The rapid evolution of artificial intelligence is fundamentally altering the landscape of modern communications, nowhere more visibly than in the high-stakes, fast-paced environment of political campaigning. As organizations across the globe struggle to adapt to these technological shifts, the Public Relations Society of America (PRSA) has stepped in to provide a necessary forum for industry leaders. On the second Monday of every month, PRSA hosts AI Pulse, a specialized briefing series spearheaded by Ray Day, APR, the organization’s 2026 immediate past chair. These sessions are designed to dissect the latest trends, tools, and ethical developments in AI, offering practitioners a roadmap for staying relevant in an increasingly automated digital landscape.
The September 14 installment of the series offered a particularly compelling look at the intersection of political strategy and machine learning. Day, who serves as the vice chair of Stagwell and executive chair of Allison Worldwide, facilitated a discussion featuring two prominent communications veterans: Amy Brundage, managing director and economic policy practice co-lead at SKDK, and Matt Gorman, chief communications officer at the public affairs firm Targeted Victory. The panel aimed to bridge the gap between political campaign innovation and broader PR applications, highlighting how the "fail fast, succeed faster" mentality of political operatives is driving the adoption of AI across the broader professional communications sector.
The Current State of AI Adoption in Political Strategy
Data provided by the American Association of Political Consultants (AAPC) reveals a landscape in the midst of a technological gold rush. According to the association’s recent findings, 57% of political consultants now report using artificial intelligence in their daily operations, while 83% engage with AI tools at least weekly. This represents a significant shift from previous election cycles, where reliance on manual data processing and human-led research was the industry standard.
However, Matt Gorman, whose background includes senior roles for the National Republican Congressional Committee and national spokesperson duties for the Jeb Bush 2016 presidential campaign, cautions against equating frequency of use with true strategic sophistication. He characterizes the current industry trend as a "highly ordinary" application of the technology. According to Gorman, most campaigns are currently utilizing AI as an automated intern—assigning it tasks such as summarizing lengthy policy documents, organizing meeting notes, or scanning massive datasets to generate initial headline drafts.
This utility-focused approach mirrors the broader adoption of Generative AI in the corporate world, where efficiency is the primary metric of success. Yet, the high-pressure environment of a political campaign introduces unique risks. Just as a campaign director would never authorize a television advertisement based on an intern’s unvetted draft, Gorman emphasizes that AI-generated content must undergo rigorous human verification before reaching the public eye. The risk of hallucinations—where AI fabricates facts or citations—remains a critical hurdle that prevents the full automation of strategic communications.
Research and Data Aggregation: The Primary Use Cases
While creative content generation often captures the public imagination, the most profound impact of AI on political campaigning is occurring in the realm of research and data synthesis. Amy Brundage, who served as deputy assistant and deputy communications director at the White House during the Obama administration, notes that the most widespread implementation of AI within Democratic campaigns is centered on the rapid aggregation of large volumes of information.
"It is very clear that AI is used most broadly in the aggregation of data," Brundage stated during the AI Pulse session. This capability allows teams with limited staff to consume thousands of pages of legislative records, economic reports, or historical data in seconds, providing a significant advantage in managing fast-moving political issues.
Gorman refers to this process as "deputizing AI to find the needle in the haystack." He notes that while the technology is exceptionally adept at scanning vast digital archives, it lacks the critical judgment required to determine the significance of the findings. "A human must determine if the result is a needle, or merely an aluminum can," he explained. This distinction highlights the shift in the role of the political consultant: moving from a researcher who spends hours digging through archives, to an editor who directs the AI’s search and interprets the relevance of the output.
The Ethics of AI in Campaign Advertising
The integration of AI into political advertising has moved beyond backend research and into the foreground of campaign messaging. As the technology becomes more accessible, the potential for its use in "controlled circumstances" to create television and digital advertisements has sparked significant debate.
Gorman identified a particularly concerning trend: the use of AI to simulate the voices or likenesses of candidates to highlight vulnerabilities. In scenarios where a candidate has made controversial remarks without a recorded paper trail, opposing campaigns may use AI voice-cloning technology to recreate those quotes, presenting them as if the candidate had said them directly. This practice, often falling into the realm of "deepfakes," represents a significant escalation in campaign tactics that many industry observers argue requires stricter governance.
Brundage observed that the discussion surrounding AI has evolved from a conversation about utility to a fundamental campaign issue itself. "We talk about AI as a tactic or a campaign tool, but the use of AI and whether it’s right or wrong has turned into a campaign issue this time around," she noted. Voters are increasingly skeptical of digital content, and candidates are now being forced to clarify their policies on AI usage, leading to a new layer of transparency demands that consultants must navigate.
Implications for the Broader PR Industry
The lessons learned from the "campaign trail" are not limited to politics. The PR industry at large stands to benefit from the methodology pioneered by political consultants. The primary implication is that AI should be viewed as an augmentative tool rather than a replacement for human intellect.
The history of political communication suggests that the industry is cyclical, marked by rapid technological adoption followed by periods of intense regulation and self-correction. As AI continues to integrate into the public relations workflow, firms are likely to see a shift toward "human-in-the-loop" protocols. These protocols ensure that every piece of AI-assisted content—whether a press release, a social media post, or a research summary—is subjected to a human verification layer.
Furthermore, the rise of AI as a political issue suggests that public relations firms must develop robust crisis communications strategies for clients who may become the targets of AI-driven disinformation. As noted by the experts on the panel, the ease with which AI can create convincing yet false narratives means that reputation management will become more difficult, requiring firms to invest in sophisticated monitoring and authentication tools.
Looking Toward the Future of AI Pulse
As the digital landscape continues to shift, the PRSA’s AI Pulse initiative serves as a crucial clearinghouse for information. By providing a platform for experts like Ray Day, Amy Brundage, and Matt Gorman to share their real-world experiences, PRSA is helping to demystify the technology and provide a framework for ethical application.
The consistent message throughout the series is that the pace of AI development is unlikely to slow. For communications professionals, the challenge lies not in keeping up with every new tool that hits the market, but in developing the strategic agility to use those tools effectively and ethically. Whether through summarizing data, accelerating research, or navigating the complexities of digital advertising, the future of the profession will be defined by the ability to balance the raw speed of machine learning with the nuanced, value-driven judgment that only human professionals can provide.
As the industry moves toward 2026, the focus will likely shift from basic AI literacy to the development of industry-wide standards and best practices. In the meantime, the insights offered by the political sector provide a masterclass in how to embrace the advantages of AI while remaining vigilant against its risks. For those in the communications field, the message is clear: the technology is no longer a futuristic concept, but a daily reality that demands both curiosity and caution. Those who learn to harness it as an extension of their own expertise, rather than a substitute for it, will be the ones who lead the industry into the next era of public relations.
