Blog Post

3 Considerations for Navigating the Rapidly Evolving AI Landscape

Publish date: Jul 28, 2023 | Reading time: minutes

It’s hard to look at the news these days without seeing headlines about AI. From President Biden’s recent meeting with tech companies to set up voluntary guardrails, to opinion pieces about what it’s like to have an AI as a boyfriend — every day there’s a new development, a new debate or a new angle to consider about this rapidly evolving technology.

Few technologies have made a bigger entrance onto the cultural mainstage. ChatGPT set new records when it reached 100 million users in just two months after launch. Since then, the internet has been fixated on dreamlike AI-generated videos, creepy reporter interviews with Bing’s AI chat and AI-generated photos of the Pope in a puffer jacket. Businesses can’t stop talking about AI either — with a record number of executives at S&P 500 companies discussing it on their earnings calls.

Clearly, it’s made a big impact on the cultural zeitgeist, but what does it mean for your business? Few companies were prepared for this rapid change, and fewer still know where we go from here. But one thing is certain: ignoring AI is not a good strategy for survival. The potential risks and rewards of this new technology are equally enormous, and companies will need to learn to navigate both to keep up. Here, we’ll look at a few key things to consider as we all adapt to a new AI-dominated marketplace.


Consideration 1: Learning To Speak AI

Large Language Models, Generative AI, Autonomous AI, Black Boxes, Hallucinations — there are a slew of new terms entering the public vocabulary to describe the capabilities and shortcomings of AI. Versing yourself in the lexicon will be critical to understanding how AI can, and can’t, serve your business. It will also be essential to communicating your strategy for incorporating AI. Here, we’ll only look at the few key definitions you’ll need to know for this post:

Generative AI — As the name suggests, Generative AI is a type of artificial intelligence technology trained on extremely large data sets to generate original content like text, code, images, video or audio. Just how original that content is continues to be a matter of fierce debate, but more on that later.

Autonomous AI — This term refers to AI systems that are designed to make decisions or execute sequences of maneuvers independent from human guidance. Although we haven’t yet realized a fully autonomous AI, this term can be applied on a spectrum to describe systems like those found in robotics or self-driving cars. As more inputs are incorporated into these systems, AI will gain more ability to learn from data and make its own decisions.

Large Language Models (LLMs) — LLMs are machine-learning algorithms that use massive data sets scraped from the internet to understand human language, synthesize information and predict content. These models mimic human intelligence by performing tasks like answering questions, generating text or translation.

Understanding the distinctions between different AI technologies is essential to understanding how AI functions. And knowing how AI works is critical to effectively using and interacting with it. For example, knowing that an LLM gives intelligent answers to questions by predicting the most likely response, without any actual understanding of what’s factual, might help us take a more critical approach to using content generated by AI.

Beyond talking about AI, we also need to learn how to talk to AI. There has been a lot of talk about prompt engineering (the writing of prompts to get AI to generate the content you want) becoming the next big job role. But the coming ubiquity of this technology will more than likely mean that everyone will need to know how to “engineer” a prompt. As companies adjust to this new reality, they should plan on training and educating their employees on effectively using AI in the workplace. Education will also be essential to minimizing the risks associated with AI, not least of which are the complicated copyright issues and looming regulatory questions.

Consideration 2: The Regulatory Environment Is Evolving, But Will It Keep Up?

Generating automated content with AI models trained on other people’s work brings up some murky legal questions. While there’s a lot of data on the internet that isn’t legally protected, what happens when an AI chat bot knows all about copyrighted material? That question has already made its way to courts in several high-profile lawsuits from writers and artists. Comedian Sarah Silverman, for example, is suing OpenAI and Meta on claims of copyright infringement, alleging their AI models were trained on illegally acquired data sets.

The questions surrounding intellectual property will likely be foggy territory for years to come, but the U.S. Copyright Office is attempting to bring some clarity. This year, it released a statement of policy that rules AI-generated content is not eligible for copyright. This should be a major consideration for businesses using AI. They’ll need sound policies for using AI to generate content if they want to protect their IP.

Even though businesses can’t claim final outputs from AI as their own, no matter how complicated the prompt, there are still many ways they can use AI to improve the quality and efficiency of their work. AI can be an extremely useful tool for inspiration and ideation; it can also have a big role to play in synthesizing and organizing information, producing strategy documents or editing human-created content.


Consideration 3: Avoiding AI Tool Overload With the Right Solutions

If it suddenly feels like there are AI tools everywhere, it’s because there are. According to Tracxn, there are approximately 58,000 AI companies worldwide, 14,700 of which are here in the U.S. Navigating the glut of AI tools might seem like an overwhelming task, but there are a few simple places businesses can begin.

Companies should first look at their existing tech stack to see what AI capabilities are already available to them. SaaS companies are racing to incorporate AI into their solutions to meet exploding demand, and chances are, the tools you’re using now already have AI capabilities integrated. These capabilities may not be public yet, so businesses may need to reach out to their vendors to see what’s available.

From there, businesses can identify gaps and begin assessing additional stand-alone tools to build out their stack. Experimentation will be key to determining which tools are right for your organization. Identify employees who would be key users and give them access and time to see what they can do with the tools you want to try. Or form a dedicated team to evaluate, experiment and develop use cases for new AI technologies.

This Is Only the Beginning

A prospect that many organizations will find equally exciting and terrifying is that the AI we’re using today is most likely the dumbest version of AI we’ll ever know. This is a rapidly evolving technology with unspeakable potential to transform the way we do business. The years to come will be a fast-paced race to keep up in nearly every industry.

Large enterprises will likely move toward developing their own proprietary LLMs to handle their unique proprietary data, while tech companies will offer ever more intelligent solutions to support businesses of all shapes and sizes. To stay relevant, companies will need robust AI strategies and policies in place to navigate the ever-changing market landscape.

Businesses will also need the right partners to support them in their journey. Working with vendors who fully understand the risks and rewards of AI, and who have robust policies of their own, will help protect IP and advance your organization. The right partner can also guide your organization on the best strategies for using AI or communicating your own AI capabilities.

At Godfrey, we’re extremely excited about the potential of this technology and we embrace the use of AI to improve the efficiency and quality of our work. But we’re not diving in without a plan. We’re developing a well-rounded strategy for assessing, implementing, communicating and scaling AI capabilities for our organization and our clients.

Where AI will take us from here is anyone’s guess, but we have a few ideas about what an AI-powered future will mean for business and marketing. Stay tuned for our next blog post on where we think AI in B2B marketing is headed.

Stacy Whisel - President

Stacy serves as Godfrey’s president and also oversees the channels and operations side of the agency. Her background in research and media is a key driver for ensuring Godfrey implements audience-focused programs.