AI Reflexes

As the bombs burst in air at the July 4th Macy's 250th Anniversary fireworks, I overheard some first-year financial analysts at large Wall Street financial institutions discussing the AI training they were required to participate in. As one AI native shared – I knew more about AI than them.

On the other end of the spectrum, I was on a board call with a very different older crowd discussing ways to chart a new direction for the organization without any reference to AI. This is what I have come to term as “dinosaur thinking.”

Occupying a space in between, a LinkedIn post from a friend focused on AI agents and how they would change organizations. This is anthropocene thinking (Age of Man), the right era, but still behind where we are in the AI Age.

Business and communications leaders have moved beyond the initial idea of experimenting with AI. Today we are using AI and implementing it into workflows. The results have been mixed, but are getting better with experience and better models.

There’s still a debate around the ROI of AI and there’s a mainstream view that we are in a bubble that is waiting to burst. And, yet, it is also clear that the technology is reshaping the world – for good and bad. It is creating opportunities for efficiencies and new solutions in the communications industry, and challenges including the decline in trust in digital content.

The technology which went mainstream four years ago is evolving at rocket pace. So fast that humans can barely keep up. The adoption cycle is so compressed that in every company or organization bleeding-edge AI evangelists, Jurassics, and Anthropocenics, are in the same room talking but not necessarily listening.

This is why we need to build AI reflexes across the organization to help close these gaps. Here are six. In this context, think of a reflex as a behavioral norm – it’s what we learn to do automatically.

Use the tools: We all need to become AI natives. If you are not using AI tools for research, idea generation, editing, tool building, and a plethora of other uses you are missing out on ways to be more efficient and productive.

Be skeptical: Know the technology foundation of how AI works to better understand its limitations. While this manifests in hallucinations, bad data, user-reverential information (it’s trying to please you), incorrect or poor-quality sources, skepticism is the basis for the work required for the next reflex…

Verify and verify again: The absence of the reflex to double-check or go to the source to verify data leads us to the statement “AI said...” The assumption that AI is right is deeply problematic and arguably something that crosses generations. The Robert Frost idea of taking the path less traveled is in this case – verification.

Do not overly rely on AI: This may be self-evident from the previous reflexes, but this needs to be a separate point. An over-reliance on AI can put your business at risk. AI-driven press releases or report creation, email automation, and customer service, may have the potential for efficiencies, but also disaster at scale.

Do not game the system: Silver bullet solutions are a behavioral trap. It’s tempting to use AI to go down the path of quantity versus quality, or look at models at a moment in time to restructure content in ways that you think will drive the search or LLM visibility. Technology infrastructure is moving so fast, that companies need to recognize that in some cases today’s solution may work against you tomorrow.

Focus on domain expertise: The “skills” era of AI is the next step after agents. Skills involve building models and tools around domain expertise! In the communications world, domain expertise is the ability to write, to develop stories that resonate, pitch to journalists, generate media coverage, and generate engagement on platforms where your clients and audiences are.

Companies and communicators need to evolve at speed. They need to head where the puck is going.

Those that are most likely to succeed will be able to build strong AI reflexes. This will take work and require a vision for AI – to motivate action.

One of the takeaways from the work we are doing at Tauth Labs to build trust into content in the AI Age – is the recognition that when it comes to communications, the expertise communicators bring to the table around building compelling narratives that resonate with real people remains key to engagement irrespective of platform. In this context, domain expertise is like gravity. It is foundational.

The combination of domain expertise, reliable data/information, and a skills-based AI-layer that connects the two is the future for AI in our industry. Building AI reflexes will be key to getting there.