We know everyone is talking the AI and ChatGPT talk these days, driven by a huge media hype. This undeniably revolutionary AI influence is changing our ways of working. But have you already asked yourself what it means for marketing content management — and specifically digital assets?
How can we prepare today for the age of AI-driven content creation and AI-driven marketing?
Many large organizations have started experimenting with AI-tools — such as ChatGPT or one of the many others — in recent weeks and months, sometimes with amazing results for creating or improving content. And all this based on a few smartly worded and simple prompts steering an AI tool to provide valuable output that remarkably fits the marketing lingo of today.
However, when discussing AI with our clients and prospects, we also feel that no one really knows how far it can go. Furthermore, it isn’t yet clear which AI algorithms will be integrated into the daily content creation or content adaption processes that take so much of marketing teams’ time.
The biggest hurdles in deploying AI for content marketing
There are many reasons why companies are only sporadically using AI for generative content. Some that we commonly see include the following:
- Many of the AI tools and technologies are still very new. Companies and individuals are only now figuring out how to even use and prompt these incredibly smart tools properly.
- AI tools such as the widely spoken-about ChatGPT have their known limitations in terms of data and, as a result, in the valuable information and content they can create.
- Marketing content should be aligned with client data in order to be relevant and personalized, which is something that the latest AI models still have not been trained to do very well.
- Companies (and, in Italy’s case, entire countries) are so unsure about what data should or can be shared with publicly available AI tools that they have temporarily banned the use of certain AI technologies altogether.
- Most organizations are trying to figure out if the use of publicly available AI databases is in the interests of their businesses or if the only way forward are proprietary AI-tools that can be separately licensed and then trained in secure environments with protected, company-specific data.
- Of the several thousands of AI tools popping up, no one can really tell which solution or model will be leading in a few years’ time – so many apply the strategy of “let’s wait and see how this plays out.”
While these are certainly very valid reasons to be cautious about deploying AI-models into core marketing processes today, the increasing speed at which the change is and will be happening cannot be ignored. Therefore, every C-Level executive — as well as any team involved in communicating with clients or managing some form of the client relationship — should urgently ask themselves what they can do today to prepare for the age of AI-driven content generation and marketing.
Getting ready for AI-supported content generation
So, even as AI is new and relatively unexplored, what is it that every company should do now? Well, as we all know already, any systems — and especially AI algorithms — are only ever as good as the data being fed into them. So how do we start training these new models that will create or adapt content specific to our business, aligned with our branding and principles of communication? If you follow this thinking a little bit further, it simply means that in an AI-driven world, digital assets are the fuel that powers algorithms. As a result, effective content and client data is essential to ensure the accuracy and relevance of the marketing data used to train AI models.
Companies who do not want to be left behind in the race for future-proof, scalable content operations need to prepare the underlying marketing data that should feed such algorithms – i.e., companies need to prepare and organize marketing content and customer data now more than ever. To avoid losing out in the race to create and train such intelligent AI models, organizations need:
- Their best practice content
- Their best marketing images and videos
- Their most perfectly designed online marketing materials and ads
- Clear brand and tone of voice guidelines
- Their most telling customer profile and behavioural information
With this ready to feed into AI tools, organizations can best train them. This should eventually help automate and multiply the company’s content output and relevance and, therefore, revenues.
To put this into simple words: if you don’t collect, organize, tag, and manage your marketing content and assets in a central system and if you don’t get your marketing and customer data structured, you will not have a useable basis to train a marketing-oriented AI model – no matter which of the AI tools eventually succeed in the market.
Why your stack matters to stay ahead of the AI curve
While the topic of collecting, organizing, and tagging content in a central solution isn’t new, the necessity of DAM, CDM, CRM, CDP, and other related solutions has never been bigger. In the future AI-driven marketing world, your company-specific data and content is the main differentiator you have. Your martech stack is becoming even more critical to your business success than ever before.
