Personalized Digital Content Creation

Most of us have at least heard about personalized medicine, but personalized content creation- in this industry???

Rest easy, we’re not talking about omnichannel marketing today.

Yet, there are still opportunities for us as biopharma communicators to personalize the types of content we do manage.

A 2021 McKinsey report found that “71% of consumers expect companies to deliver personalized interactions. And 76% get frustrated when this doesn’t happen.”

Although these stats don’t exactly apply to most of us on the corporate communications and PR side, there’s definitely something to it.

In 2022, UC San Diego researchers reported that the average American consumes about 34 GB of information every day.

With that much coming at any given audience and the demand for hyper-personalization, we have to make every effort to tailor our materials as much as possible.

So, what ARE easy ways that we can create personalized experiences through corp affairs-driven content?

Common AI tools like ChatGPT are actually powered by Natural Language Processing, or NLP.

This doesn’t mean that every output sounds completely natural – we all know that’s not the case… yet.

But we can still take advantage of the way these types of tools work to adapt the same content for investors, or patients, or the media, or any given group.

And we can even pressure test customized messaging for each audience BEFORE it’s deployed by prompting these tools to have the same context and priorities as those actual groups.

That may even mean creating your own knowledge base for training data, including examples of past materials and any metrics you’ve used to assess success.

Then, once you’ve decided whatever you’re working on is as good as it’s going to get and actually deploy it, you can go BACK in with these AI tools again to help analyze how it landed.

So we keep going through this feedback cycle.

What does your own feedback cycle look like for personalized digital content nowadays?

Driving the AI Change Management Conversation

The Marketing AI Institute’s annual “State of Marketing AI Report” came out last week.

Among the nearly 1,800 marketers surveyed, they found a year-over-year uptick in both enthusiasm for and adoption of AI.

The institute also highlighted, though, the pressing need for more formal training and guidance to support this profound shift in the way we work.

Zooming in on one aspect of this infrastructure, researchers found that, although more GenAI policies have been rolled out since last year, still, a total of only a little more than a third of companies overall have adopted a formal policy.

In an industry rife with SOPs and best practices, inserting ourselves into the conversation about yet another policy can feel exhausting and daunting.

However, an org’s core AI policy has the potential to function as an arbiter of a consequential workplace dynamic change.

And if we’re not careful, there could be implications for company culture, too, an especially dangerous possibility we need to keep in check in an industry that prizes innovation and forward-thinking.

In some ways, the introduction of AI is classic change management: share a vision, tell a story, make it inspiring, show not just tell the path forward and what the future could look like.

Striking that balance of ensuring there’s not an over-reliance on comms to drive the actual transformation for full AI adoption with our responsibility to help drive the conversation as comms counsel is delicate.

But as the connection nodes that all of us are, we’re up to the task, to advocate for governance frameworks that allow for individual experimentation and creativity.

Authenticity’s Premium in the Age of AI

The flood of AI-generated content isn’t coming, because it’s already here.

Microsoft and LinkedIn reported that three-quarters of global knowledge workers are using AI on the job.

While there are obviously many pros to using AI in our role as communicators, we really need to be careful when it comes to content generation.

In this year’s annual communications trend radar, researchers at the Academic Society for Management & Communication call this issue “information inflation.”

They say, “The value of information is diminishing due to the continuous surge in the volume and accessibility of data and content.”

Sure, there are a few tell-tale signs of AI-generated copy.

As one example, senior AI researcher and lecturer at Swinburne University of Technology Dr. Jeremy Nguyen found an exponential increase in the word “delve” in papers on PubMed in 2023 and 2024, coinciding with ChatGPT’s widespread adoption.

We’ve also noticed an uncommon volume of other words like “tapestry” and “weave,” as well as disproportionate usage of “not/but also” sentence constructs in AI-generated copy.

Despite signs like these, it’s getting harder to tell if content has in fact been AI-generated.

Researchers at Cornell recently showed that GenAI text detectors’ accuracy rate hovers around 40%, but that that already-low rate gets cut in half when machine-generated content is manipulated.

Though it’s possible to use AI tools to enhance our outputs, unique points-of-view and writing styles with character will be even more critical to demonstrate authenticity in our communications, to build credibility, and to reach the intended audience.

AI’s Impact on the Way we Work and How We Hire

Where biopharma comms veterans today can say they remember waiting by the fax machine on PDUFA dates, pretty soon, we’re going to be the ones saying,

Back in my day, we had to Google.

The 2024 edition of the Ragan Communications Leadership Council Benchmark Report says that “survey respondents highlighted gen AI as the top specialization that communicators will need to future-proof their roles.”

Some, like Cision’s Director of AI Strategy Antony Cousins, say that “80% of your job will change,” and “the tasks in the 20% which you wish you had more time will become more of a focus.”

But what does that look like exactly?

Comms thought leader and researcher Stephen Waddington says there are several categories in our profession where AI, right now, can help:

“Editorial assistance, content creation, professional support, education, creativity, and research, analysis and decision-making.”

Conor Grennan, Chief AI Architect at NYU Stern, posits that this fundamental shift in how we work will consequently impact who we hire and how we hire them, too.

Where we’ve historically hired for specific skills and experience, he suggests through his “AI-Ready Hiring Matrix” that, instead, focusing on critical thinking, adaptability, AI proficiency, communication, and creativity will become more important.

The jagged frontier is not only that – jagged – but it’s evolving by the second.

It’s all too easy to feel overwhelmed by the speed of change.

So, our call to action is to lean into the possibilities instead.

Overlooked Nonconfidential AI Applications

The reality is that there are already troves of publicly available information – and therefore, opportunity! – to leverage AI for a surprising number of comms scenarios, even in biopharma.

Before we go any further, let’s be clear about two things:

First, this is NOT a call to skirt your company’s or clients’ compliance or security guidelines.

And second, we are neither claiming to be AI experts nor legal experts.

With that out of the way… Training data for AI platforms is often kept secret, and copyright law is still TBD for a lot of this, but it’s safe to assume that anything in the public domain could be referenced or used to train AI systems.

So, why not take advantage?

We recommend taking inventory of public materials that you can use on your own to equip AI tools with context, tone, format, style, and voice.

Only a FEW examples include corporate website copy, past social media and blog posts, press releases, earnings call transcripts, and medical meeting presentations.

Much of our comms work is confidential, of course.

But using public materials for future plans or recycling previously released content with AI assistance are great use cases.

Let’s say you’re writing a series of follow-on social posts for leaders on your team to amplify key messages from a recent press release.

Or maybe you’re doing research for scenario planning and want to take into account outcomes with peers and competitors.

There’s so much more.

The point is, regardless of how AI-prepared your org is, you can still adopt these game-changing tools.

AI is NOT Coming for Your Job

At this point, we’ve all heard what’s become a trite sentiment, “AI won’t take your job but someone who knows how to use AI will.”

And maybe you’ve heard about Sam Altman’s prediction that AI will do “95% of what marketers use agencies, strategists, and creative professionals for today” within about five years.

Do we think this is all true?

Eh, sort of.

The best characterization we’ve seen is this one by Wharton Associate Professor Ethan Mollick:

“Experts in a field are going to be the best users of AI in that field.”

Yes, while you can use AI as your intern to draft a press release or administrative assistant to clean up documents, the explosive productivity and creativity gains in our profession are seen when this technology can be appropriately directed to target very specific and refined outcomes.

After all, someone has to be able to tell if an output is missing something, or if it’s garbage or on-point.

That’s only possible through good old-fashioned, on-the-job experience.

So, if anything, we have to be even MORE proficient in our craft as biopharma communicators, not less.

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