In Forrester’s 40 years, we’ve rarely recommended that customers move quickly to build new technologies. We especially recommend cautious experimentation until the technology matures and the vendor landscape rationalizes.
We’re breaking that rule with Generative Artificial Intelligence (GenAI). We believe you should move now.
It’s not crypto and it’s not blockchain and it’s not metaverse. Crypto was for speculators; Blockchain was for programmers; Metaverse was for gamers. This is the biggest technology/business change of my lifetime, and if you’re in your 40s, it’s probably one of the two or three biggest changes. your Over the course of a lifetime this change will lead to extinction for many, but opportunity and growth for many more. Position yourself not to be a victim. Position yourself to win.
For my entire career, going back to 1979, I have been told that artificial intelligence is the “next big thing” and that “next year, it will come and change everything.” It wasn’t, and it never did.
In the technology industry, big changes are hard to predict. The elements may be visible, but it is impossible to see when they combine to form something new. Years ago, Forrester noted that technological change can appear sudden, abrupt, and out of the blue — like a thunderstorm on a hot summer’s day. You’re out in the sun in the morning, go inside for lunch, and come out to lightning and rain. Tech thunderstorms come with sneaking surprises.
What triggers these tech thunderbolts? They are usually ignited by a fundamental change in the user interface. The PC thunder started in 1982 with MS-DOS – an easy-to-use and accessible personal computer operating system. In 1994, the Netscape browser suddenly entered the World Wide Web. Steve Jobs’ app home screen, the heart of the iPhone, opened the door to smartphones in 2007.
The next user interface change to generative AI was OpenAI’s ChatGPT prompt, which became available in November 2022, exactly five years after researchers defined the technology. This simple and easy way to query large language models galvanizes users. Theory turned to reality and storms ensued. If you haven’t tried it, go here.
What is this thing?
Here’s my simple definition: Generative AI enables humans to converse with large piles of data in their own language and create new content from that data.
I have a life insurance policy and every few years, my broker sends me to review the policy. I dread that moment because I don’t understand insurance — I find it opaque and boring. But what if I could communicate my strategy?
“How much have I paid into the policy?”
“If I die today, how much will the beneficiaries receive?”
“How much will I get if I cash the policy today?”
“Can I change the beneficiary?”
“Yes you can. Do you want to do it now?”
“Yes, change the beneficiary from A to B.”
“Well, we’ve made that change. Do you want me to send you a revised policy?”
“Yeah, that would be great.”
The world is filled with huge piles of data that humans either don’t understand or don’t want to read or don’t have time to read. With genAI, they can interact with that data and get what they need in a form customized to them. This is a huge thing that will fundamentally change how knowledge is created, distributed and consumed.
Impact one: No more web as we know it
There is no bigger pile of data than the web. For 30 years, we’ve spent our lives sifting through the rubble in search of answers. The web has always been a simple mess, with poorly designed pages, confusing sites, non-sequitur graphics, and buried data. But it’s all we have, so we’ve used it for 30 years.
Generative AI will change much of the web. Instead of going to Bank of America’s website to look up balances, credit card transactions or mortgage payments, you go to your bank’s big fat prompt box and start a conversation. Behind that prompt will be your bank’s “content” — a constantly updated generative big language model that answers your questions and dynamically creates graphics and charts to help you understand what’s happened to your money. The result will be faster service, on-the-fly customization, an improved experience, and a more informed and satisfied customer.
What will this new world look like? You type www.taylorswift.com and go to the site. That won’t change. But what you’ll find there will be very different from the old web. Yes, there will be some artistic pictures from the latest tour. But the primary experience will be through a “talk to teller” prompt box, where fans can buy tickets, buy merchandise, find out tour dates and get the latest videos, all through conversation. And fans will speak to the “Taylor Language Model.” These personal conversations with “Taylor” will be driven by models trained on the artist’s lyrics, interviews, statements, diaries and proprietary content.
The age of data discovery is in its twilight. The age of conversation with data is dawning. Yes, the web will still be around (many will still want to search and read). But a more convenient and faster genAI experience will overload it.
Impact Two: The Death of Google
The decline of the web has rung Google’s bell. Why are we all on the web search treadmill, being given a bunch of websites and then reading through those websites hoping to find an answer? Because Google gets paid every time you search for a website. The company wants us on this treadmill because 80% of its revenue comes from selling Google ads.
But generative AI will shut us down.
I recently boarded an American Airlines flight from Boston to Dallas, connecting Austin. When the pilot announced that four of the tires on our plane needed to be replaced (they were new to me after flying millions of miles), we were all hooked. I was nervous because I wanted to be in Austin that day. I quickly pinged chatgpt with this question: “How long does it take to change a tire on an Airbus 319?” And I immediately got this answer: “About 30 minutes.” So I did the math: 4×30 minutes means two hours I won’t make my connection. I quickly booked the last seat to Dallas on another carrier. Five minutes later, the pilot came over the intercom and said, “It will take two hours to change the tire.” I was saved by generative AI. Conversely, if I had Googled my question, I would have been thrown into a pile of websites that I would have had to sift through. Would I have skimmed through the 500-page A-319 repair manual? Maybe.
Generative AI will end the maddening game of searching the web for pages that may or may not give us answers. Bypassing Google and Bing will give us faster answers. What will happen to the ad word model? A new advertising paradigm will undoubtedly emerge — AI woven into the conversation.
Effect Three: Trust as a Business Weapon
Will consumers trust generative AI? Not if it produces what Forrester calls “coherent nonsense.” If companies push unfiltered and inaccurate generative AI content at unsuspecting consumers, they will lose share, brand currency, and buyers.
This means people are still in the picture. As companies deploy generative AI, they need to constantly monitor and ensure that it is providing valuable information, not illusions. In that context, this is an “Iron Man” moment, not a robot moment—an opportunity to put workers in “suits” of technology to better serve customers. As long as the customer knows that a man is in that suit, trust will build, because people trust people.
And that will happen because employees are relieved of repetitive tasks, freeing them up to devote high-quality time to their customers (such as answering the same question over and over again). I’m going to coin a new term here: “Human AI,” which combines the quality and speed of digital with just the right sprinkle of human connection and intimacy.
There will be fewer human touch points, but they will become critical moments of truth.
Now is the time. Companies and leadership teams can’t wait. The opportunity is too significant, and the learning curve too big to ignore — jump on it right away. Begin the process of transforming your large piles of data into models that your customers can interact with.
We recommend that companies appoint an executive team member to lead artificial intelligence. Going too early will be too technical, so we advise that the CIO or Chief Digital Officer run the point. And since much of the generative AI content will be used to improve the customer experience, the CMO should be a close partner to the CEO.
Welcome to what Ted Schadler at Forrester calls “The Intelligent Century”. Here are links to Forrester material that can give you more of the basics (with accuracy if you’re not a client):
This post was written by CEO George Colony and originally appeared on here.
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