’t lose the truth, context or understanding behind it.
Because our job is no longer simply to help technology be heard.
It is to help the world understand what it is hearing.
