How Well Are Communicators Scaling Generative AI?
In the late '90s, when I was fairly new to the agency world, I started working for a mid-size PR firm that was ... let's just say it was wedded to the past.
They had one email account for the entire team of 20. Twice a day, the finance director printed the emails and a junior delivered them to people's offices. We were then expected to read them and handwrite our response.
That's an extreme example of PR tech aversion. But let's face it, if you look at social media or digital communications, the industry doesn't have the greatest reputation when it comes to technological change.
So when I saw The Communicator's Role in Driving Generative AI Adoption, a new report from the Institute for Public Relations , I was curious to see if the tradition had continued.
And whether PR professionals were shunning or embracing generative AI.
'Random Acts of AI'
The report featured an analysis of over 30 interviews with senior comms and tech leaders representing agencies, corporations and academic institutions.
Participants worked in a wide range of sectors including technology, healthcare, financial services, telecom, NGOs and government. As a result, responses were a good proxy for the PR industry as a whole.
The good news? The majority of organizations (87%) were offering employees AI training and 77% had already developed guidelines for AI use. And comms leaders were seen as 'strategic change catalysts' who worked alongside IT and other departments to help guide the enterprise implementation of AI.
The most common AI use cases were summarizing and analysing reports, creating and editing content and streamlining productivity through the use of custom GPTs or other prompted agents.
Yet only 37% of organizations had a formalized AI adoption road map, tracked KPIs to measure generative AI use or shared a cohesive change management story that outlined their AI vision and goals.
Other barriers to AI adoption included reputation risks and a lack of time to test the tools.
This left a gap between organizations that developed an enterprise approach to AI and the ones that are stuck in more tactical applications, or what one expert called 'random acts of AI'.
The report also revealed that successful enterprise adoption required C-suite leaders to walk the talk and demonstrate AI use as a strategic priority. And that effective communications played a key role in getting the team onside.
Three Levels of AI Maturity
One insight that stood out for me was how organizations are moving from basic use to AI sophistication by developing processes and protocols that enhance the ways employees interact with the tools.
The first level of maturity, and one many organizations are still in, focused on tactical adoption and using AI for simple drafting and summarization tasks that may or may not be consistent across an organization.
From there, businesses moved up to a more strategic implementation, where AI was used for some workflows.
The final level, transformational implementation, integrated AI systems 'organization wide' and regarded AI use a hybrid human-machine collaboration.
Regardless of the level, a 'human in the loop' approach was fundamental to maintaining oversight over AI outputs. And professional judgement, organizational voice and ethical standards were of prime importance, especially when it came to combatting misinformation or other inaccuracies.
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"The human side of AI transformation will be a critical factor as organizations adopt this technology on a larger scale," said Olivia K. Fajardo, M.A. , director of IPR research. "Communicators are uniquely positioned to lead this human-centered change."
The Road Ahead
Overall, communications leaders seemed optimistic about the future and saw a clear value for their role in responsible and ethical AI transformation.
They also viewed AI as a gateway to deeper insights and analytics that could help tie their teams' outputs to business goals. And they believed it could help them spend less time on repetitive tasks focus more on creativity, strategy and relationships.
Leaders envisioned the communicator's role as being AI implementers, explainers and bridge builders across an organization.
Yet there were few mentions of how generative AI might affect trust as it upended the relationships organizations maintained with their stakeholders and teams. Or how a hybrid human-AI workforce might alter enterprise culture.
Perhaps these areas could be examined in another study.
In the meantime, the full report will be presented at the upcoming IPR Bridge Conference, March 18 to 19 in Chapel Hill, North Carolina.
I'll also be there doing an interactive talk and demo on how to conceptualize and build AI agents with Samantha Stark.
Here's a link with more info on the IPR Bridge schedule and registration details if you'd like to attend.
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Well, it's time for you to dig into the report and for me to wind down issue #134.
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Between issues, I share shorter posts on LinkedIn with my take on digital marketing and generative AI. Another way to stay on top of the trends.
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I'll be back in about a month. See you then!
Note: All the content in this post was written by a human -- me -- and not Martin-bot. Disclosure: I'm a volunteer member of the IPR Digital Media Research Center.
Loved this, Martin Waxman, MCM, APR. The bit on “random acts of AI” vs real transformation really resonates. In my experience, the turning point is clear governance and communication: people need to know what AI is allowed to do, what stays human, and where to go when something looks off. I’d also add “easy to use” to the list – we can’t expect everyone to become LLM experts or prompt wizards, so adoption really jumps when the entry barriers are low and the tools fit naturally into existing workflows
The "random acts of AI" framing really captures what I see in a lot of organizations. The 87% training stat is encouraging on the surface, but training without a clear change management strategy and AI roadmap is like giving everyone a GPS without telling them where they're going. What I've noticed is that organizations stuck in that random-acts phase usually have one thing in common: they're optimizing for adoption metrics (seats activated, prompts used) rather than business outcome metrics (time saved, quality improvement, revenue impact). The three-level maturity model is useful here. The jump from Level 1 (experimentation) to Level 2 (integration) is where most organizations stall — not because technology fails, but because workflow redesign and stakeholder alignment work didn't happen first. For communicators specifically, the ones scaling fastest treat AI like an editorial assistant with institutional knowledge — investing in prompt systems, content libraries, and brand voice guides that carry context across sessions. That's what separates "using AI" from "scaling with AI."
Great, insights Martin Waxman, MCM, APR as usual, we must not be left behind in this AI wave. Especially as it matters to marketing team's and organizational objectives.
As someone who opened a business in the late 90s as a solid 20th-Century marketeer, then spent the first couple of decades of the 21st Century building comparable digital chops, I'm feeling like every time we catch and get good at riding a new wave of marketing opportunity, we have to face and paddle through the white water of a new and gnarlier break. Right now it's AI. I appreciate your informative blog and its additional references. Thanks, Martin.
Random acts of AI is a perfect way to put it. The roadmap gap is showing up everywhere. The teams that get leadership and IT in the same room early always seem to move faster once the real work starts.