After the Gen AI and ChatGPT tsunami that has taken so much of the marketing dialog in 2023, we thought it would be a good time to sort through the noise, assess where we are and set the stage for 2024.
Where Are We and What Did We Achieve in 2023?
Generative AI has established itself firmly as part of the marketing firmament. Many of the commercially available LLM’s and applications such as ChatGPT and now Google Gemini have proven themselves to be trainable, mostly accurate, and usable in a variety of settings. According to McKinsey, over 70% of businesses across geographies are somewhere along the spectrum of actively using AI to have tried AI at least once, with very few showing no familiarity with AI and its use.
Marketing and sales are the most common use cases for Generative AI. Generative applications are now in use to generate text, imaging, and to automate campaigns. Many of these tools and applications exist in siloes and have not yet been integrated into enterprise workflows, and overall integration risk around data and accuracy are correctly creating a slight slowdown in universal use. Most martech providers are, authentically or not, claiming AI features in their platforms.
However, Generative AI adoption is proceeding at a breakneck pace. Compared to the digital revolution, we have accomplished more in a year than the first 5 of that transformational period.
So, what’s next and what should marketers be thinking about headed into 2024?
Key Themes For Marketing AI in 2024—The Year Of Integration
While we expect the evolution of tools and AI capabilities to continue, we’re now entering a phase of integration and adoption—arguably, the harder parts of the equation. Executing well will require businesses to be on top of both the technology and the change processes needed to create AI “wins”:
- Bigger and more powerful models: The introduction of LLMs by Google and Amazon with an increasing depth and breadth of training parameters and capabilities will usher in increased capability, complexity and accuracy.
- More use of true AI in enterprise tools: The surface level introductions of AI in martech tools will get deeper and more real, and business and IT users will need to constantly evaluate their partners and the buy or build choice.
- Point solution acceleration—but the start of the shakeout: The VC community has thrown money at AI startups over the last few years, but the sheer volume of competing businesses and the short fuse that all VC funds are on given interest rates and pressures on returns will result in a flood of new applications, but a short runway for many of them. End users will want to be judicious in which tools they license.
- Increased pressure on data and IT resources: Data volume, velocity, and accuracy will be of increasing concern for IT and business users and the volume of compute needed to power increasingly sophisticated models and applications will increase exponentially.
- Multimodality: As GPT-4 and Gemini demonstrate, text, images, code, video and audio will be everyday inputs and outputs, with seamless navigation between them.
- Personalization: Generative AI models are also becoming more adaptive and responsive to the preferences, needs, and contexts of the users across all kinds of experiences and shopping models. As it has been for the last few years, consumers will respond favorably and require marketers to keep raising the bar.
- Buy or build decisioning: Business and IT leaders will need to grapple with licensing SaaS tools with AI components, building AI predictions and the likely hybrid scenario of licensing an LLM and customizing applications on top of them. There is no right answer, but this dialog will and should be persistent.
- Governance: As we move from point solutions to more tools and models that are integrated into enterprise workflows, setting up formal data and AI governance structures will become a requirement—and possibly slow down adoption. All for good reason.
- Team and Process Development: Back to the “Year of Integration” theme, teams and business processes will need to evolve in a structured way to take advantage of the potential that Generative and Predictive AI offer. This will require imagination, creativity and good process all in parallel. We have opined on those topics in the previous edition of Growth Marketing Insider, available here
