By Michael Steavenson

The lowest point on the Dunning-Kruger scale is where a person has acquired only a small amount of knowledge on a subject and consequently feels the least confident in their understanding of it. It was at precisely this point that I stepped into Generative AI World last week, the inaugural conference from analyst firm GAI Insights. I was there to represent FleishmanHillard as a principal sponsor [disclaimer], but also to learn about how this fast developing technology is affecting virtually every client we have, as well as the effect GenAI is going to potentially have on the entire communications industry. And I was in rich company, as the conference brought together a unique collection of the most senior leaders from world-class institutions such as Harvard University, Mayo Clinic, PwC, Ensemble Health Partners, Microsoft, Coffee Labs, Tomorrow.io, Jerry, Mass General and more, to share real-life lessons on project and technology selection, ROI calculation, team organization structure, data and IP approach and lessons learned.

Here’s what I took away from two days immersed in all things GenAI.

Common GenAI Terms

There is a lot of new language (mostly acronyms) associated with GenAI. Here are the terms I heard used most often and what they mean:

AI (Artificial Intelligence): Computers that can think and learn like humans.

GenAI (Generative Artificial Intelligence): AI that produces media (e.g., text, video, images, audio)

GAN (Generative Adversarial Network): A type of computer program where two parts compete to create realistic-looking things, like images or text.

LLM (Large Language Model): A smart computer that understands and writes human-like text.

NLP (Natural Language Processing): Teaching computers to understand and talk like people.

WGAN (Wasserstein GAN): A special type of program for making realistic images.

VAE (Variational Autoencoder): A program that learns how things work and can make new things that look like the ones it learned from.

RL (Reinforcement Learning): Teaching computers to make good decisions by trying different things and getting rewards.

SD (Synthetic Data): Refers to artificially generated data that mimics real-world data but is created by computer programs or algorithms rather than being collected from actual observations or measurements.

MU (Machine Unlearning): Teaching a computer to forget something it learned before, often used to remove biases or outdated information from AI systems.

Predicting the Impact of GenAI

So, what does this mean for the industry and business leaders of today who are approaching GenAI with a mixture of excitement and fear? Here’s what stood out:

Cutting Through the Noise: Everyone feels like they now must have an AI story.

Hitting the New LLM Gold Rush: There is currently a rush for companies and organizations to build their own LLMs, most with little understanding of the risks associated or their own ability to scale.

Democratizing GenAI Integration with Synthetic Data: Synthetic data may help level the playing field for some by providing researchers and developers without access to large data sets with the ability to create diverse and privacy-preserving training datasets in LLMs. It can also improve the model’s performance and mitigate concerns related to privacy and data scarcity, as it avoids using real, potentially sensitive or limited data directly.

Selling GenAI into the C-Suite: There is a level of accessibility with GenAI that did not exist with Web 2.0 and the Cloud, so selling it into the C-Suite is already proving easier. “The FOMO is very real with GenAI,” said one Health Data & AI advisor.

Predicting Industry Regulation: There is unlikely to be sweeping regulatory legislation in the U.S. for the foreseeable future. The EU is passing laws this year that do not go into effect until at least 2025 and the U.S. is significantly behind in its own prioritization of AI regulation.

Recognizing Security and Compliance Risks: What is the potential for generating misleading or harmful information and the risk of infringing on copyright or privacy when generating content based on existing data? Several high-profile companies have seen recent cases of confidential and proprietary information being leaked due to employee GenAI misuse.

Impacting Global Labor Markets: GenAI may lead to increased productivity but also job displacement, shifting labor markets towards AI-related roles, potentially exacerbating economic inequality, and impacting global competitiveness.

Overall, one thing came through loud and clear – GenAI should NOT be considered by industry, organization and business leaders as a plug-n-play addition to their tool stack, it must be set at the strategic level. While it offers the promise of automation and efficiency, its strategic integration allows leaders to align it with broader business objectives, such as innovation, stakeholder engagement and long-term growth.

GenAI and the Communications Industry

There is no question that GenAI has the potential to significantly impact the communications industry. It can streamline and automate tasks like media monitoring, data analysis and content creation. This could enhance the efficiency of PR professionals, allowing us to focus on more strategic aspects of our work, like building relationships and crafting compelling narratives. GenAI can also help identify trends and sentiment in real-time, enabling quicker responses to crises and opportunities. However, there are concerns about AI-generated content’s authenticity and ethical implications. It may be challenging to maintain transparency and trust when using AI for PR, and there’s the risk of misinformation or biased messaging. Striking a balance between harnessing AI’s potential and upholding ethical standards will be a key challenge for the industry as it adapts to this evolving technology.

I leave you with perhaps the most compelling quote from the conference. It came from Harvard Business School professor, Shikhar Ghosh, shedding light on “The View from the C-Suite and the Boardroom” regarding AI’s impact on businesses. He said “AI should be likened to termites, not tornadoes. Its influence will not be a sudden disruptive force like a tornado but rather a gradual transformation affecting business models like termites weakening the structure of a house.” While this might sound a bit apocalyptic, it should be noted that termites, like all good technology disruptors, are actually agents of growth and renewal.

This communication is offered as general background and insight as of the date of publication, but is not intended to be and should not be taken as legal advice. Each organization should confer with its own legal counsel and its own business and strategic advisors for guidance that is specific to and considers the organization’s status, structure, needs and strategies.

To all the generative AI fearmongers: Don’t we all complain that there’s never enough time in the day to do the critical, long-term, deep-thinking work? 

It’s time to reframe the discussion around the impact of generative AI from jobs and roles to tasks and deliverables. Too many of today’s generative AI discussions focus on the number of jobs that will be eliminated rather than considering all the new opportunities that can be unlocked when we automate tasks, thus freeing up more time for higher-value work and the eventuality of new roles. 

And let’s be honest … we have been using automation, natural language processing and computer vision to complete tasks long before the surge in popularity of generative AI. That’s because when technology truly does its job, it becomes nearly invisible. While the concerns may be altruistic, they’re also misguided. It’s not the technology that matters as much as the benefits you derive. It’s the suggested cart item, the grammatical correction, and the hyper-relevant search result. It’s the surfaced insight, seamless customer experience and so on. When we embrace the potential value to be gained, our mindset can shift from worrying about AI replacing jobs to reimagining a future where AI can enhance and augment our own human excellence.

When humans focus solely on the task at hand, we prioritize near-term deadlines at the cost of longer-term, higher-level ideas and creativity. For example, in PR we may rush to finish a measurement report only to quickly move to the next one when that time could be better spent developing more actionable insights based on the data, which can then be used to develop more strategic and impactful plans.

And what happens after tasks? When generative AI takes on enough tasks, it can create a full-time role just to manage and optimize all those tasks. For example, a new type of AI graphics manager can focus on generating the best possible images to convey a story. Meanwhile, the roles of traditional graphics managers have moved on – they’re now spending their time digging into data and creative sources to come up with more effective visual concepts, out of which generative AI can rapidly create 100 or more variations for consideration. This will provide more choice and options at scale — and for a fraction of the cost — while also freeing up the designers to take on more fulfilling work.

This certainly isn’t the first time that communications roles have evolved in ways we previously couldn’t have imagined. Let’s look at two historical PR examples where technology impacted what we do daily and was perceived as a significant threat to jobs but ended up creating new and better opportunities for individuals in those roles.

First, those of us working in this industry in the ‘90s can recall when media lists began to move online (for those starting after 2000, lists were previously created manually from a printed directory of media contacts).

The task: Creating a media list.

New opportunity created: More time for counselors to develop better story pitches and cultivate deeper relationships with reporters, analysts, and later bloggers and influencers. 

Result: New roles emerged, like media and data analytics, which help our media relations pros determine which outlets and story angles will deliver the most impact.

Now, let’s consider the seismic shift that happened because of AI-powered video editing.

The task: Studio editing.

New opportunity created: Producing higher-quality video became accessible and attainable to all, enabling talent to develop more customized video solutions at a fraction of the cost.

Result: As video production became significantly more affordable and internet/mobile bandwidth expanded rapidly, video became much more common on social media, leading to even more demand for video content from brands and, therefore,more creative and production jobs in PR.  

What many fear about change is often only the mind’s reaction to something unfamiliar. Change often happens one step – or task – at a time. When real change comes to fruition, new roles and higher-value opportunities inevitably arise to meet the demands of the latest technology. It’s everywhere in industry’s history – from horses to cars, factories to robots and typewriters to computers. So far, history is repeating itself, and that’s creating even more opportunities, one Gen-AI powered task at a time.

This communication is offered as general background and insight as of the date of publication, but is not intended to be and should not be taken as legal advice. Each organization should confer with its own legal counsel and its own business and strategic advisors for guidance that is specific to and considers the organization’s status, structure, needs and strategies.

From unionization efforts by Amazon and Starbucks employees to months of recent coverage on Hollywood’s WGA/SAG strikes, the Teamsters contract negotiations and an unusually public start to UAW contract negotiations, a union-centric national narrative has taken hold. As hourly workers (both union and nonunion) absorb these media and social conversations, corporations should pay close attention to their employee engagement levels.

In the most pro-union environment in decades, support for the hourly workforce follows the national focus on well-being and equity. Add to that the shift in power from employer to employee as companies struggle to fill positions, and you have trending topics that are about much more than wages and benefits for a particular company’s rank and file. Today’s conversation is about fair play, respect and dignity for the workforce.

It’s a topic that impacts a much wider circle of companies beyond those involved with or directly impacted by union contract negotiations. It threatens to widen the gap between workers and management. Whether your hourly workforce is under 10 or over 10,000, those employees are part of the conversation: on TikTok, social media groups or Glassdoor reviews. Your workforce—and its collective satisfaction—is the core of your reputation, and taking a hands-off approach can put any organization in a perilous position. Management’s messages and actions during a potentially charged environment will speak volumes about its attitude toward and support of its workforce.

At FleishmanHillard, our counsel is to take nothing for granted. When employees are flooded with outside points of view, it’s critical for leaders to assess what the workforce is being impacted by—both internally and externally—and how they can authentically address concerns. The employee engagement principles below are a good place to start.

How to Keep Employees Engaged

Keep listening. There’s a real danger to assuming what the workforce thinks/feels/believes. Use a variety of approaches—1:1 meetings, group discussions, surveys, advisory groups, diagonally slice meetings— to get input from all levels and a realistic picture of the good, the bad and the ugly.

Assess what’s working. Revisit current communications channels, employee events, Employee Resource Groups or other workforce committees to identify if employees are effectively receiving information, building communities and providing feedback.

Make managers integral to success. Ensure they are well-equipped with information and training to communicate with their teams and shepherd feedback.

Maintain a people-first, empathetic approach. The steady coverage on strikes and workers’ rights can be both exhilarating and exhausting for a workforce. Remember the importance of humanity in communications and actions.

Maintaining a positive, respectful work environment requires commitment to listening and following through on what you hear. It’s about regularly, and authentically, demonstrating a thoughtful approach to a future of shared success.

The workforce has changed. There’s a new generation with its own perspective on work-life balance. There’s an increased demand for transparency and equity. There are more communication channels to share ideas and points of view. Leadership’s ability to embrace this evolution will play a big role in an organization’s success as an employer of choice.

Donna Fontana is the global Manufacturing practice lead for FleishmanHillard.

The ongoing MOVEit vulnerability has become one of the most significant cybersecurity issues in recent years. Several hundred companies have reportedly been affected to date, with the potential of thousands more globally and across nearly every sector.

Unfortunately, this situation is only the latest example of a growing cybersecurity trend: attacks on software vendors that can result in millions of individual victims. The SolarWinds attack in 2020 may be the highest-profile example of this type of event, but in recent months, other examples include a business communications software provider and a developer platform.

It’s imperative that leaders consider the reputational implications of an attack stemming not just from internal systems, but from anywhere within their software ecosystems — including vendors.

The FleishmanHillard Cybersecurity practice has supported multiple clients affected by MOVEit and numerous other breaches. In helping these clients effectively protect their reputations while dealing with these matters, we have identified notable trends that others should consider.

What to Consider When Communicating About a Cyberattack

Accept accountability while providing context.

In cases where MOVEit or another compromised software was used by a vendor rather than by the company, that company may have the option to allow the vendor to disclose the breach to the affected individuals directly. Before choosing a path, the company should weigh this choice against their stakeholder’s expectations.

Consider all audiences and be prepared.

Organizations may receive questions from stakeholders regarding risks associated with MOVEit. When deciding when and how to communicate — whatever your level of exposure — have a plan that balances transparency without causing undue alarm.

Take a long view.

Examine your current risk and ask yourself: Is the data I collect essential for conducting my business? Will my stakeholders be surprised by the data I collect? How many third parties receive that information? What are their data privacy standards and practices?

Prepare ahead of time.

Experiencing a data privacy issue is no longer a question of if, but when. These attacks are increasingly more sophisticated and common — a trend that will only continue. While a data security incident by itself does not necessarily represent a reputational crisis, failure to meet your stakeholders’ expectations regarding your level of preparedness and ability to respond in a manner that is transparent and timely could result in long-term reputational damage. To maintain that trust and protect business continuity, it is critical to have a communications plan that is up-to-date and takes these nuances and possibilities into account.

You can reach the FleishmanHillard U.S. Cybersecurity Practice Group at [email protected].