The thrilling and terrifying power of AI

Generative AI, says Shelly Palmer, is a turning point in technology: “If you are not terrified by this … if you’re not excited beyond anything you’ve ever seen before, you don’t know enough about it.”

An interview with Shelly Palmer by Paul Feldman, Publisher helly Palmer believes that if you invest a little time in learning how to use generative AI in your business, your staff will immediately become 5% to 25% more productive. Palmer is professor of advanced media in residence at the Newhouse School of Public Communications at Syracuse University and CEO of The Palmer Group.

Named LinkedIn’s Top Voice in Technology, Palmer covers tech and business for Good Day New York and is a regular commentator on CNN. His latest book, Blockchain — Cryptocurrency, NFTs & Smart Contracts: An executive guide to the world of decentralized finance, is an Amazon No. 1 Best Seller. Palmer spends a lot of his time learning about generative AI, following its lightning-fast evolution, and providing insights and practical advice to the Fortune 500 business world. The insurance and financial services industries are already using AI to some extent. Generative AI, though, has just changed the stakes. In this interview with InsuranceNewsNet Publisher Paul Feldman, Palmer warns that you must adopt generative AI as a tool, or your business may quickly fall behind — and maybe even perish.

Paul Feldman: What do you think life insurance agents and financial advisors should know about AI? Should they fear it?

Shelly Palmer: I think anybody with half a brain should be scared out of their wits. If you’re not scared out of your wits, you don’t know enough about it. That said, AI is here to stay. There was a time before generative AI hit the consumer zeitgeist. And a time after. It’s like there was a time before the internet. And a time after. There was a time before generative AI. And a time afterward. This technology is so deep, so pervasive and so capable that those who use it best will have an immense early competitive advantage.

The playing field will ultimately level because those who are not good at this will perish. Not languish — perish. And those who are good at it will fight it out. Ultimately, the AIs are going to be fighting it out, but that’s for later in the story.

There are a couple of different ways to look at this. The first way to look at it is that throughout history, productivity has been the key driver of economic success. The more productive you are, the more economically successful you are. It’s that simple.

In, let’s say, about 45 minutes, I could train everybody who sits in front of a terminal in your entire organization to properly prompt the commercial-grade version of ChatGPT Plus. At the end of that 45 minutes, every single person who was in that seminar would be between 5% and 25% more productive. That will directly equate to the bottom line. You’re going to make more money, create more value, grow your business.

Feldman: What are some examples of how AI could make a business more productive?

Palmer: Let’s say I have three Excel spreadsheets. The first one starts off with first name in the first column, then last name in the second column, then company, then title, then email. And the second sheet starts off company title, email, last name, first name. And the third sheet starts off company title, first name, last name, email. And you need to make that into one spreadsheet. Ten seconds after putting that request into any of the GPT engines, you get out the file you want in CSV format.

So, something that took you 20 minutes, or took your admin 20 minutes, now takes 10 seconds. You have 20 minutes of paid time back. What will you do with it?

You have a meeting on Zoom. Somebody is taking notes. They’re going to summarize that meeting.

They’re going to have action items in bullet points. There is probably a solid 30 minutes of someone’s time plus the 45 minutes of the meeting. In the world we live in now, that transcript comes out of Zoom, goes directly into GPT-4, comes out of an autonomous agent, fully finished, in an email sitting in a draft folder for you to approve and send out.

What was 20, 30, 40 minutes of somebody’s time is now a couple of seconds and your approval. How many times would that be replicated throughout your organization or throughout the business world?

On the high end of the spectrum, we go from conversational AI clients like ChatGPT and like Bard, like the interface on Bing, which actually sits over GPT-3 or GPT-4, and OpenAI through Microsoft. We go to what’s known as autonomous agents. Autonomous agents are scripted AI models. Their job is to run as many different AI models as they need to accomplish your goal. So rather than learn to break a problem down into individual tasks so that you can ask ChatGPT to do your work one task at a time, instead, with an autonomous agent, you set your goal.

So, let’s pretend we’re researching something. We’re going to research pet insurance, and what we’re going to do is we’re going to say, “What are the top five most pet insurance-friendly dog breeds, and why would I want to recommend them to my clients? Which breeds live the longest? Which live the healthiest lives? Make me a table and cite your sources.”

The goal of doing that in a chat client will take you 10 or 15 minutes to work through all the parts of the problem. And the big chat clients, the commercial ones, have only read the internet up to 2021, so you don’t have current information. With an autonomous agent like Auto-GPT, Godmode, AgentGPT and hundreds of others that have been coming out — there’s literally an app a day coming out across the whole landscape — you give it a goal, and the goal would be “Please do comprehensive research on the five most family-friendly dogs that I can recommend to my clients with the best breeders in the area.” That’s all you’d tell it.

It would go out to the internet, it would cite its sources, it would go to the American Kennel Club, it would go wherever it has to go, it would show you its entire process. The agent would do it all for you. You’d walk away, go get a cup of coffee, and when you came back, the research all would be there.

Now, that’s going out to the internet. Another way you could use an agent would be to say, “I want a comprehensive summary of all of the policies and programs I presented to and sold to my clients this year, for a year-end summary. I also want to know what they were closest to on my pipeline and what I need to do to get them over the goal line.” That’s the goal for the agent. you train AI to help you — maybe even when you’re not there with the client directly?

That’s a couple of days of research with you and an assistant — or a trip to the coffee machine and back for an autonomous agent. That’s the kind of productivity we’re talking about. To say nothing of the generative tools that would allow you to build the PowerPoints from scratch based on demographic knowledge or knowledge from your customer relationship management system.

Palmer: That’s the ultimate end of this. We’re working on this for almost every client — some kind of autonomous agent that is going to do all this work. At that point, it is your employee; it’s truly a co-worker in your agency or in your company. That requires a feedback loop mechanism that does not exist, al-

So, there isn’t any area of the insurance business that won’t be impacted by this. Strategies for actuaries, strategies for mitigation of risk — down the list. Playbooks and program lists and operations manuals for your clients, compliance manuals, compliance checklists.

Any process where you ever sat down to enumerate any workflow for internal or external use will be done faster, cheaper, more efficiently, more productively by these tools. There is literally nothing in the insurance business other than taking someone out to lunch this won’t do better than you will.

Feldman: I think one of the things that has become big in the insurance industry is a program such as Copytalk. Advisors and agents are either recording their client conversations or they’re recording their notes. They’re in their car, they call it up, and that’s generating a text summary.

Our average reader has about 200 or 300 clients. Some have 5,000 clients and more. They’re doing all these presentations and conversations and transcribing them for compliance purposes. How do though the people at OpenAI have said they’re working on ChatGPT for business and GPT-4 for business, and that will include a mechanism for uploading your own data sets.

Feldman: What are some ways an insurance agent or financial advisor could best use this in their practice today?

Palmer: I think first off, productivity increases. The second thing is you can get good at automating some processes that used to take a lot of time. If you wanted to do a compare and contrast for clients, these are tools that do those kinds of analysis extremely well and lay out their thought processes.

To automate sales pitches, to automate any kind of go-to-market materials, or to take the go-to-market material that your big carriers are giving you and turn it into something that’s customized for clients based on the CRM — I think that’s really the magic here.

Feldman: Let’s say you have financial advisors and insurance agents who have consistently held seminars. If they’re doing two or three a week, and they do it for five or six years — or whatever that period is — could AI tell them what their conversion rates are, what their closing ratio was? Maybe tell them when the optimal time is to follow up, what’s the best email to send? With CRMs today, you collect a lot of data, but a lot of people aren’t utilizing that data, aren’t making it actionable.

Palmer: You’re 100% right. We collect data, but you need to make it actionable. Most people do not have the tools to make the data actionable. The way that most people would use Salesforce or a CRM system like HubSpot when they’re talking to someone is they would see their last notes: “How was your trip to Bali with your wife?” and “So last time we were talking about cyber insurance, where’d you guys land on that?” That’s how you would use it, and you might go back a little bit further or review some of the policies they already have. You might even farm it a little bit for some metadata to send a bulk email, but that’s not the same as pulling real insights from the data that you collect.

We train the AI, but the AI is training us. Once you start to get familiar with the kinds of insights that you can gather, you’re going to collect different data because it will help you do better.

Feldman: It’s amazing how in the last six months, the whole world has changed, and that’s just from a consumer perspective.

Palmer: We haven’t even started to talk about the way they’ll use this for advertising, and building custom ads, and social selling. So, if you tend to use the internet, if you tend to use social media, if you are someone who advertises on Twitter or LinkedIn or Facebook or Instagram or Snapchat, you can use it to build out these programs. It also does a really nice job of responding. You can give it a range of responses, and you can have it automate the responses if you want to keep active on Twitter or LinkedIn. There’s just no end to how you can use this.

People at Adobe just came out with Firefly. I would say within just a few months, Midjourney will have an application programming interface, and it will handle text better.

And Canva already has incorporated some AI into their social art tools. So right now, for someone who runs an agency, go look at Canva and see how you could automate your news items that you put into LinkedIn or Facebook stories or Instagram stories or in a carousel.

Firefly ultimately will be the Adobe answer to that, which will be the higher-end, more robust version, although Firefly is amazing. There’s a video company called Runway, which does browser-based video editing. It’s spectacular. If you were doing production artwork and promotional materials, there’s a world of these tools out there.

There’s a website called Futurepedia.io. I believe they have created the largest, most comprehensive database of emerging AI tools. They haven’t had a chance to vet them all, so you go there at your own risk. What I do like about Futurepedia, though, is that it is a comprehensive list. You can go there and see what’s new.

You need to use this every day in your business. You also must go to their terms of service and check the box that says they’re not allowed to look at your information for quality assurance purposes, so that it is protected. The best thing you can do is reach out to their sales department, get a commercial API for your business, and build your own chat client or your own interface sitting above GPT-4. And the reason for that is that then, by contractual agreement, they can’t look at your data, so your data becomes your own.

Privacy and security are important here, but for every purpose that most people would use ChatGPT Plus, you can just go check, “You can’t use my data for quality assurance.” And then your data is yours.

These models don’t learn from you. They don’t remember; they have no memory. You will keep a separate chat for each individual thing you’re doing. So, client A gets their own chat, client B gets their own chat. It’s costly because those chats get longer. The model, because it has no memory, must read it every time. So, the best practice is to have an individual chat for each task that you’re trying to accomplish or each client individually.

Feldman: One of the things that’s an issue right now is what are called AI hallucinations. Hallucinations are when AI will literally just make something up. Is that just something we must accept for now and make sure we verify everything? Will AI get beyond the hallucinations at some point?

Palmer: It’s a great question it’s an important question. There are several different solutions. The main solution is you must bring a lot of subject matter expertise to both the input and the output. The better you are at your job providing input, the better ChatGPT will be at helping you do your job.

Second, this concept of embedding and context injection — creating your own database that restricts what the model will use as input — will help curb hallucinations dramatically. Third, human beings have to understand that the conversational AI interface was specifically built to trick you into believing you’re talking to a human, and so people immediately fall into that trap.

The evolutionarily stable way for human beings to interact with one another is called the “default to trust.” The default to trust is that until you prove yourself not to be trustworthy, I’m going to trust you.

The only evolutionary stable strategy for human beings to interact with large language models and artificial intelligence is a default to distrust of the machine. You must immediately assume 100% of what you’re reading is nonsense, and if anything feels like nonsense, you ask about it.

Feldman: So how do we get better at that? Everything that you do should be reviewed if you’re going to use ChatGPT. Content creation is one thing that is very important for insurance agents and financial advisors. So how much of it do we trust? How much do we verify?

Palmer: If you bring more expertise to it, you will get more out of it. But even if you don’t bring anything to it, you’re still going to get something out of it. The hallucinations problem isn’t going away anytime soon. Nobody really understands why that is. There’ll be some guardrails put up there. This is early days.

If you go to shellypalmer.com and subscribe to our newsletter, we will try to stay on top of it. But more importantly, you need to stay on top of it however you can. And there are lots of newsletters out there. There are plenty of videos on YouTube. There’s a lot of reading to be done. Nobody wants to have to learn something new every 15 minutes, but right now, you must learn something new every 15 minutes.

You must do this, because if you get this wrong, someone’s going to basically be able to take your business away from you.

Feldman: It’s either you surf it or you get crushed by the wave.

Palmer: Yes.

Feldman: Where are we going to be in one year from now with AI?

Palmer: No idea. What I do know is that there will be a catastrophic AI event sometime in the next 12 months. I don’t know what it’s going to be. Stock market crash, airliner forced down by misinformation, something horrifying. It’ll get in front of Congress, and we’ll have a little come-to-Jesus moment, and that’s going to sober everybody up. That’s my prediction. Something terrible is going to happen because no one knows — we’re literally standing knee-deep in gasoline and we’re playing with matches, and I have no idea where this is going.

If you are not terrified by this, you don’t know enough about it. If you’re not excited beyond anything you’ve ever seen before, you don’t know enough about it. Those are just two emotions that generally don’t come together at the same time.

Maybe the only other time I’ve ever felt this way was only for a few seconds. I was honored and lucky enough to jump out of an airplane with the Golden Knights, which is the Army’s crack tandem skydiving team. And they took me up to 10,000 feet, and they strapped me to a young man I entrusted my life to. The two of us, strapped together, jumped out of the airplane.

I had never been more thrilled and more terrified at the same exact time in my life. That first 15 seconds — when you are just falling through the air from 10,000 feet, abject terror and you could taste the adrenaline in your mouth — that’s how I go to work every day now.

Insurers optimistic about hiring, revenue

Areas Where Insurers Plan To Add Staff

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Insurers are showing hiring optimism, as 67% of them have plans to increase their staff during the next 12 months, driven by the property/casualty segment at 69%. In addition, 79% of companies expect to grow revenue during the next 12 months. This is according to a study by The Jacobson Group and Ward, part of Aon plc.

In addition, 93% of life/health companies expect an increase in revenue, and 50% of the companies stated that change in market share will drive their expected revenue changes. Thirty-five percent also cited pricing factors.

The primary reason companies plan to increase staff during the next 12 months is an expected increase in business volume, the survey said. More than two-thirds of companies (37%) listed this as the primary reason to hire, followed by areas being understaffed.

In addition to these plans for growth, 10% of companies are planning to decrease their number of employees. When it comes to reductions in headcount, 8% of companies report that reorganization will be the primary reason for this activity during the next 12 months.

Nearly half (42%) of all advisors expect the impending recession to be short and shallow, beginning and easing gradually, while under a quarter (23%) expect a significant and prolonged market downturn marked by stagflation and instability.

4 IN 10 INVESTORS SAY WE’RE IN A FINANCIAL CRISIS

Is this a financial crisis? Four in 10 investors said they think so in a recent Nationwide Advisor Authority study. Three in 10 (30%) believe the U.S. is approaching one, and only 36% are confident that they will survive the next financial crisis despite living through many prior episodes.

Survey respondents say financial crises feel more like an inevitability than a possibility. One-fifth (20%) of investors expect to face two more financial crises in their lifetime, and nearly half (43%) expect to face three or more. In addition, many are worried that their finances will not survive the next market downturn, with nearly 4 in 10 (39%) investors indicating that after living through a previous crisis, they are more nervous about their ability to protect their finances.

As investors across older generations rely on previous lessons learned, many are bracing in anticipation of an economic downturn. For example, 38% of Gen X and 29% of baby boomer investors expect a prolonged period of severe downturn marked by stagflation and instability. What’s more, they don’t expect this to be the last crisis they live through. Twothirds (65%) of Gen X and almost half of baby boomers (48%) expect to live through at least two more financial crises in their lifetimes.

Taylor Swift Questions

‘UNREGULATED

SECURITIES’

Singer and megastar Taylor Swift decided to “shake it off” when offered the opportunity to endorse FTX. Swift is the lone celebrity pursued by disgraced cryptocurrency developer Sam Bankman-Fried who asked the right questions about FTX, an attorney suing SBF said.

“[She] actually asked that, ‘Can you tell me that these are not unregistered securities?’” Florida attorney Adam Moskowitz said. Moskowitz filed a November