Using AI for Strategy: Major Implications

Artificial Intelligence (AI) Language Models, such as GPT-3, have taken the world by storm with their astonishing ability to comprehend and generate human-like text. These models possess an almost uncanny capacity to accumulate knowledge and provide responses that seem nothing short of miraculous. But every obscene gift comes with a catch...

Unveiling the Generic Genius

When engaging with an AI LLM, you may notice that it tends to offer responses that are eerily familiar or lack specificity. This is because these models have been trained on a colossal amount of data, absorbing a wide range of information from diverse sources. As a result, they have a propensity to generate answers that align with common knowledge or conventional wisdom, rather than providing tailored and nuanced insights. It's like having a conversation with a genius who knows too much but struggles to offer novel perspectives.

To illustrate this point, let's consider a thought experiment: Imagine you ask an AI LLM for recommendations on improving customer satisfaction in the hospitality industry. Instead of offering unique and innovative strategies, it might regurgitate well-known solutions like personalized experiences, prompt customer service, or attention to detail. While these suggestions hold merit, they lack the depth and creativity that human experts bring to the table.

Precision: The Art of Directing AI

To maximize the value of AI LLMs, it is crucial to provide them with specific frameworks, industry knowledge, and contextual information. By going beyond surface-level questions and modeling out precise scenarios, we can elicit more tailored and insightful outputs. For instance, if we guide the AI to consider the impact of digital innovation on customer satisfaction in the hospitality industry, it may generate more specific solutions like implementing mobile check-in systems, personalized mobile concierge services, or using artificial intelligence to predict guest preferences. The deeper you prompt it, the more useful it will be. Feed it a framework to answer with, demand that it come up with 'never before seen' ideas, demand for it to do better. These all work. The key is to be precise in our instructions, allowing the AI to delve deeper and deliver more original insights.

Our Moral Obligation

As AI continues to advance, the responsibility falls to us to address the moral implications and redefine the role of analysts in the age of AI. Working with AI LLMs is like having an infinite team of analysts that can provide instant answers on any imaginable topic (again and again). With their help, projects that used to take weeks can now be completed in hours. But where does this leave analysts without experience worldly experience needed to get the most out of AI? How can they hope to make the best use of this incredible resource?

As we stagger into a new era, analysts must adapt and evolve alongside AI LLMs. Instead of being replaced, their role transforms into one of guiding and augmenting the capabilities of AI. We must train analysts with invaluable domain expertise, critical thinking skills, and the ability to ask the right questions. Then, they can direct AI LLMs, provide context, and interpret the outputs in a meaningful way. To some, this is going to seem like wasted effort, but we must consider this our succession plan for the industry.

While AI LLMs have an awe-inspiring capacity for knowledge, we must be aware of their tendency to produce generic responses. By incorporating human expertise, directing AI with specific frameworks, and guiding the modelling process, we can unlock the crazy potential of these models. While we run headlong into AI, we must maintain a discerning eye, strive to extract meaningful and tailored insights that drive innovation and retrain our teams so they can feel valued and ready – not antiquated.

AI is a tool, but we have not seen a tool like it since the ‘invention’ of fire. It’s our responsibility to wield it to the results we want – for our clients and our teams. 

This post was entirely written by Chat GPT under my guidance.