You’re already behind: The time to embrace generative AI is now

Many trends have hit marketers and marketing strategy over the past 15 years

Some have simply been flashes in the pan, like the metaverse, cramming B2B on Instagram, while others have been durable and had a lasting impact on marketing techniques and channel usage. Some trends have stuck around but evolved significantly, such as the way marketers approach personalization — the transition from profile data to engagement data for decision making. Over time, the strategies that enter the digital marketing canon are the methods that are both genuine and widely practiced.

Given this, it’s not surprising that marketers’ outlook when a new disruptor comes blasting into our work-i-spheres is often, “well, we’ll just see about that ?”. Given the martech landscape, which is littered with some hits but many misses, we can’t be blamed for sometimes being a little hesitant with new tech and strategies. As marketers, we gain confidence when we are able to pilot a trend, and then stop to evaluate data, and then make decisions about potentially moving ahead or changing course. Does the new strategy get cut? Does it evolve? Does it stay exactly the same because maybe our control was compromised?

But AI isn’t new. In fact, it's been hyped as the hot trend for years. Looking back to 2017, Forbes and Gartner both predicted 2017 to be a pinnacle year for utilizing artificial intelligence and machine learning. We’ve seen movies like “Her”, where artificial intelligence isn’t some scary, oppressive phenomenon, but embraced and cemented into society.

Let’s define…

Generative AI defined from Gartner: “techniques that learn a representation of artifacts from data, and use it to generate brand-new, unique artifacts that resemble but don’t repeat the original data. These artifacts can serve benign or nefarious purposes. Generative AI can produce totally novel content (including text, images, video, audio, structures), computer code, synthetic data, workflows and models of physical objects. Generative AI also can be used in art, drug discovery or material design.”

Machine learning defined from IBM: Machine learning is a branch of artificial intelligence (AI) and computer science which focuses on the use of data and algorithms to imitate the way that humans learn, gradually improving its accuracy.

Why is AI now resurfacing as a must-have? Why Now?

Historically, artificial intelligence really was for the tech savvy employee or developer who had access to code or tools. You needed something like a customer data platform, a CRM system (think Salesforce Einstein) to really grasp and execute what earlier stages of AI looked and performed like. You needed to be hands-on, in the driver's seat with a dedicated plan to utilize artificial intelligence. The user interface and usability is why now is the time. Accessibility + simplicity + intuitiveness is the foundation to technological acceptance.

The iPhone has a similar beginning. Smartphone devices were around for a few years prior to the iPhone. However, when the iPhone was introduced, it succeeded and became an essential piece of technology because of the interface. The simple navigation of the apps steered adaptability and usage. When technology becomes accessible, simple and intuitive, it becomes an essential component of daily life.

Now, anyone with access to the internet is able to experience and engage with AI. The interface is now easy to use. You don’t need access or a subscription to a massive tech platform behemoth like Adobe or Oracle to see what artificial intelligence can do. It’s not also not contained to just what your work role might ask of you. Using ChaptGPT, endless options for use are available. Plan a multi-stop vacation, generate a survey, proofreading, market research, create a quiz, html generation, debugging, documentation. You could also write music, translate language, and simply have a chat companion.

Furthermore, we’re at a turning point where our mountains of big data can be accessed and tapped to pour the relevant information we want. The human element of interpretation and the need to analyze is removed in a way. Imagine approaching your CRM platform with one set question or task in mind. Imagine being able to just ask: “I am going on a client visit today, what do I need to know?” Instead of searching in multiple places - employee engagement page, account details, registered deals, annual renewal dollars - you can ask the CRM a question, and it will provide only the data you need. Only the relevant data, in one place. Our dashboards do this today, and we can craft what they look like in anticipation of what a seller or executive might want to see, but we’re still serving a search and analyze view of important information for what will be a human to human interaction.

When you think of your favorite apps, are they on the top of your list because the information is easy to find, searchable and comprehensible? Banking and fitness apps standout, where they help show so many insightful graphs of data. Data personal to you and how you’re actively living. How many steps you took, or how much you spent just on lattes at your favorite coffee shop. This data is presented to us in a beautiful way, but we still need to interpret and sort out the elements that are important to us. AI is when the data says “You’re spending too much money on lattes”. Making sense of the data and providing an actionable next step.

Likewise, think of the annual Spotify email we all look forward to at the end of the year. It’s showing us a view, providing us with data about what we listened to all year. It so beautifully presents the statistics or our listening behavior, but what from it, did we ask for? What from it will we action on? We get lost in data. We get distracted by data. And so many of us are used to these landing zones of data. (Wikipedia hole anyone? Facebook circa 2004 anyone?) Having a tool to pick out the necessities and make sense of it is where AI is going to have the biggest impact.

Technology platforms are collecting more data than ever before through tracking tools, and AI offers a solution for effectively harnessing this data to achieve our goals.

What’s next?

Think of generative AI as a conversation. Your CRM system is being asked a question and answering with the data you need. Your mountain of data is being reviewed and thought through. It doesn’t just stop with marketing or sales tools. Think of any platform that can collect and house data. Genetic testing sites could start to collect not just your health and DNA makeup, but start to gather your life story. Could you write down your essays, thoughts, journals, so that future generations, great-great-grandchildren could interact with a platform to find out more about you, from the actual source?

Are we approaching the waning significance of search as AI starts to dominate our technology interactions? Should I be searching, reading, analyzing, when I could be asking and conversing with data.

So, what is the best way to embrace it?

No company wants to be left behind when it comes to the latest technology and no company wants to be using archaic marketing strategies. AI is not a tech squall, it's ready and now is the time to embrace.

Generative AI adoption should not be a one-size fits all approach. It’s unique and personal to your brand. As a digital marketer, the focus areas for AI will be to continue personalization, testing and iteration, maintaining a solid brand voice, designing engaging conversations and integration with and through all channels. There are ways to utilize it both internally with your operations teams and externally to your customers and prospects. Content maintenance and governance through digital asset management and content management systems is easily achieved. Acquia’s Digital Experience platform has AI features that will alleviate the workload associated with crafting content components, speeding up the time it takes to bring products to market and improving accessibility in the process. Read more about the advancements here.