I was a supermom meticulously planning Disney World trips (six in about a decade) when the kids were young. The adventure began months before we hit the parks:

• ► Picking parks based on crowd data, thanks to touringplans.com.

• ► Securing prime dining reservations 180 days out at 4 am in Denver!

• ► Planning favorite rides during low-wait times and tracking schedules with my color-coded spreadsheet (see below).

• ► Scanning blogs and following influencers for Disney tips.

• ► Coordinating flights, Disney’s Magical Express bus, and grocery deliveries.

It was exhausting while juggling a full-time marketing exec job, but worth every second.

Now, I imagine AI agents handling all of this. It’s not far-fetched. Think about those Magic Bands we wore that we used to pay, get on rides, and access our rooms. Combined with our family’s profile in Disney’s system, I’m pretty sure those Magic Bands geo-track too.

That’s a goldmine of data that could be used to plan the perfect Adams family vacation. Who knows what else Disney collects?

And it’s already happening in business:

• ► HubSpot’s “Breeze” agents are creating content, managing social media, and automating customer outreach.

• ► Salesforce’s “Agentforce” is handling customer service, sales, and beyond.

These aren’t just chatbots. They’re taking action and doing real work autonomously.

But will we trust them?

We’ve been down this road before. Remember when online banking felt risky? Or when getting into a stranger’s car seemed crazy? Now, we barely think twice about Ubering.

AI agents are next on this journey of trust. The challenge isn’t just about building smarter AI, it’s about earning our trust, one step at a time.

In a previous post, I talked about the trade-offs between AI convenience and maintaining personal control. Privacy and transparency in how our data is used are critical, and we each have our own comfort level with that balance (you can check out my thoughts here: https://lnkd.in/gmFiz83A)

And for those interested, I even used AI to analyze wait times for Disney World’s iconic Splash Mountain, using publicly available data. If you’re curious about the insights, take a look here: https://lnkd.in/g4SFXF4m

My kids want to revisit Disney World for old times’ sake. If Disney offers an AI planner agent in the next few months, I’m game with caveats. I’d love to see its suggested plan, tweak it, and give the final thumbs-up.

Baby steps, Disney AI Agent. Impress me, and maybe next time, you’ll get free rein. 😉

What are your thoughts? Is the future of vacation planning or business operations in the hands of AI agents? Or will we always want that human touch for the things that matter most?

#AIAgents #ResponsibleAI #PersonalizedExperiences #Automation GrowthPath Partners

Share with AI your unique ideas and insights based on your experience and expertise. It can be just your stream of consciousness or a bunch of uploaded stickies from a brainstorming session.

Then work with AI to organize your thoughts and write a first draft. But don’t stop there.

Use AI as a thought partner, not just a tool. Go deeper. Here are some of the questions I often use with AI to challenge my thinking:

• How might this be perceived by different audiences?

• What assumptions am I making, and are they valid?

• Does this meet my goal (e.g., engaging, inspiring, thought-provoking)?

• What counter-arguments might someone have, and how can I address them?

• Is there an important perspective or insight I might be missing?

• What kind of emotional response might people have to this?

• How can we tell a story or make it more relatable?

• Would this sound natural if I explained it out loud?

Not all of these questions may apply, and some topics might need different approaches. The key is to keep collaborating with AI until you find what really makes your ideas better. Or simply start with, “Your thoughts? Be honest and unbiased.”

I put these questions to the test with ChatGPT using this post to show an example, see below.

AI offers suggestions, but we make the final call. We learn with AI, but we guide it throughout by giving it context, challenging it, offering examples, or providing feedback.

Here’s another example of how I use AI as a thought partner, https://lnkd.in/g6nKkMXT

How have you used AI beyond the first draft? What questions have helped you get the most out of it?

#ThoughtPartner #AICollaboration #ChatGPT #ContentCreation #Ideation GrowthPath Partners

Another sobering report that women are using AI less than men. [UPDATE: I originally thought that women are at par with men in the area of marketing based on the size of the bars on the chart. However, given that the numbers are not specifically called out, I’m not sure.]

See Ethan Mollick’s post on this today, https://lnkd.in/gFgUQVHc

Similarly, from an article in the Economist, it showed that women are 16-20% less likely to use AI tools than men in similar roles.

It also said that high-achieving women are less likely to use AI. The researchers suggest this might be due to self-imposed restrictions, with one describing it as a “good girl thing” – the idea that

“I have to go through this pain, I have to do it on my own and I shouldn’t cheat and take short-cuts.”

I discussed this Economist article in a previous post (https://lnkd.in/gtv9K3RE) and you can see insightful comments from many women leaning in.

Using AI tools responsibly isn’t cheating. You guide AI with your unique expertise, knowledge, and data to get the most out of it, making your work faster, better, and innovative.

For AI to benefit everyone, we need diverse voices guiding it.

I used ChatGPT to analyze its own future as OpenAI shifts to a for-profit model and key execs, like CTO Mira Murati, leave the company. This seemed like a good “Business Scenario Planning & Strategic Forecasting” use case for OpenAI’s latest model, ChatGPT o1-preview (seriously, who names these models?!)

o1-preview has better reasoning and math skills. It’s great for solving complex problems thinking through approaches step by step, like planning strategies.

So, I put it to the test. I asked it to evaluate future scenarios for OpenAI using a framework: criteria, ratings, weights, pros/cons, and reasons.

It took 27 seconds to think before giving its answer. Unlike earlier versions like ChatGPT 4o, o1-preview takes its time to give more thoughtful responses.

Below are the top three outcomes from each model. (See the ChatGPT conversations with analyses in the comments, https://lnkd.in/gGbWCEBR, including other scenarios evaluated like return to non-profit, full-profit shift, and internal collapse)

I was curious how o1-preview would react, so I shared GPT-4o’s analysis. It adjusted its top choices to align more closely with GPT-4o. I like that it can adjust based on new input.

Initially, I thought o1-preview’s improved reasoning made it the clear choice. But after seeing different results across multiple tests, I wonder if it lacks the consistency needed for strategic forecasting. Also, GPT-4o’s web browsing might give it an edge in staying current, especially in a space that’s moving fast.

I then asked Claude, Anthropic’s AI, since the ChatGPT models seemed to like Anthropic. Claude also leaned toward a merger with Anthropic, plus acquisitions by Microsoft and Google.

Looks like all three models prefer reuniting most original OpenAI execs, likely due to their focus on safety and reducing risks.

Of course, take all this with a grain of salt. These models have key limitations:

• ► Training data – o1-preview and GPT-4o are trained up to Oct 2023. Claude is trained up to Aug 2023. None have knowledge beyond these dates.

• ► No browsing – Of the models tested, only GPT-4o can browse the web.

• ► No specialized knowledge – None have insider knowledge or domain-specific expertise. (And neither do I in guiding them.)

• ► Lack of human context – Most importantly, they can’t account for human factors like desire, fear, trust, greed, and relationships, which influence real decisions.

This is just a demo of AI tackling complex problems using public data, not financial advice or predictions

Still, it shows how AI can help bring structure to decision-making. It gives us a starting point, but human judgment, expertise, and oversight are key.

In OpenAI’s case, I think the human factors will ultimately be the trump card.

What are your thoughts? Is a Microsoft acquisition inevitable for OpenAI? Or is there a better path to OpenAI’s mission of ensuring AGI benefits all of humanity?

#OpenAI #Microsoft #AI #AISafety #ChatGPTo1 #Anthropic GrowthPath Partners