Enterprise AI Adoption Challenges: Trust, ROI, and Job Market Transformation

Key Quotes

"I thought it was great I particularly appreciated three points that he talked about one was all around this notion of clearly agents which he talked about you know these three frontier agents that he's bringing out you know that aws is launching something like an autonomous coding agent to security agent to devops I thought that was compelling because you're effectively moving finally in that direction which I think is uh you know the conversation that enterprises that we've had them with our second internal product and so obviously our own solution plays into that that was one."

Prashanth Chandrasekar highlights the emergence of AI agents, specifically mentioning AWS's autonomous coding, security, and devops agents. Chandrasekar finds this compelling because it signifies a move towards a direction that enterprises have been discussing, aligning with Stack Overflow's own product development.

"The other aspect was he used this great analogy about you know raising teenage kids and uh this notion of trust but verify and I think this is again very especially true in the enterprise where there's a lot of enthusiasm for ai agents and assistance and ai in general but the trust level still is low and for you to gain any sort of scale across enterprises you're going to need to focus on trust and again something that you know we think about at stack quite a bit with our products."

Prashanth Chandrasekar uses the analogy of "trust but verify" when discussing teenage children to illustrate the current state of AI adoption in enterprises. Chandrasekar explains that while there is enthusiasm for AI, a low trust level remains a significant barrier to widespread adoption, emphasizing the need to focus on building trust for scalability.

"And I think that it's going to be similar with ai I don't think that jobs are going to go away I think that they're going to radically change because ai is good at some things so we don't need people to do x but it's going to be bad at some things so we do need people to step in and do x on the security front there's going to be new security vectors and vulnerabilities that crop up that's going to need these type of attention and in the people that I've been talking to at the conference one of the things that I hear frequently is my job isn't going to change but that job over there is going to change and I'll even have people that are they're not directly pointing fingers at each other but it's like oh the data engineers should be worried and then I go and I talk to a data engineer and they're like no no my job is rock solid those people over there they're going to change they're going to be concerned."

Michael Foree draws a parallel between the advent of the cloud and the impact of AI on the job market. Foree believes that jobs will not disappear but will fundamentally change, with AI excelling at certain tasks and requiring human intervention for others, particularly in emerging areas like security vulnerabilities. Foree notes a common sentiment among conference attendees that while some jobs will transform, others will remain stable.

"The number one of course being ai right and so I think that combining ai with robotics is a natural question to ask and is absolutely a place where people should consider combining one thing that that limits llms today is that you have to be in front of a computer to interact with them right but the robot gets it out of that computer realm and allows it to interact with the world around it right that's that's one thing that you you can't quite do with the cloud or with data centers or the internet or so on and so forth so I think that people have been trying to interject robots and autonomous cars as an outstretch of that to interact with the actual human beings and I think that the advancements with ai in computing are going to help blend those worlds go forward so I'm I for one am really intrigued to see how robotics ai computing are going to blend the the digital and the physical space and I i think it's absolutely going to be a world right for disruption in the near future."

Prashanth Chandrasekar discusses the synergy between AI and robotics, identifying it as a significant area for investment and innovation. Chandrasekar explains that while current Large Language Models (LLMs) are confined to computer interactions, robots can extend AI's capabilities into the physical world, enabling interaction with humans and the environment. Chandrasekar expresses intrigue about the future blending of robotics, AI, and computing.

"And I think that the number of jobs in aggregate I think will continue to increase because there's only going to be more possibilities more problems to solve now that we've unlocked all this new capability so for example I was talking to a ceo yesterday the areas in life sciences he's building like a frontier lab for life sciences and this that would never have existed a few years ago in the context of what he's doing and he's like it's a complete game changer for us to have access to this kind of end to end integrated sort of tech stack for the ai capability and so that only creates new companies like that in aggregate right so overall there'll be more companies created and you're seeing that in the startup ecosystem you see that here shows a great event you know it's bustling in the startups uh and we see that on our own platform you know people are using stack overflow a lot of early stage startups who are you know building new things asking me a lot of questions on ai etc and so all those things are indications that there will just be the ecosystem will be increasing but to michael's point the types of jobs will change most likely because some of them will be automatable."

Prashanth Chandrasekar predicts an overall increase in the number of jobs due to the expanded possibilities unlocked by new AI capabilities. Chandrasekar cites an example of a life sciences CEO building a frontier lab, a venture that would not have been feasible previously, highlighting how AI enables new companies and opportunities. Chandrasekar agrees with Michael Foree that while the total number of jobs may grow, the nature of those jobs will likely change due to automation.

"The non deterministic angle is is really quite quite stressful from an engineering point of view and it's something that I'm looking to try and lean into how can the non determinism be at an asset and an advantage and so trying to box in the llm like where can we really let that grow and expand so you've got these two bimodal cases from a normal user it's so easy to use from a technical angle integrating it into my tech stack I'm seeing a lot of friction when I talk to people about when when to plug it in and how to use it properly."

Michael Foree describes the non-deterministic nature of LLMs as a source of stress from an engineering perspective, but also sees potential in leveraging this characteristic as an advantage. Foree notes that while LLMs are easy for everyday users, technical users integrating them into their tech stacks encounter friction regarding when and how to properly implement them.