I was intrigued by a Seth Godin podcast episode that talked about the Gartner Hype Cycle. After a year of reading lots of different views from across the industry and helping test AI app development amid the buzz around this latest big thing, I wondered how AI sits within that.
As digital marketing professionals, we are naturally drawn to the latest and greatest technologies to understand how we can leverage them and maybe get a jump on competitors and seize the chance to develop new techniques or ways to add value to campaigns. Artificial intelligence (AI) has dominated emerging trends, promising to revolutionise everything from content creation to campaign optimisation. But amidst the hype, lies a crucial question: Which AI solutions will be truly transformative, and which disappoint after inflated expectations?
What is the Gartner Hype Cycle?
The Gartner Hype Cycle represents a methodology for separating the wheat from the chaff. Every year, Gartner maps out emerging technologies across industries, charting their journey from innovation trigger to plateau of productivity. The 2023 cycle, unveiled in August, provides valuable insights for AI-curious digital marketers like us.
Let’s dive a little deeper into the Hype Cycle to uncover the opportunities and pitfalls for AI in today's marketing landscape.
- Innovation Trigger
This is where we see the sparks of initial excitement, amplified by media buzz and early adopters. In 2023, generative AI, capable of creating text, images, and even code, grabs the spotlight. Imagine crafting personalised marketing copy at scale, or generating unique visuals that resonate with diverse audiences. The possibilities seem endless, but remember, this is just the beginning.
- Peak of Inflated Expectations
Here, enthusiasm reaches a fever pitch, often surpassing the technology's actual capabilities. AI-powered customer service chatbots are a prime example. While convenient, many fall short of offering truly human-like interactions, leading to user frustration and disillusionment. As digital marketers, we must approach early adopters with realistic expectations, setting the stage for sustainable long-term adoption.
- Trough of Disillusionment
As limitations become apparent and initial hype fades, many technologies fall into this valley of despair. Hyper-automation of marketing tasks exemplifies this. While automating repetitive processes holds promise, overreliance can lead to homogenised, uninspired campaigns that miss the human touch, not to mention the question of regulation. This phase serves as a crucial reality check, urging us to focus on AI's ability to augment, not replace, human creativity and strategic thinking.
- Slope of Enlightenment
Through rigorous testing and refinement, viable solutions emerge from the trough. AI-powered personalization stands out. Imagine tailoring websites, emails, and ad campaigns to individual user preferences in real-time. This phase emphasises the need for data-driven experimentation and a focus on measurable outcomes. As marketers, we must invest in building AI expertise and robust data infrastructure to navigate this critical stage.
- Plateau of Productivity
Finally, technologies that deliver real value reach mainstream adoption. Predictive analytics, powered by AI, is a great example. Anticipating user behaviour and tailoring marketing strategies accordingly. This plateau signifies the true potential of AI, but reaching it requires collaboration between marketing and data science teams, along with a clear understanding of business goals. We have experienced this to some extent with Google Analytics but I am sure this will evolve rapidly.
Beyond the Hype
The Hype Cycle offers a valuable framework, but it's just the starting point. Here are some key takeaways for AI-savvy digital marketers:
Focus on business problems, not technology solutions. Don't be seduced by shiny new tools. Define your marketing goals and identify areas where AI can add real value.
Embrace experimentation and iteration. AI is not a silver bullet. Be prepared to test, refine, and adapt your approach based on data and performance.
Build your data foundation. AI thrives on quality data. Invest in data cleansing, integration, and analytics capabilities.
Foster collaboration. Bridge the gap between marketing and data science teams to ensure effective implementation and integration.
Stay human-centric. AI should enhance, not replace, human creativity and strategic thinking.
The 2023 Hype Cycle paints a fascinating picture of AI's potential in the marketing landscape. By understanding the phases and adopting a strategic approach, we can avoid the pitfalls of inflated expectations and unlock the true power of AI to build meaningful connections with our audiences, driving tangible business results. Remember, the journey from hype to reality is a marathon, not a sprint.
Let's tread carefully, learn from the past, and embrace AI as a powerful tool to elevate our marketing strategies and deliver unparalleled customer experiences.
By Stephen Caple with the help of Bard ;-)
Image credit: Gartner.com
