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The Gist
- AI marketing tools. 2023’s AI tool experimentation sets stage for strategic alignment in 2024.
- Process standardization. Ad hoc AI tool usage transitions to systematic integration and policies.
- Demanding ROI. Shift from experimental AI use to focused, result-driven applications in 2024.
From the amount written and discussed about the topic in 2023, you’d have thought that artificial intelligence was invented in late 2022 if you didn’t know better! Regardless, it has been hard to have a conversation about marketing technology, let alone marketing and advertising — or really anything lately — without AI coming up.
Let’s take a look at the state of AI marketing tools.
Some of this hype is justified, and some of it is, of course, just hype. That said, many companies have made many investments in AI marketing tools, methods and technologies. Some of these have been very strategic and well-aligned with organizational objectives, and others have been much more ad hoc and tactical, with the results either unclear or not shared more broadly within the organization.
I believe that, while 2023 was the year of experimentation with AI — from dabbling in ChatGPT to doodling in DALL-E — 2024 is going to be The Great Reconciliation, where all of those experiments, whether scientific or not, will need to be aligned with larger goals, budgets and workstreams.
In other words, 2024 will be the year we stop playing with AI and get back to work.
In this article, I’m going to talk about three ways that this Great Reconciliation will occur and some reasons why this is a good thing to happen.
Related Article: AI in Marketing: More Personalization in the Next Decade
AI Marketing Tools: Scattered Trials Become Standardized Platforms
Let’s start by talking about all of the trying and testing that has been going on. With the myriad of AI-based platforms, for a variety of needs that include text, image, video, audio and even design generation, individuals and teams have had a hard time keeping up with all of them. That isn’t to say, however, that they haven’t tried plenty of them.
Trying out the AI Tools
For instance, as of June 2023, there were over 18,500 AI startups in the United States alone. I feel like I’ve tried a good percentage of those myself, but know that I only really scratched the surface, even with an extensive amount of time experimenting. That said, large organizations with many team members, all trying different tools means that there have been a lot of trials started, a lot of duplicate evaluations, and some missed opportunities to coordinate trials and the learnings from them.
New AI Features in ‘Traditional’ Platforms
Additionally, many of the more “traditional” platforms that marketing teams use, such as Adobe, Hubspot, and Salesforce, have also introduced AI marketing tools. These and many other longstanding platforms have added generative AI features, from chat interfaces to other elements. And, like any implementation of a new feature by an existing platform, sometimes they work really well and sometimes they leave a little to be desired.
That said, there is often less perceived risk from using an already-vetted software platform than in trying something brand new from a fledgling startup, so the powers that be are generally going to be more keen on using the AI tools from the established players, even if they sometimes may not be as innovative or groundbreaking in their execution.
The AI ‘Wild West’ Won’t Last
In 2024, we’re going to see the “Wild West” scenario of a hundred different platforms used, tried, and kept or discarded, being consolidated to a handful of go-to tools that are recommended. Additionally, those organizations that have made heavy investments in existing platforms that have added AI capabilities are likely going to encourage their teams to use those, regardless of the quality of the results achieved through those platforms.
Relate Article: Staying Human While Using Generative AI Tools for Content Marketing
Experimentation With Approaches Becomes Codified Processes
With the amount of attention given to AI-based tools and the experimentation around them in 2023, there was no doubt some impacts to both existing processes, as well as how future processes, are being planned. That said, in one study, nearly one-fourth of respondents said that they were covertly using ChatGPT at work because they didn’t know their own company’s policies on generative AI usage. So much of the work being done with AI tools was either circumventing existing processes, or at least working within them as to minimally impact them.
All of that said, in some areas of marketing, AI-based tools are likely to have required some bigger changes to process. Particularly when generative AI is being used in personalization across channels, in ecommerce and similar use cases, these are not things that simply happen on an ad hoc basis. Yet, a lot of the usage of AI marketing tools has been relegated to less integrated systems and done in a more ad hoc manner.
The ‘Anything Goes’ Approach
In 2024, we’re going to see the “anything goes” approach to working AI marketing tools into some existing processes to much more standardization both at the company level as well as at the department or team level. Expect AI policies, approved uses, products and more to be a lot more prevalent. While all of this might sound like a downer to some of you, for others where the blanket policy has been two letters — N-O — this greater depth of policy is a good thing. It means that some of the more conservative organizations that simply banned AI usage at first are going to need to take a second look and have a more nuanced approach.
Related Article: The 2024 AI Roadmap for Marketers
Outcome-Independent Trials Become a Demand for ROI From Leadership
We’ve talked about the sheer amount of AI-based platforms available to experiment with over the last year, as well as how those tools have the ability to impact existing (and brand new) processes that marketing teams use.
Last, but certainly not least, let’s talk about how success is measured.
How Much Measuring Took Place?
In the case of initial experiments with brand-new platforms from startups that may not have existed six months prior, I’m going to go out on a limb and assume that there was simply a lot of ad hoc trial and error with these platforms. Therefore, strict KPIs and measurements around their success were less of a focus than answering questions like, “Does this platform even work?” or “Will this platform do what me and my team need it to do on a consistent basis?”
Of course, that’s not the case for all AI usage, particularly when the scale of usage was large and when there was a direct impact on sales or other revenue-adjacent activities. But when usage of AI was done behind the scenes, or in and around current ways of working, there was likely little measurement of even time and cost savings.
AI ‘Honeymoon Phase’ Will Be Over
In 2024, we’re going to see a pretty stark contrast here for those organizations that haven’t already begun taking a sharper look at their employees’ AI usage. The “honeymoon phase” of AI experimentation over and managers and leaders demanding more concrete ROI from the tools that teams are using. This could be a either generating more revenue, or saving more money — or both — but the days of rampant experimentation are going to be tempered by a return to the way things are normally done from a cost-benefit standpoint.
Final Thoughts on AI in Marketing
I must admit that it’s been a fun year — at least when it comes to exploring artificial intelligence platforms. Getting the chance to play with hundreds of AI-marketing tools, features and functionality has given teams a lot of learning and perspective on what they really want and need. So in that sense, the experimentation has been worth it.
But, with 2024 on the horizon, it’s time to get a little more serious about how AI tools, the processes used to operate them, and the results we expect to gain from them.
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