This blog is an excerpt from a presentation delivered recently by Daksh Sharma, the co-founder of Iffort, at the 7th edition of #SMLive, Social Samosa’s virtual conference. To know more, click here.
For more than a decade, I have witnessed the remarkable influence of Artificial Intelligence (AI) across various industries, including marketing. Leveraging AI in marketing has become a game-changer for brands and agencies, enabling us to analyze vast amounts of data, extract valuable insights, automate processes, and deliver personalized experiences to consumers. I firmly believe that AI in marketing has the power to revolutionize how we, as marketers, engage with our audience.
At Iffort, a technology and digital marketing partner, we have actively embraced the potential of AI in our marketing endeavors. Contrary to the common belief that AI is limited to ChatGPT and Midjourney, I introduced our AI technology stack, showcasing the wide spectrum of AI applications and debunking misconceptions. To provide a comprehensive understanding, here I refer to Jeremiah Owyang, a Forrester Research Analyst, who outlined the key layers of the AI infrastructure.
The foundation of all AI models lies in the data layer. This layer comprises public data, proprietary data, and synthetic data. Public data, accounting for 20% of the stack, encompasses the content consumed by Large Language models (LLMs). Behind organizational firewalls, we have proprietary data, while synthetic data is generated during interactions with LLMs. I emphasized the significance of future data validation, known as ‘Proof of Fact,’ which will add an extra layer of credibility to synthetic data.
The AI infrastructure layer plays a vital role in supporting AI operations and consists of hardware and data centres. It is worth noting that a significant portion of global AI production, around 90%, originates from Taiwan, where there is high demand for hardware resources.
In the AI model layer, marketers and developers have a wide range of options, including proprietary and open-source models. To achieve the best results, I recommend combining both types of models.
AI Apps and Autonomous Agents are gaining popularity across various domains. There is an influx of emerging AI apps, with a website called “There’s an AI for that” offering over 6,500 projects. These apps cater to both B2C and B2B markets, providing diverse solutions. Additionally, autonomous agents, formerly known as bots, play a crucial role and can be configured and optimized to tackle specific tasks or problem-solving.
What makes AI truly remarkable is its constant evolution. Any challenges we may face today will soon be resolved, thanks to the dynamic nature of AI.
I also want to talk about the AI marketing stack, which encompasses a wide range of AI-powered applications and tools designed for marketers. Each layer within the stack addresses specific marketing requirements, such as research, long-form content creation, video editing, and more.
Looking ahead, AI holds tremendous potential for optimizing marketing strategies. It will accelerate content production timelines, reduce costs, and give rise to a new wave of AI-led agencies with innovative business models. Marketers will need to closely observe how users consume content and embrace automation. However, it’s essential to acknowledge that as AI tools continue to evolve, security remains a significant challenge. Furthermore, building the brand voice and establishing trust when LLMs make recommendations are ongoing issues. Copyright concerns also arise as AI becomes more prominent.
AI in marketing extends beyond specific applications. Embracing AI allows marketers to gain deeper insights, enhance efficiency, and create impactful campaigns that resonate with their target audience.
In conclusion, AI empowers marketers to think from a creative lens and push the boundaries even further. It presents an exciting future for the marketing industry, and I am thrilled to be at the forefront of this transformative journey.