Embracing an AI native financial communications effort 

Key Takeaways:

• AI is transforming financial communications by automating research, media outreach strategies, and content planning to boost productivity. 
• Human oversight is vital to ensure authenticity, accuracy, and compliance in AI-assisted work.
• An AI-native strategy combines automation with human insight to enhance efficiency and professional growth. 

Let’s return to the topic of AI after last week’s blog on Muck Rack’s research on what AI reads and the implications for PR.

A few weeks into 2026 and the forecasts and capital market assumptions for all the big firms are in and most fall within a relatively predictable range. The truth is no one knows exactly what will happen. The one common theme, though, is the dominance of AI as a major technology likely to continue to drive markets and the economy.

We see this every day in the increasing role AI plays in our financial communications work. Even with compliance departments placing significant guardrails on the use of these tools, AI has impacted communications and promises to transform our work. Here’s how teams can begin to create an AI-native approach that harnesses tools to improve productivity and outcomes while avoiding the technology’s hazards.

Streamlining work

The improved productivity of having an AI assistant help with research, building media lists, summarizing reports or notes, and checking grammar frees us up to spend time on higher-order work. We prepare outlines for the financial content we draft for clients and ask our enterprise AI tools to help us spot any items we may have overlooked. We prepare pitches for media, identify a few targets and ask AI for the names of other reporters we may have missed who might be interested in the pitch. AI is like having a dedicated intern that can summarize, compile and track down details. Hallucinations still happen, but most tools share citations making it easy to check your work.

Far from making us dumber as many fear, AI tools allow us to ask questions and go deeper. We spend less time on the mundane and more time on delivering value.

But overreliance on AI creates problems for users and readers alike. We’ve seen early career communicators rely too heavily on AI, churning out inauthentic content and failing to develop the writing and thinking skills they need. We’ve all received emails from strangers that are creepily too familiar. And the long email story pitches AI can crank out feel too polished or TL;DR. People’s AI radar is up, and most prefer not to interact with machines.

In fact, overreliance on AI can be hazardous for those seeking to be found online. Google can identify AI content and deprioritize or penalize it as low quality, unoriginal or created specifically to manipulate search.

Remember, like human readers, Google appreciates content that reflects Experience, Expertise, Authority and Trustworthiness (EEAT). We’d add authentic. Your clients recognize their subject matter experts’ distinct voices. When that voice suddenly changes and you substitute overly polished and adjective-laden AI language, it is obvious to critical readers.

Creating an AI native communications approach

A popular term, at least among the companies producing AI tools, is “AI native.” What this means is an environment where AI is incorporated into daily work. While teams must lead with human judgment, creativity and relationships (and we believe direct relationships with media still matter – at least for now), they incorporate enterprise-level tools to handle repetitive tasks, sort through data-heavy research or reporting, and support decision-making.

An important caveat for financial services-focused firms like ours is to use enterprise tools to protect proprietary information and data, maintain confidentiality and avoid crossing compliance lines. These tools prevent the data you enter into the apps from being used to train tools or be released publicly.

What does that look like?

• Tools are used to gather and analyze data to support pitching or content creation.
• AI is integrated into daily workflows including checking drafts, summarizing notes, and structuring reports.
• Executive summaries of surveys or reports are drafted for your review.
• Past news releases can be fed into AI to help create first drafts of news releases.
• Agents run routine searches to stay in front of important filings or activities that could be newsworthy or pitchable.
• Outcomes are analyzed to track what works, test narratives and refine messages.
• Reporting expands beyond counting clips to analyzing sentiment or share of voice data.

AI can’t replace your thinking, but it can be your thought partner. As you manage projects, consider new products, or face challenges or crises, AI tools can help you analyze various scenarios.

• You can use AI tools to compare your products to a competitive set and identify the differences.
• You can put questions you think your likely clients might ask into an AI engine and check for inaccuracies to plan for any proactive or corrective communications.
• When facing a crisis, you can quickly perform scenario planning, create rapid briefings or test holding statements.

Controls and compliance

As you rely more on AI, it is important to establish clear policies for your team. Just as you would check any other research, AI output must be checked for accuracy. Be clear what information can and cannot be used and any required review and sign-off.

If creating content that might be used for client communications, it must meet all the SEC requirements of suitability, it can’t be misleading and it must provide for fair and appropriate disclosures. Performance comparisons, in particular, can be troublesome and trigger detailed disclosures.

Early career implications

Many of the skills that help early career PR pros develop, including media monitoring, list building and research, are now being automated by AI tools. Reporting and the deep research and audits that once took hours or even days to complete can now be accomplished much more quickly.

That is both good and bad. While some of the drudgery disappears, exposure over time to the stories and the reporters writing them helps to build awareness of what makes a good story pitch. Compiling reports helps provide exposure to industry dynamics. Data literacy skills are ever more valuable. Developing needed industry awareness and skills will require partnering with more experienced practitioners, getting mentored and applying feedback to develop the judgment to be effective.

Experienced and early career professionals alike are living through an exciting transformation. As you embrace this rapidly developing technology, let us know how it is going. We’re here to help you optimize the results.