AI is no longer science fiction — it’s a practical tool that’s available today in a variety of forms across the tech industry.
As AI tools such as ChatGPT and Google’s Bard continue to improve over the coming months and years — and are integrated into other technology and digital services — it will become increasingly important for marketers to understand the capabilities and limits of this technology, as well as the ethical concerns that surround it.
Artificial intelligence and machine learning have supported tools in the MarTech and business ecosystem for years, ranging from proofing tools like Grammarly to content generators like MarketMuse and Frase.
However, at a higher level nearly every tier 1 and tier 2 tech company (from FAANG/MAMAA to financial giants to industry staples like Adobe, Intel, and Salesforce) has been integrating at least some form of machine learning or algorithmic automation into their products and services since the early 2000’s.
To tie a more specific date to this trend, most major acquisitions, advances, and investments into AI began a little more than a decade ago, when Apple formally revealed Siri (2011), Amazon first released Alexa (2014), and other major players began making large strides in digital assistants, machine learning, and automation.
Today, AI is predicted to have an immense and profound impact on how we do marketing, and how we interact with our increasingly digital world.
In 2019, for example, McKinsey & Company predicted that AI and deep learning programs could account for “between $3.5 trillion and $5.8 trillion in annual value” for major corporations, with up to a $2.6 trillion impact on sales and marketing alone.
This major disruption in the business ecosystem means that B2B marketers need to adapt and evolve their workflows and strategies to thrive.
Importantly, marketers should be on the lookout for changes in the areas of research and automation, as tools and services come online that can make your job more efficient.
On the other hand, marketers should be especially careful of utilizing AI for content, as machine learning tools cannot and will not replace the need for strategic content creation and thought leadership.
AI and machine learning tools (such as ChatGPT) cannot and will not replace the need for strategic content creation and thought leadership.
Instead, these tools will simply change the process for creating such thought leadership — automating certain aspects of ideation, research, and proofing and ultimately simplifying and streamlining how we convey our insights and subject matter expertise to the broader world.
The growing presence of AI and machine learning programs in our daily lives necessitates an understanding of the capabilities of these programs, as well as an accounting of their limitations and flaws.
First, it’s important to note that understanding the basics of what ChatGPT is and how it fits into the broader discussion around AI is key.
Specifically, since services such as ChatGPT are simply the most recent step forward in the field of machine learning, it’s critical for early adopters of all AI technologies to know the capabilities and limitations of the algorithms and systems that support it.
Understanding AI programs like ChatGPT means learning the answers to three key questions:
ChatGPT is a large language model developed by OpenAI and based on the GPT architecture, which is further segmented into different versions (GPT-3, GPT-3.5, and GPT-4) — each with a higher level of access to more recent information, additional training data, and the broader internet.
It is a generative algorithm that takes user input and compares it to the information and knowledge stored in its database to identify patterns and build a response that appropriately answers the query through organic-feeling written responses.
Basically, the program reads your prompt and responds with the most appropriate human-sounding pattern it can generate using both the training data it has access to and the sum of all prior interactions people have had with the software.
The program learns what responses a user expects to receive from various prompts, and then uses the sum of the knowledge available to it to create new “patterns” (responses) that match the response a normal human would give.
By its very nature, however, ChatGPT can only reframe existing dialog and content in new ways — since all it’s doing is reorganizing the words and sentences it has access to in ways that match the patterns and cadences of normal human writing.
For this reason, ChatGPT and services like it will never create truly original content, and are often better used for researching existing topics, summarizing longer content, or manipulating information in ways that make it more presentable, readable, or scannable.
ChatGPT represents a foundational shift in what we can do with AI technologies.
Basically, previous implementations of AI were limited in scope or complicated enough to use that they weren’t really accessible to the public. They were hidden away in academia or labs — or implemented through simple buttons or features that limit user interaction with the AI technology.
ChatGPT, on the other hand, makes it incredibly simple to “play” with the AI through an intuitive chat box without having to spend money or understand the nuances of the system itself.
It’s tactile, and makes users feel like they have more control over what the algorithm can make or produce. All you need to do is give it a command in simple, everyday language and then see what it says back.
These traits (it’s power and utility, the lack of a cost, and the ease at which even non-technical individuals can use it) has contributed to a snowballing effect where people use the tool and then immediately rave about it in their social circles, spurring other people to try the tool and spreading through the social consciousness like wildfire.
This dual position as an exceptionally useful tool for business and as the shiny new toy of the internet has led to explosive growth, with ChatGPT reaching one million active users less than five days after its release in late November of 2022, and having more than 100 million monthly active users in January of 2023.
ChatGPT’s release can be viewed as the point where AI went mainstream.
We’ve been using more niche and focused forms of AI for years, such as the spam filters that keep our email inboxes clean or the search engines that suggest the most relevant, authoritative, and trustworthy answers to our questions.
Really, voice services like Alexa or Siri are the closest we’ve been to true AI that can do everything, and those effectively boil down to advanced, voice-based search engines.
The release of ChatGPT represents the identifiable moment where we’re transitioning from systems-focused AI programs — which serve to support the back-end of our modern tech-focused economy — to generative and responsive ones that people can actually use it in an intentional, focused way.
Further, ChatGPT’s success is representative of need and hype in the market surrounding the potential that these tools have for reshaping the profession of marketing.
As other organizations “scale up” their use of AI to meet public interest, we expect to see a boom of tools and solutions that use machine learning to drive more personalized and customized experiences for users.
Tools like ChatGPT raise valid ethical concerns relating to how marketing develop and publish content and thought leadership online.
There are five core considerations you should make when deciding how you’ll integrate AI into your current workflows:
At face value, any of these five topics should make you pause to think through your adoption of AI technology as a marketer.
Together, however, they raise an ethical storm around the subject of the role of machine learning in the broader marketing ecosystem.
For this reason, marketers should largely approach AI solutions with caution to ensure they’re the right fit and the right approach for your specific goals and initiatives.
Remember, AI programs are good at finding patterns, not at creating original, unique, and compelling content. As with all major advances in technology, it’s wise to question the “why” and whether you should before diving into the deep end of the AI ecosystem.
Programs such as ChatGPT won’t replace marketers or the need for thought leadership, it will just allow us to focus on other tasks that may require a more human element.
This means that the adoption of AI requires a reevaluation of what you do as a marketer, what you can automate using AI, and what you should automate to make your workflows faster and more efficient.
Specifically, AI’s best use case is to automate repetitive, time-consuming tasks that may otherwise take you away from the high-impact specialty work that has a lasting impact on your business’s bottom line.
For example, an evolving use case for machine learning programs like ChatGPT is to take meeting or interview notes as an input with an instruction such as “summarize these notes into a bullet list of the key takeaways and deliverables.”
The program will then read the notes, analyze the content, and provide a short summary of the important information you should take away from the meeting.
Rather than combing through your notes for hours trying to summarize the key points for stakeholders, you can automate the process in less than a minute and then spend another few minutes revising and editing the copy to fit your individual needs and goals.
Use cases such as this can help us identify the three key ways that AI can accelerate your productivity at work:
ChatGPT, Google’s Bard, and other similar services — in their current state as of March of 2023 — only scratch the surface of the potential of AI.
It seems like advances are made every day as the algorithms behind these tools improve and companies build AI integrations into their own services.
However, the most important takeaway in this rapid advance of AI programs will not alter the foundational elements of marketing (or put us out of a job) — it will just affect the way that we approach new marketing initiatives by providing us with tools to make our jobs more efficient.
As noted by Sabine Hauert, co-founder of Robohub.org and Associate Professor in the Bristol Robotics Laboratory at the University of Bristol:
Robots are not going to replace humans, they are going to make their jobs much more humane. Difficult, demeaning, demanding, dangerous, dull — these are the jobs robots will be taking.
Programs such as ChatGPT will simply remove the difficult, demanding, and dull aspects of marketing — the repetitive tasks that take us away from the work that requires a human element — ultimately making us more efficient and more effective in telling our brand stories and improving every experience and touchpoint relating to our organizations.
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