The Communications Staffing Crisis Nobody Is Naming

A Links Global thought leadership article by M. Sanchez, founder of Links Global, a communications firm working at the intersection of trust science, narrative design, and civic engagement. Part of the Links Global article series: AI and Technology. Drawn from field practice since 2002 and evidence-based research in strategic communication, public engagement, and institutional trust.

In Brief

Production tools have made it cheap to look professional. That has convinced many organizations they no longer need professional communicators. This article separates production work from judgment work, explains why the second cannot be automated or delegated to a generalist with good tools, and describes what sound communications staffing looks like now.

There is a conversation happening in organizations of every size, in every sector, that is reshaping the communications profession faster than most practitioners have recognized, and not in the ways that either the technology enthusiasts or the professional preservationists are describing.

The conversation goes roughly like this: AI tools can write copy. Design tools like Canva make professional-looking graphics accessible to anyone with a laptop. Three out of four PR professionals now use generative AI; more than 80 percent use the tools for brainstorming, and more than half use them to write press releases and craft pitches. Social media management platforms automate scheduling and analytics. Video production tools eliminate the need for specialized technical skills. And large language models can produce in seconds the first drafts that junior communications staff used to spend hours on.

The conclusion organizations are drawing from this conversation is equally consistent: we can do more communications work with fewer communications staff. We can hire less experienced people and give them AI tools to compensate for their inexperience. We can eliminate specialist roles and replace them with generalist staff armed with technology. And we can reduce investment in communications as a professional function because the technology has democratized the production capacity that used to require specialized expertise.

This conclusion is wrong. It is also understandable, because it reflects a genuine misunderstanding of what communications work actually is, a misunderstanding that the profession has not done nearly enough to correct, and that the proliferation of AI and design tools is now making devastatingly expensive in organizations that adopt it.

What Communications Tools Have Actually Changed

To make an honest argument about what the current technology environment means for communications staffing, it is necessary to be honest about what the tools have actually changed, and what they have not.

What has genuinely changed: The production threshold for minimally adequate communications materials has dropped dramatically. A competent generalist with access to Canva, a large language model, and a social media management platform can produce, in a fraction of the time it previously required, materials that look professional, read coherently, and are distributed efficiently. The raw production labor that once required specialized technical skills (graphic layout, copywriting, video editing, web publishing) has been substantially commoditized. This is real, and organizations that are still staffing as if the production labor is the scarce resource are misallocating.

What has not changed: The judgment work that makes communications effective. The ability to accurately read the trust condition of an audience before designing a message. The capacity to distinguish between a message that is technically accurate and one that will be received as authentic. The skill of designing a multi-audience narrative architecture that serves different constituencies without sacrificing coherence. The professional judgment to know when a communications approach will make a crisis worse rather than better. The experience to recognize when a client is asking for the wrong thing and the authority to say so. The strategic capacity to connect communications decisions to organizational outcomes rather than to activity metrics.

This distinction, between production work and judgment work, is the one that most organizations are currently failing to make. They see the production work being automated and conclude that the judgment work is also being automated. It is not. And the organizations that staff as if it has are discovering this in the most expensive possible way: in failed campaigns, in crises that escalated because the communications response lacked strategic judgment, in institutional damage that cheap, AI-assisted production cannot repair.

The Canva Illusion

Canva is an extraordinary product. It has genuinely democratized access to professional-looking visual design, allowing individuals and organizations with no graphic design training to produce materials that meet a basic standard of visual quality. For organizations that previously could not afford design support, it has expanded what is communicatively possible within their resource constraints.

It has also produced an illusion that is currently doing significant damage to communications practice: the illusion that the ability to produce professional-looking materials is equivalent to communications competence.

A professionally designed graphic is not a communication. It is a container. What the container holds (the message, its framing, its relationship to the audience’s actual prior expectations, its sequencing relative to other communications, its consistency with the institutional narrative it is supposed to reflect) determines whether the communication is effective. Canva can optimize the container. It has no capacity to optimize the content, and no ability to evaluate whether the content is appropriate for the audience, the moment, or the institutional context.

The practitioner who knows how to use Canva but lacks the judgment to evaluate what belongs in the template is not a communications professional. They are a production operator with access to professional-looking tools. The distinction matters because the damage from poor communications judgment is not mitigated by professional-looking execution. It is often amplified by it, because materials that look authoritative and polished carry the implicit claim that they represent considered professional judgment, even when they do not.

Organizations that have replaced professional communications judgment with Canva competency are discovering this in specific, predictable ways: in messages that are visually polished and strategically incoherent; in social media presences that are aesthetically consistent and communicatively empty; in crisis responses that look professionally executed and make the crisis worse; in campaigns that meet production specifications and produce no behavioral change.

What Large Language Models Are and Are Not

The same distinction applies, more consequentially, to large language model tools in communications work.

Large language models can produce first drafts at speed, generate variations on a message for testing, translate materials into different languages and reading levels, summarize large volumes of text, and assist with research aggregation. These are real productivity gains for communications practitioners, and the practitioners who use them well are genuinely more productive than those who do not.

What large language models cannot do is exercise the professional judgment that makes communications effective.

They cannot assess the trust condition of a specific audience in a specific institutional context. They have no knowledge of what the institution has promised and not delivered, what the community’s prior expectations are, or what messages will be received through a defensive prior versus an open one. They produce confident outputs regardless of whether the communications context warrants confidence. They have no ability to recognize when the client’s ask is the wrong ask, or when the communications approach that is being requested will produce outcomes different from the ones the client wants.

Most consequentially: large language models reflect the patterns in their training data. In communications contexts, this means they reproduce the dominant patterns of institutional communication: the patterns that characterize the mainstream of communications practice, including its documented failure modes. An AI tool trained primarily on institutional communications will produce institutional communications. It will produce them fluently, coherently, and at speed. It will not produce them with the judgment that distinguishes effective institutional communication from the averages of the field.

This creates a specific and underappreciated risk: the use of AI tools in communications work will, in the absence of professional judgment to evaluate and redirect their outputs, produce a convergence toward the mean of existing practice. Organizations that replace professional judgment with AI production will not fall to a lower standard of communications than the worst in the field. They will fall to the average standard of the field, which, as the best-known meta-analytic evidence on health communication campaigns suggests, is not adequate for the outcomes communications is supposed to produce. The best-known meta-analysis of mediated health campaigns found an average short-term behavioral effect of about r = .09, with correlations between roughly .04 and .15 depending on the behavior: real, small, and nowhere near what the field’s own claims imply.

The Staffing Model That Is Actually Failing

The staffing model currently being adopted in many organizations is some variation of the following: fewer senior communications professionals, more junior generalists with technology access, supplemented by AI tools for production work and freelance or contract support for specific campaigns.

This model has a seductive logic. It reduces the most expensive line items in the communications budget, senior professional salaries, while maintaining the appearance of communications capacity through the production volume that junior generalists with good tools can achieve.

It fails systematically for a reason that is straightforward once stated: the value of senior communications professionals is not primarily in their production capacity. It is in their judgment: the capacity to accurately read the institutional communications environment, design responses appropriate to it, recognize when the approved approach is wrong, and make the case for a different approach to leadership that may not want to hear it.

This judgment capacity is not reproducible by junior generalists with better tools. It is not reproducible by AI systems with more sophisticated training. It is built through years of professional experience across multiple institutional contexts, multiple communications challenges, and multiple occasions when the judgment call turned out to be wrong and the professional had to learn from it.

Organizations that have eliminated this capacity are not running lean communications operations. They are running communications operations without the function that makes communications effective, and their communications activity levels, which may be high, are producing a fraction of the institutional value they could.

What Proper Communications Staffing Looks Like Now

The proper response to the current technology environment is not to resist tool adoption or to staff as if the tools do not exist. It is to be clear about what the tools change and what they do not, and to staff accordingly.

The judgment function needs to be preserved and invested in. Senior communications professionals (people with the experience, credibility, and professional authority to make accurate trust-condition assessments, design appropriate strategic responses, and tell leadership when the approved approach is wrong) are more valuable in the current environment, not less. The complexity of the communications environments that most organizations are operating in has increased. The stakes of communications failures have increased. The argument that technology has reduced the need for senior professional judgment is backwards.

The production function can be rightsized. The genuine commoditization of production work means that organizations can maintain production capacity with fewer production specialists and more generalists with good tool access. This is a real efficiency gain. But it should be redirected toward better outcomes, not just lower costs: investing the savings in stronger strategic and judgment capacity rather than simply reducing the communications budget.

The AI integration function is new and genuinely necessary. The capacity to evaluate AI tool outputs with adequate professional judgment, to recognize the limitations of AI-generated communications content, and to redirect AI production toward communications goals rather than away from them is a genuine new professional competency that senior communications professionals need to develop. Organizations that have adopted AI tools without this integration capacity are getting the costs of AI adoption without the benefits: their AI tools are producing high volumes of content that their professional staff lacks the capacity to evaluate critically.

The Profession’s Responsibility

The communications profession has not made an adequate public case for the distinction between production competency and professional judgment. This is partly the profession’s fault: the field’s tendency to define itself by its outputs (the brochure, the campaign, the press release) rather than by its judgment function has made it easy for organizations to conclude that the outputs can be produced by cheaper means.

The current technology moment is forcing a reckoning with this. Organizations that have adopted the “anyone can do communications with the right tools” logic are discovering its limitations in ways that are creating real institutional damage. The profession’s responsibility is to name, clearly and with evidence, what professional communications judgment is, what it requires to develop, and what its absence costs, not as a professional self-protection argument, but as an honest contribution to organizational decision-making in a moment when the decisions being made are producing predictable and preventable failures.

The tools have changed what communications production requires. They have not changed what communications effectiveness requires. That distinction is the most important thing the profession can communicate right now, and the most important thing organizations need to hear.

Where This Fits

The judgment function described here is what the NSI white paper treats as infrastructure and what the Trust Audit Practitioner Course teaches. If your organization has the tools and not the judgment, the Links Global Trust Audit is a good place to see the difference.

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Sources

• Snyder, L. B., Hamilton, M. A., Mitchell, E. W., Kiwanuka-Tondo, J., Fleming-Milici, F., & Proctor, D. (2004). A meta-analysis of the effect of mediated health communication campaigns on behavior change in the United States. Journal of Health Communication, 9(S1), 71–96. doi.org/10.1080/10810730490271548

• Muck Rack. (2025, January 16). State of AI in PR 2025. muckrack.com

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Ownership and use

© 2026 Links Media, L.L.C. d/b/a Links Global. All rights reserved. The Links Global Trust Audit, Narrative Stewardship Infrastructure, NSI, Epistemic Re-Regulation Architecture, and ERA are proprietary frameworks of Links Global.

You are welcome to read this article, link to it, share it, and quote brief passages with attribution to Links Global and a link to this page. Reproducing it in whole or in substantial part, adapting or translating it, or using the production-versus-judgment staffing model in training, consulting, publications, or derivative works requires prior written permission from Links Global. Please cite as: Sanchez, M. (2026). The Communications Staffing Crisis Nobody Is Naming: What Canva, AI Tools, and the “Anyone Can Do This” Myth Are Doing to the Profession. Links Global. www.linksglobal.org.