This year Dream Strength And Incoming user conferences were all about AI agents.
“When we look back on this event in a few years, you will remember it as the year of the AI agent,” said HubSpot co-founder and CTO Dharmesh Shah.
“The only thing we’re going to do Sales force is AgentForce,” said CEO Marc Benioff. (Goodbye Customer 360 and Data Cloud, hope you enjoyed your time in the spotlight.)
Having the same goal sapped enthusiasm from both pep rallies, and many attendees said they were disappointed by the events. The reason for the similarity between Dreamforce and Inbound lies in the similarities between the different generative AI models. Similar models result in similar innovations.
Salesforce and HubSpot are right about the importance of agents. Why this is true also illustrates the problem facing the entire genAI industry. A problem that presents a great opportunity for marketers.
What is an AI agent?
An agent is software that uses AI and tools to achieve a goal that requires multiple steps.
HAS Chris Penn quoteThe must-read blog post: “If this sounds like an app, it is. “AI Agent” is just a fancy and expensive language for a standalone application.
They are best suited to handling repetitive tasks with predictable results. Things like reporting on regular arrivals or the role of sales assistants, price optimization, consumer chatbots and customer service.
Dig Deeper: How to build interactive apps with generative AI
“Many people think of AI agents as just chatbots, the same way they think of ChatGPT as just a blog writing tool,” Penn further quotes. “Yes, they can do it. But using it just for that purpose is like taking a Harrier (VTOL fighter jet) to the grocery store. He can do that, but he is capable of so much more.
To the quick store!
Fortunately for most marketers, many companies offer low-code/no-code ways to create agents through pre-built modules. Among them are Salesforce’s Agent Builder and HubSpot’s Agent.AI (Dharmesh Shah: “Agent.AI is the number one professional network for AI agents. It’s also the only professional network for AI agents.”).
So, yes for the agents. The only reason to choose one creator agent over another is if you are already involved in that company’s ecosystem. Therein lies the problem for AI companies: for most users, there is no difference between the products that companies spend hundreds of billions of dollars on.
Here’s an example: I primarily use AI to generate article summaries to post on LinkedIn. My choice is Perplexity, with Gemini as a backup. For what? Perplexity can find the article as soon as it is published, while Gemini needs about five minutes. Other than that, the results are indistinguishable. They both add false information or give me a summary of a non-existent article at about the same rate. When this happens, I try the other AI. When they both suck, I wait a bit and try them again.
Or look at the illustrations here and above. One is DALL-E 3HD, the other is OpenAI HD and the fact that I can’t remember which one says all you need to know.
Experts tell me that there are differences between the latest ChatGPT and Gemini models. One can do things the other can’t do (I can’t remember which one does what). However, only experienced and experienced users need or will notice this difference. Additionally, these systems catch up very quickly, so this is unlikely to be a long-term benefit.
Is exuberance rational or irrational?
AI is now a commodity for most users. When a product becomes a commodity, one brand is as good as another and price is the only differentiator. This is good news for AI users, but very bad news for the AI industry.
“We estimate that building Al infrastructure will cost more than $1 trillion over the next few years alone, which includes spending on data centers, utilities, and applications,” wrote Jim Covello, chief technology analyst at Goldman Sachs, in a now famous article. investment case on AI. “So the crucial question is: What $1 trillion problem will Al solve? »
Dig Deeper: How to use ChatGPT to simulate martech tools and marketing strategy
VisiCalc’s spreadsheets have made PCs essential for businesses, but AI lacks an equivalent revolutionary application. It can do a lot of awesome things: automate processes, find patterns in gigantic data sets, and generate images and text as springboards to better ideas. But increased efficiency will never be enough to justify the price of AI.
Fortunately, the use cases offering the best return on investment are mainly related to marketing. If you’re not already on the AI train, get on board. Take advantage of the hundreds of billions of dollars others are spending to make your job easier! Do it now, before investors start asking pesky questions like “Where’s my money?”
