Smarter Decisions can lead to Product Growth, Uptick in revenue, Market capture and Business Growth. Would you recommend using Generative AI to drive decisions?
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With generative AI, patterns and opportunities can be uncovered that human intuition alone often overlooks. When used correctly, it can not only accelerate decision-making but also offer creative solutions that provide real value. However, it’s crucial to ensure that the technology remains up-to-date and that various approaches are considered.
It's similar to hardware: no one wants to rely on outdated technology. You want to stay current and use the latest hardware. If your computer starts slowing down, at some point, you'll replace it. The same logic applies to AI tools.
That said, the human factor remains key. The person using the technology must always assess how much value it truly adds. The principle is: leverage the benefits, but keep control as the final decision-maker.
Drive decisions - no. Impact, shape and inform decisions - yes.
Generative AI can provide the framework for decision-making by quickly gathering and analyzing data, identifying trends, and generating insights without the time traditionally required to do so.
Just as research and reporting has provided the foundational building blocks for a person or organization to make these decisions, AI accelerates this process. Yet, the strategic positioning of these building blocks and the thoughtful consideration of the insights given remain essential.
AI is a tool to enhance our capabilities, but human expertise and strategic thinking are still paramount.
Decisions Generative AI Can Support:
Real example of effective usage: Amazon uses a generative AI model to create personalised shopping experiences. The model analyses user behaviour, purchase history, and preferences to generate product recommendations. For example, if a person recently bought a hiking backpack, the system might suggest hiking boots or camping gear.
What we want from Gen AI usage, in general: Increased Revenue by personalised recommendations , customer retention by accurately predicting and fulfilling customer needs, operational efficiency by AI-driven recommendations reduce the need for manual curation, etc.
Though, there are risks: Bias risk - if the training data is biased, the recommendations can miss the real needs; Lack of transparency - difficult to understand how decisions are made, data privacy - AI often requires large amount of data, which is directly linked to user privacy and data security.
But most importantly, imagine healthcare industry, in addition to privacy issues and biases, there is a huge risk for clinical decisions errors: if the model is not well-validated, it can lead to incorrect diagnoses, treatment plans, or drug recommendations endangering patient safety.
So, it really matters which industry at which level decides to use it.
Generative UI can be a helpful starting point, but it's important to rely on your own judgment and experience to make decisions that align with your product objectives, revenue targets, and market demands.