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Ever since the launch of ChatGPT in November 2022, the ubiquity of words like inference, reasoning and training-data is indicative of how much AI has taken over our consciousness. These words, previously only heard in the halls of computer science labs or in big tech company conference rooms, are now overhead at bars and on the subway.
There has been a lot written (and even more that will be written) on how to make AI agents and copilots better decision makers. Yet we sometimes forget that, at least in the near term, AI will augment human decision-making rather than fully replace it. A nice example is the enterprise data corner of the AI world with players (as of the time of this articles publication) ranging from ChatGPT to Glean to Perplexity. Its not hard to conjure up a scenario of a product marketing manager asking her text-to-SQL AI tool, What customer segments have given us the lowest NPS rating?, getting the answer she needs, maybe asking a few follow-up questions and what if you segment it by geo?, then using that insight to tailor her promotions strategy planning.
This is AI augmenting the human.
Looking even further out, there likely will come a world where a CEO can say: Design a promotions strategy for me given the existing data, industry-wide best practices on the matter and what we learned from the last launch, and the AI will produce one comparable to a good human product marketing manager. There may even come a world where the AI is self-directed and decides that a promotions strategy would be a good idea and starts to work on it autonomously to share with the CEO that is, act as an autonomous CMO.
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Overall, its safe to say that until artificial general intelligence (AGI) is here, humans will likely be in the loop when it comes to making decisions of significance. While everyone is opining on what AI will change about our professional lives, I wanted to return to what it wont change (anytime soon): Good human decision making. Imagine your business intelligence team and its bevy of AI agents putting together a piece of analysis for you on a new promotions strategy. How do you leverage that data to make the best possible decision? Here are a few time (and lab) tested ideas that I live by:
Before seeing the data:
While looking at the data:
While making the decision:
At this point, if youre thinking, this sounds like a lot of extra work, you will find that this approach very quickly becomes second nature to your executive team and any additional time it incurs is high ROI: Ensuring all the expertise at your organization is expressed, and setting guardrails so the decision downside is limited and that you learn from it whether it goes well or poorly.
As long as there are humans in the loop, working with data and analyses generated by human and AI agents will remain a critically valuable skill set in particular, navigating the minefields of cognitive biases while working with data.
Sid Rajgarhia is on the investment team at First Round Capital and has spent the last decade working on data-driven decision making at software companies.
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