INBOX INSIGHTS, August 7, 2024: Generative AI All or Nothing, Unstructured Data Analysis with AI - Trust Insights Marketing Analytics Consulting

INBOX INSIGHTS: Generative AI All or Nothing, Unstructured Data Analysis with AI (8/7) :: View in browser

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Is Generative AI All or Nothing?

Chris asked me about how to convince someone that they should use generative AI. In last week’s newsletter, I wrote about how process development is going to be critical. This week I wanted to try an experiment. Not to turn you away from using generative AI, but perhaps to help those who feel like AI is all or nothing. To write this week’s post, I used three different AI models. First, I used KatieGPT. This is the LLM we built using my voice and catalog of writing. Next, I ran the post through the Trust Insights ICP-GPT. This is the model we built using our Ideal Customer Profile. I gave ICP-GPT the post and asked for recommendations to make the post more relevant to our ICP. Lastly, I copied the post into Hemingwayapp AI editor and only used the AI suggestions for rewriting. Mostly only the AI suggestions. Some of it was incoherent, to be honest.

Here is the 99% AI-generated post:

As AI becomes part of our daily work, leadership must focus on emotional intelligence (EI) more than ever. As leaders, we must balance AI’s efficiencies with our human need for empathy, understanding, and connection.

Developing Emotional Intelligence in Leadership During the AI Era

As we embrace AI’s advancements, we must remember our teams are made up of individuals. They have unique emotions, perspectives, and needs. The tech can optimize processes and provide insights. But, we need emotional intelligence to manage complex human interactions. It helps us keep a motivated, cohesive workforce.

Here are key areas to focus on:

1. Self-Awareness

Recognize your own emotions and how they impact your decisions. In an AI-driven world, data can overshadow human intuition. So, be self-aware. It will keep you grounded and aligned with your values.

2. Self-Regulation

Adaptability is crucial. AI tools can create rapid changes in workflows and expectations. Leaders who can manage stress will set a positive example for their teams. This will foster a resilient, adaptable culture.

3. Motivation

Use AI to identify opportunities for team growth and improvement. However, intrinsic motivation – the drive from within – is nurtured by a leader’s ability to inspire. They must align team goals with individual passions and aspirations.

4. Empathy

AI can analyze patterns and predict behaviors, but empathy allows leaders to understand the context behind the data. It helps in addressing concerns, recognizing efforts, and building stronger, more trusting relationships.

5. Social Skills

Communication remains at the heart of effective leadership. Leveraging AI for enhanced data communication can improve transparency and trust. But it’s your ability to listen, resolve conflicts, and lead through influence that will ultimately drive success.

Practical Steps to Enhance EI in an AI-Driven Workplace

1. Regular Check-Ins

Use AI tools to track team performance and well-being. Also, schedule regular one-on-one and team meetings to discuss these insights. This humanizes the data and shows your commitment to their development and welfare.

2. Feedback Loops

Create systems where feedback is continuous and goes both ways. AI can help collect and analyze this feedback. But, it’s your response that shows empathy and a commitment to improve.

3. Personalized Development Plans

AI can find skill gaps and growth opportunities. But, it must tailor development plans to each team member’s career and personal goals. This approach shows respect for their unique journey and fosters deeper engagement.

4. Transparent Communication

Utilize AI to enhance data transparency. Explain how AI-driven decisions are made and involve your team in the process. This builds trust and reduces anxiety around the unknown aspects of AI.

5. Promote Collaboration

Encourage cross-functional collaboration by using AI to identify potential synergies and foster connections. Celebrate collective achievements to strengthen team unity and shared purpose.

The Balance Between AI and EI

AI is a powerful tool for efficiency and insight. But, it is our emotional intelligence that will ensure its effective integration into our workflows. By merging these two forces, we can create a workplace that is both high-tech and human-centered. As leaders, we must use AI to support our teams. We must do this while being empathetic and understanding.

By focusing on these aspects, we can thrive in the AI era. We must ensure our leadership is both effective and compassionate.

How do you balance AI and EI? Reach out and tell me, or join the conversation in our free Slack group, Analytics for Marketers!

Ok, Katie here again. The post isn’t terrible. But it’s not up to my standards of writing. It lacks personality, anecdotes that only I know, and heart. Overall, I’d give this post about a C, C+ to be generous.

I did this not to show you that you shouldn’t use AI. You should where it makes sense. I did this exercise to show those that are worried that AI will take their jobs and steal their creativity that AI isn’t you. You are what makes an AI output better. I can use KatieGPT to help generate ideas. I can use ICP-GPT, to gut check. I can use Hemingwaypp AI editor to help polish. But at the core, I have to do the work. I am the subject matter expert, not the other way around. Generative AI will and should play a supporting role in your job.

Like I said in last week’s newsletter, process documentation will help you figure out where AI fits. It may help automate whole tasks, or just parts. You are in control of it, not the other way around. If you have your feet firmly planted in the “AI will take my job” camp, read this post again. It’s not me. Only I can write like me. AI will get good, but it doesn’t know what I know or how I feel. There is a time and place for this kind of streamlined writing in my workflow. I will probably reuse this AI-generated content for something else, like a series of quick tips on LinkedIn. I’ve gotten past feeling like AI will take my job. I’m now working on where AI can better support me so I can do more high-value work.

Are you coming around to using AI? Reach out and tell me, or come join the conversation in our Free Slack Group, Analytics for Marketers.

– Katie Robbert, CEO

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In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss how to help your team embrace AI and what to do with team members who are resistant to AI adoption. Learn why the human element remains critical for successful AI implementation and how to best communicate the value of AI to your team. Discover why throwing AI at a problem isn’t the answer and how Katie uses AI to support, rather than replace, her work.

Watch/listen to this episode of In-Ear Insights here »

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In this week’s Data Diaries, let’s talk about a use case for generative AI that very few people think about: generation of quantitative data.

Now, before we proceed, I want to be clear we are doing what’s essentially a summarization task. We’re not asking AI to make net new data out of whole cloth. It can do that, but you probably shouldn’t under most circumstances.

No, instead we’re talking about turning unstructured data like text or images into structured data.

What kind of structured data? Pretty much anything you can think of. For example, take this social media post:

Black Forest Labs’ Flux model came out last week, and it’s incredible. And it runs on your laptop. It’s head and shoulders better than similar-sized models and competitive with the big paid services. It’s good enough that many of its images will pass casual inspection as “real”, like the one on this post. Gone are the days of obvious artifacts like a person with 13 fingers on one hand. Detection is getting harder. And by extension, if detection of AI content is getting harder, then the quality of AI content is improving. After all, if you can detect it easily, it’s probably also not great quality.

What could you do with this piece of unstructured text? You could count things like the number of characters, words, or sentences, sure.

You could also do things like judge readability. Sentiment. Tone. Formality of writing. Writing style. Named entities. Topics. Themes. That’s all text analytics.

What would you do with that information? This is where classical AI would step in, things that generative AI models can’t do (because it’s complex math). You might take your social media posts and their performance, have a generative model create different text analytics, and then run a regression analysis to ask, “What, if any, text features correlate with higher social post performance?”

One of the biggest challenges marketers face is understanding WHY something is working. We have basic measurements to know broadly what worked, but it’s rarely clear if it’s working because of something we did or something beyond our control.

If we use the power of generative AI tools to generate data that would otherwise take enormous amounts of time, we can better analyze the outcomes with the methods and understand what, if any, effect our efforts have.

For example, Katie and I were looking at our content recently, and we used generative AI to score every piece of content we’ve created over 6 years against our Ideal Customer Profile, our ICP. How much, on a scale of 0-100, would our ICP find any given blog post, newsletter, podcast, or livestream useful? What we found was fascinating:

By using generative AI to create the data from the unstructured data we already have, we can judge whether our content marketing strategy is effective. And thankfully, ever since we started being laser focused on content that our ideal customer profile – you – want, we’ve seen our scores go up.

What text data do you have on hand that you wish you could analyze further? Unleash the power of generative AI on it and see what your data has to tell you.

And of course, shameless plug, if you want someone to do this for you, we’re happy to help.

Here’s a roundup of who’s hiring, based on positions shared in the Analytics for Marketers Slack group and other communities.

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Imagine a world where your marketing strategies are supercharged by the most cutting-edge technology available – Generative AI. Generative AI has the potential to save you incredible amounts of time and money, and you have the opportunity to be at the forefront. Get up to speed on using generative AI in your business in a thoughtful way with our new offering, Generative AI for Marketers, which comes in two flavors, workshops and a course.

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