AI Direction Strategy for Selecting Suitable Generative AI Endeavors
Right in the AI Zone:
Artificial Intelligence (AI), machine learning, and Large Language Models (LLMs) are the new cool kids on the block, sweeping across every sphere of human endeavor like a tidal wave. After OpenAI released their GPT application to the world, these babies have been the talk of the town. It's party time in the tech world as businesses and organizations are jumping on the AI bandwagon to create unique applications aiming to outdo their competitors.
But what's the big deal with LLMs and how will they make an impact? The debate is heated, yet murky. Businesses that understand the potential of LLMs and capitalize on it will gain a great advantage.
Params and Play: Generative AI, an offshoot of AI, has a massive audience. It can generate reports, drafts, and even out-of-the-blue ideas, making it the life of the party. So, let's cut through the noise and focus on where LLMs can make an initial splash.
From Danger to Delight
Risks and demands vary across businesses and industries. Drawn up in a 2X2 matrix, we can summarize it like this:
- Low-risk, high-demand: Copywriting, marketing, learning, ideation, design, and reviews.
- High-risk, high-demand: Medical diagnostics, coding, legal advice, business intelligence, compliance technical writing.
- High-risk, low-demand: Specialist technical advice.
- Low-risk, low-demand: Social media posts, images, jokes, poems - spontaneous applications.
The first category - "low-risk, high-demand" is like a gold mine, and businesses are already diving in with innovative solutions using LLM models to churn out content. After all, marketing needs plenty of ideas, customization for target audience, rich, engaging content. Creating learning content also requires pinpoint accurate delivery of content tailored to the audience segment. Since there's an overabundance of content available, LLM applications can learn quickly, digest it, and deliver quality content to the target audience like a well-fed, well-trained pup.
Other tasks may be more important to businesses with higher risk but less demand. Businesses should draw up a demand vs risk matrix for their industry and determine which tasks or functions to tackle first. They can then use it as a starting point to map out the opportunities👌[1]. Investing wisely to prove the use of these tools will instill confidence in the workforce.
Tread Carefully
The other three categories are tricky and should be approached with caution. There's a flurry of regulatory measures being planned and discussed to ensure these tools don't cause harm to the general population. In these areas, their impact might be significant💣[2]. So, without a roadmap, it's better to wait for the rules to become clear before diving in.
- disclaimer: Low-risk is still a risk as the output from LLMs could go haywire. Businesses developing new models should have adequate tests in place to ensure these errors are eliminated before sharing with their audience. They should strike the right balance between quality and speed.
Gear Up for the AI Raceby Marc Zao-Sanders and Marc Ramos, HBR, 2023/03
Marketing and Copywriting leveraging LLMs can significantly reduce the time and effort required, allowing marketers to focus on strategic decisions. LLMs can generate wide-ranging content types, power conversational AI tools, translate content accurately for global marketing efforts, and analyze large volumes of customer feedback and market data to provide valuable insights. While offering benefits, the operational costs of LLMs may impact smaller businesses or those with limited budgets. Balancing AI-driven content with human creativity and empathy remains crucial to maintain authenticity and brand voice. Regulatory and ethical considerations related to data privacy and the use of AI-generated content should be addressed proactively.
Artificial Intelligence (AI) and Large Language Models (LLMs) are proving to be game-changers in the "low-risk, high-demand" sector, significantly reducing the time and effort in marketing and copywriting. These advancements empower marketers to focus on strategic decisions while generating a wide range of content types, powering conversational AI tools, translating content for global marketing efforts, and analyzing customer feedback for valuable insights.
However, smaller businesses or those with limited budgets should carefully consider the operational costs associated with these technologies. Balancing AI-driven content with human creativity and empathy is essential to maintain authenticity and brand voice. Furthermore, regulatory and ethical considerations related to data privacy and the use of AI-generated content should be addressed proactively.
