AI agents took the stage at this year’s Dreamforce and Inbound User conferences.
“This will be remembered as the year of AI agents when we look back on it in years to come,” stated Dharmesh Shah, CTO of HubSpot and co-founder.
“The only thing we’re going to do at Salesforce is AgentForce,” CEO Marc Benioff declared. (Goodbye, Customer 360 and Data Cloud; I hope you enjoyed your time in the limelight.)
The same focus sucked the energy out of both pep rallies, and many participants reported being disappointed by the activities. The commonalities between Dreamforce and Inbound stem from the shared characteristics of the many generative AI models. comparable models generate comparable advances.
Salesforce and HubSpot are correct about the necessity of agents. Why this is true exemplifies the issue affecting the whole genAI sector. A situation that presents an amazing chance for marketers.
What is an AI Agent?
An agent is software that uses AI and tools to complete a multi-step task.
According to Chris Penn’s must-read blog post: “If this seems like an app, it is. “‘AI Agent’ is just fancy, expensive language for a self-driving application.”
They are best suited to repeated work with predictable consequences. Things like generating reports from often arriving or being shopping assistants, pricing optimization, consumer-facing chatbots, and customer service.
“A lot of people think AI Agents are just chatbots, in the same way, they think of ChatGPT as just a blog post-writing tool,” Penn said. “They can do that. However, utilizing it just for that purpose is like bringing a Harrier [VTOL combat plane] to the grocery store. It can do that, but it is capable of much more.”
To the Prompt Store!
Fortunately for most marketers, several organizations provide low-code/no-code options to develop agents using pre-built modules. Salesforce’s Agent Builder and HubSpot’s Agent are two such examples (Dharmesh Shah, “Agent.AI is the premier professional network for AI agents. It is also the exclusive professional network for AI agents.”
So, cheers for the agents. The only incentive to pick one agent creator over another is if you are already invested in the company’s ecosystem. The challenge for AI startups is that most customers see little difference between the solutions that enterprises spend hundreds of billions of dollars on.
According to experts, the most recent ChatGPT and Gemini models differ from one another. One of them can accomplish things that the other cannot. However, only sophisticated, powerful users must or will notice the distinction. Furthermore, these systems catch up rapidly, so the advantage is unlikely to last long.
Is the Exuberance Rational or Irrational?
AI is today considered a commodity by the majority of consumers. When a product becomes a commodity, one brand is equal to another, with price being the sole distinguishing factor. That is great news for those who utilize AI, but it is negative news for the AI sector.
“We estimate that the Al infrastructure build-out will cost over $1 trillion in the next several years alone, which includes spending on data centers, utilities, and applications,” said Jim Covello, Goldman Sachs’ top technology analyst, in a now-famous investment brief regarding AI. “So, the crucial question is: What $1 trillion problem will Al solve?”
VisiCalc’s spreadsheets made PCs indispensable in business, but AI lacks an analogous killer tool. It can accomplish a variety of astonishing tasks, like automating procedures, detecting patterns in massive data sets, and producing springboard pictures and words to greater ideas. However, enhanced efficiency will never be sufficient to justify the cost of AI.
Fortunately, the use cases with the highest ROI are generally marketing-related. If you haven’t already joined the AI bandwagon, do so now. Take advantage of the hundreds of billions of dollars that other people are investing to make your work simpler! Do it now, before investors start asking annoying questions like “Where’s my money?”
Source- Martech
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