The AI-Driven Insights Dilemma: Balancing Automation and Expertise

I recently found myself in a fascinating conversation with a new acquaintance about the role of artificial intelligence (AI) and self-service tools in our industry. It’s so rare to meet insights people ‘out in the wild,’ so needless to say, it was a joyfully geeky conversation. As we discussed, it's clear that these technologies are increasingly being applied to insights work - but what does this mean for the future of our profession?

On one hand, AI is simply another tool in the toolbox. It can help us process large datasets faster and more efficiently, identify patterns and even generate initial hypotheses. And let’s face it: who doesn't love having an extra pair of hands (or rather, algorithms) to take some of the grunt work off our plates?

On the other hand, just because we have these tools at our disposal doesn't mean they can replace our expertise entirely. To truly get value from AI and self-service insights, we need to be, and to consult, subject matter experts who can understand the output and translate it into something actionable.

The UX360 conference highlighted this very debate. One side of the discussion hailed self-service tools as a liberating force for insight managers. They argued that these tools enable us to focus on higher-level questions and provide more nuanced insights to our stakeholders.

But the other side was more cautious. They pointed out that with great power comes great accountability - if we're relying solely on self-service tools, who is ultimately responsible for the accuracy and validity of our findings? And what happens when these algorithms make mistakes or produce misleading results, e.g., hallucinations.

As I listened to this discussion, I couldn't help but think about my own role in this ecosystem. As a researcher/data analyst, I believe that we need to be advocates for using AI and self-service tools judiciously - not as replacement for our expertise, but rather as tools that can enhance our work. I’m a bit of a geek so I’ve tried to find ways to incorporate it into my work. For me, though, the old adage still holds — trust but verify.

As with all things, we need to strike a balance between automation and expertise. We should be embracing these new technologies with open arms while ensuring that we're holding ourselves accountable for their output.

What are your thoughts on this topic? Do you see AI and self-service tools as friends or foes in the insights profession?

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