AI Adoption in Marketing
The Martech world has been flooded by new AI capabilities, tools and advancements that are both incredibly exciting and pretty overwhelming. While we all want to take full advantage of the AI boom and its potential, it is neither realistic nor profitable to invest our time and money into every single AI innovation. The enthusiasm is real, but we must prudently step through this new world in a similar manner as tech professionals once did when adopting the early internet to be successful.
Now obviously all AI tools and capabilities are not created equal, but for the sake of this discussion I’m taking the liberty of grouping them together as one overarching technological advancement. I don’t have the time (or probably the IQ) to attempt to discuss the nuances of adopting all recent AI innovations in the Martech space. So instead, I think it would be both interesting and relevant to review some common challenges to adopting any AI capability in our rapidly evolving industry. Below are some general themes that seem pertinent to most use cases.
It Takes Time, Be Patient
In this Martech.org post about technological adoption, Marc Sirkin compares AI adoption to past advancements where “we were spectacularly wrong about the timeline and embarrassingly naive about the slog involved in getting there.” These previous naiveties can be seen today as we impatiently attempt to unleash the full capabilities of AI “overnight”, while ignoring or misinterpreting the lengthy onboarding and training necessary.
Similarly, this report by Influencer Marketing Hub explains that AI adoption in marketing processes faces several hurdles like budget constraints, limited technical expertise and organizational resistance. But “lack of understanding” stood out as the primary barrier to over 70% of respondents. Gaining deeper understanding and familiarity with these tools can only happen through experience, and experience takes time.
Myopia Trap: Focus on Your Goals
Focusing on tools’ features blinds us to their actual impact on outcomes and the customer experience. A good example of this is when your organization either upgrades a software platform or purchases a new optimization tool with fancy AI capabilities. Immediately the desire is to test out the new features as soon as possible, with less focus on the end results. A solid best practice is to stay focused on your bottom-line business objectives and work backwards. If one of the new capabilities can accelerate your path to reaching your goals, then go for it!
Trusting the Machine
According to a recent IBM survey related to AI adoption, 45% of respondents indicated concerns about data accuracy or bias, while 40% expressed concerns related to privacy and confidentiality of data. “Letting go of the wheel” is a huge obstacle to fully unlocking AI tools, while excessive manual intervention and limited usage can stifle ROI, ultimately making organizational buy-in even more difficult. Smaller, incremental successes are paramount to growing organizational buy-in for AI tools, as they demonstrate tangible value, build trust, and encourage broader adoption. As described by Emerson Taymor of InfoBeans, “Small wins are essential for building momentum in AI adoption. They provide quick, measurable results that help establish trust, demonstrate ROI, and reduce resistance to change.”
Cultural Change Lag
Organizational culture evolves linearly, resisting rapid tech-driven shifts (Martech’s Law). Habits and processes change incrementally, slowing adoption of new tools. Similarly to how your customers don’t drastically change their onsite behaviors overnight, marketers and end-users of these new capabilities will likely not change the way they work instantly either. This slow cultural change can be due to many factors including behavioral inertia, fear or simply lack of understanding and training resources.
According to a Salesforce survey 39% of marketers aren’t sure how to safely use gen AI, while 43% said they don’t know how to get the most value out of it. Successfully investing in these tools means investing in training and onboarding as well. As Sirkin puts it, “The marketing leaders who thrive in the AI era won’t be the ones implementing every new tool or chasing every shiny object. They’ll be the ones who remember that technology is never the hard part. The hard part is always the humans.”
Everyone is Different
Just as all GenAI tools, chatbots and LLMs are not created equal, neither are the end users of them. Marketing technology is a vast and diverse space that is changing constantly. We all will unquestionably find our own favorite tools and programs that strengthen our overall service offering. As examined on Smart Insights, the chart below shows how diverse AI usage already is today. We can only expect this to usage diversity to increase as new capabilities are introduced to the market.
Organizations will need to prioritize AI strategy to efficiently and intelligently evolve with these technologies. An AI “playbook or governance plan to focus on specific use cases and tools” will be super important to managing internal adoption and create a unified brand voice.
To summarize, Martech’s AI boom excites but overwhelms. Prudent adoption – not chasing every tool – is key. Challenges include time-intensive onboarding, goal misalignment, trust issues, cultural lag, and diverse user needs.
