3 gaps your comms team should zero in on now.
Most comms teams are falling behind the AI curve because they’re missing a few foundational skills that AI depends on.
“You can’t use AI in communications until you can clearly explain how you do your job,” said Alex Sevigny, associate professor of communications at McMaster University, longtime communications consultant for the Canadian Public Relations Society and Center for AI Strategy advisor.
“We aren’t used to specifying our workflows in the same depths and detail as, say, an accountant or an engineer,” he said.
Sevigny, who will be presenting at AI Horizons Conference next month, said the good news is comms team can get up to speed fairly quickly.
Here are the three biggest gaps and practical ways to close them.
Build strong allies
Communicators often work in a bubble, he said.
“We don’t necessarily have friends or colleagues we talk to constantly in IT, data science or finance,” Sevigny said. That isolation makes AI harder to adopt.
Those teams already know how systems, data and automation work. Without relationships there, communicators struggle to ask the right questions or even get invited into AI conversations at all, he said.
So start with people instead of tools.
“The best place to start is organizational allies,” Sevigny said.
Then explain your work in detail, he said.
“Tell them, ‘This is what I do hour to hour. This is how I produce my work,’” Sevigny said. “Ask them how to make it more ‘AI friendly,’ what data could help, and what questions you should be asking.
This does two things, he said. It helps you learn the technical side faster and it educates others on the real value of communications.
Define your work
Most communicators know what they do but not necessarily every step they take to get there. That’s a problem for day-to-day AI integration, he said.
“If you can’t tell me blow-by-blow how you produce a writing product, you can’t really automate it in a safe or credible fashion,” he said.
Other professions are better at this because they’ve had to be. Accountants and engineers can explain their work in extensive detail. Communicators usually can’t, which makes AI adoption messy, risky or impossible, he said.
Start small and get specific, Sevigny said.
Take one common task, like writing a press release or preparing an investor deck, and write out every step:
- Where does the information come from?
- Who reviews it?
- What decisions get made along the way?
- What tools are used at each stage?
Once the workflow is clear, AI becomes easier to test, automate and improve, he said.
Understand how to use data
Many communicators come from journalism or humanities backgrounds, where numbers aren’t the focus. But AI runs entirely on data.
“If you’re going to use AI effectively in a way that’s verifiable and defensible, you have to understand what data it’s working on,” he said.
Most comms teams already generate huge amounts of data between emails, content systems, CRM records and stakeholder interactions, but they don’t fully understand what data they actually have, what they’re allowed to use, where it lives and who else uses it, he said.
That makes it hard to explain ROI, validate AI outputs or answer tough questions from leadership.
You don’t need to become a data scientist but you do need data literacy, Sevigny said.
Start by asking what systems do we use every day? What data do they collect? Who owns that data? What’s off-limits?
Sevigny emphasized learning with help, not alone.
“There are great courses on specifying workflows and data-driven decision making, including through platforms like Ragan Training,” he said, but real progress often comes from internal conversations.
Register here to learn more from Lamp and other industry experts during Ragan’s AI Horizons Conference Feb. 2-4 in Ft. Lauderdale, Fl.
Courtney Blackann is a communications reporter. Connect with her on LinkedIn or email her at courtneyb@ragan.com.
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