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OpenAI Presence: The Rise of Real-Time AI Customer Service Platforms
The AI landscape has shifted rapidly, but a recent development is quietly reshaping customer interactions. OpenAI has introduced a new enterprise offering: a platform designed to let companies build, deploy, and manage real-time voice and chat agents for core business functions such as customer support, sales, HR, and IT. While the launch lacked viral fanfare, the implications for business operations are significant, especially as AI models now meet performance thresholds previously unattainable. Here’s a detailed look at the practical impacts and operational opportunities for organizations evaluating AI customer service platforms.
AI Customer Service Technology: Closing The Last-Mile Gap
A key theme that emerged was the transformation of AI-driven customer service from underwhelming, slow, and robotic systems into sophisticated, responsive, and contextually aware agents. Earlier implementations struggled because models often could not process real-time conversations or navigate the nuances of spoken language, often pausing mid-interaction and misunderstanding sarcasm or emotion 08:08. The latest models, such as OpenAI’s GPT Live and Real Time 2, now engage in fluid, human-like conversations and handle background tasks like database lookups and tool integrations without lag 07:58 or ambiguity.
Companies can expect these AI agents to learn and adapt through exposure to real-world scenarios, using production interactions and performance metrics to drive ongoing improvement 12:15. This means that over time, the quality of service can rise above the historical standard of long wait times and repeated agent hand-offs.
OpenAI Presence Platform: Enterprise-Grade AI Agent Management
The discussion explored the architecture of the newly launched enterprise platform. OpenAI’s approach centers on bundling not just the voice models but the full stack of enterprise tools necessary for compliant, controlled deployment at scale 18:16. Included in the platform are:
Policies and Guardrails: Admins define exactly which actions agents can take, which require human intervention, and how escalation is managed. There’s emphasis on starting with narrowly scoped tasks and explicit escalation pathways, especially during early deployments 15:34.
Simulation and Evaluation: Built-in tools allow businesses to simulate edge cases and risky scenarios before agents go live with real customers 19:49. Human operators can monitor and step in mid-conversation, ensuring oversight during critical interactions.
Continuous Improvement: Integrated with OpenAI’s Codex, the platform reviews live customer signals and automatically proposes updates that can be tested in a sandbox environment before deployment 20:03.
This infrastructure focus is designed to support responsible scaling, making it easier for organizations to transition from beta to full deployment while aligning with their compliance and quality mandates.
Voice Model Benchmarking: AI Performance for the Enterprise
A critical insight for business decision-makers lies in OpenAI’s performance on independent speech-to-speech benchmarks. The conversation highlighted that OpenAI now holds four of the top six spots in the Artificial Analysis Speech-to-Speech Index, including its new GPT Real Time 2 model 10:00. Even earlier versions of OpenAI’s models outperform Google Gemini’s current offerings 10:11.
This technical advantage matters for organizations prioritizing natural customer interactions and fluid digital experiences. The competitive landscape is shifting as Anthropic and Google invest in new real-time voice capabilities as well, but presently, OpenAI’s platform leads on both speed and conversational quality.
Practical Deployment: Organizational Integration and Internal Use Cases
One concept discussed was the practical integration of these AI agents beyond traditional customer service. Use cases extend to demand generation, claims processing, procurement, IT help desks, and HR—particularly in large organizations where scaling traditional support staff is costly and often infeasible 12:41.
Moreover, for companies that previously could not justify dedicated customer service due to scale, the technology now lowers that barrier. Internal support for large teams and personalized employee services is achievable with this infrastructure, especially when agent interactions can draw context from company data systems and maintain continuity across both phone and chat channels 12:49.
Customer Experience and Business Value: The User Perspective
Several points were raised, including evidence of consumer demand for improved AI customer service. Citing a recent study, the episode notes that 80% of consumers are willing to interact with AI-powered service tools if it means resolving issues faster and with less friction 24:08. The conversation underscores that the AI agent’s effectiveness hinges on transparent escalation to human agents, ensuring user needs are met rather than frustrated by technological barriers 23:51.
This aligns with persistent consumer dissatisfaction around traditional service channels—slow, inefficient, and often leaving issues unresolved. Businesses tapping these AI tools can differentiate by offering faster solutions, leveraging persistent records across channels, and aligning customer preference with operational efficiency.
Strategic Considerations: Infrastructure Before Innovation
A key message for organizations is the importance of internal readiness. The discussion stressed that AI-driven customer service success does not start with maximum autonomy or broad deployment, but with well-defined use cases, carefully monitored guardrails, and integration with company knowledge systems 16:03. Firms should develop their own benchmarks, focus on low-stakes, high-volume queries first, and scale up as confidence grows in the technology’s ability to handle nuance and ambiguity 16:26.
Presence, as a platform, is accessible only to organizations willing to invest in this infrastructure-led deployment path—making it crucial to evaluate internal data readiness and escalation policies before considering a launch.
Outlook: Real-Time AI and The Next Phase of Customer Operations
The conversation concluded with the perspective that AI-based customer service may represent the first widespread, consumer-facing disruption delivered by next-generation, real-time models 26:26. As the competitive field accelerates, companies with the right foundation and processes can benefit from increased consumer trust, cost-effective scalability, and access to actionable insights from every customer interaction. The technology is now mature enough for mainstream enterprise adoption, provided it’s deployed strategically and in alignment with real business objectives.
Topics Covered in This Episode:
- OpenAI Presence Launch and Industry Response
- Real-Time AI Voice Agents for Customer Service
- OpenAI Presence vs. Competing AI Voice Platforms
- GPT Live and Real-Time Model Capabilities
- Enterprise AI Integration: Guardrails and Escalations
- Multichannel AI Agent Consistency for Support
- Speech-to-Speech Benchmark Rankings and Analysis
- Deployment Challenges: Beta to Production Readiness
- Consumer Demand for AI Customer Service Solutions
- Internal and External Use Cases for AI Agents
Episode Transcript
Jordan Wilson [00:00:16]:
OpenAI announced a new offering yesterday in OpenAI presence, a service that I thought would make a pretty big splash. Yet in the first twenty four ish hours since its announcement, it's been surprisingly silent. I mean, kind of below average chatter online, below average media coverage, nothing really went viral or took off when maybe it should have. But this emerging category needs your attention. So what is OpenAI presence? Well, it's an enterprise AI platform that lets companies build, deploy, and manage real time voice in chat agents for customer support, sales, HR, and IT. OpenAI says each agent improves through real world experience. And I've thought for years that eventually one of the first big disruptions in AI would be customer service, but the real time models weren't narrow enough or fast enough or nearly smart enough. Now they are.
Jordan Wilson [00:01:19]:
And the path for disruption is almost impossible to ignore. I mean, customer service has been historically poor quality, slow, not helpful, and seemingly running on pre Internet technology, let alone pre AI technology. The other main thing worth pointing out, while anthropic has recently been grabbing headlines by pulling models from subscription, OpenAI is seemingly focusing beyond the model now. So will your company be employing customer service agents anytime soon? And might that be a good thing or a bad thing? Well, let's find out, and welcome to Everyday AI. Here's the big picture on what's new. So OpenAI has launched their new presence to automate customer service. So presence lets companies deploy real time voice and chat agents for support, sales, and internal workflows. And OpenAI says that these things just get smarter the more that your company uses them in the real world interfacing with customers.
Jordan Wilson [00:02:19]:
And right now, customer service does anyone actually like it? For me, it's almost the bane of my existence. I know I'm gonna have to, you know, get transferred six times if I have to actually call the company. Those companies that have tried to roll out voice agents were maybe ahead of the curve and the technology really wasn't ready. So I always thought that AI would be, you know, kind of fitting this, huge gap, but it was too early. But now we're actually there because if you haven't used OpenAI's new GPT live or GPT real time two models, you would not know any better. You would say, oh, any AI agent. Yeah. I've I've heard these talking to customer service.
Jordan Wilson [00:03:01]:
They're slow and very robotic. Well, that's not the case anymore. So on today's show, here's what you're gonna learn. You're gonna know what OpenAI presence actually is and why it's not the new voice model everyone assumes. You're gonna know everything that goes into building one of these agents and how OpenAI keeps it in check and how your company can too. You're gonna know the one number OpenAI is using to prove presence works and everything that number leaves out and what this could mean for your company, your team, and every customer who maybe calls in if you are using it. Alright. Welcome to Everyday AI.
Jordan Wilson [00:03:33]:
If you're new here, my name is Jordan Wilson, and we do this every day. This is your unedited, unscripted daily livestream podcast and free daily newsletter, helping business leaders like you and me keep up with everything that's happening in the world of AI. I tell you what matters, what doesn't. You use that information to grow your company and career. It's cheat code. So it starts here, but make sure you go to our website at youreverydayai.com. We're gonna be recapping the main points of today's show as well as all of the other AI developments that you need to keep in mind. Alright.
Jordan Wilson [00:04:04]:
So open AI presence. Let's get into it because I'm wondering if the customer service takeover is finally now arriving, because we saw some of these earlier products launch, you know, like, two or so years ago. It was kind of like the 2023, maybe 2024 normal AI agents launch. Right? There's all this hype behind it, but the technology, I don't think, for actual on demand agents that can help you with your work, I don't think that really arrived until, like, the past six months. So the same thing we saw with voice agents. Right? As soon as voice models became available, you you know, commercially and from the consumer side in, like, late twenty twenty three, early twenty twenty four, you know, there was already this first warning sign. Right? The the the boy who cried wolf came and said, hey. Customer service, you know, all these jobs are gonna go away.
Jordan Wilson [00:04:55]:
But it wasn't the case. The models weren't good. But now this may be different now. But first, I wanna zoom out and not just talk about OpenAI presence, and I wanna talk about the space in general. Because oftentimes, it is the competition, that ultimately drives the end product or the services that those product that those products get rolled into. And reportedly, right, we'll see and we'll be covering this tomorrow, on our, you know, Friday feature show where we go over features that are available for everyone to use. But, reportedly, we'll be getting a codex real time voice mode soon, right, that acts more like a personal assistant, like a smart AI powered Siri that actually works. Alright.
Jordan Wilson [00:05:40]:
So that would be amazing, but they're not the only company that's obviously investing heavily in voice As more and more people seemingly become more comfortable talking to or with AI, right, maybe it's because of the dictation, maybe it's because, well, now the models are actually smart enough and responsive enough that we can actually use these voice models, and people see how powerful that is. Right? Everyone's always wanted to have their own, you know, Jarvis that you could just say something to and it, you know, understands and it thinks about it, and it doesn't just give you a robotic response back. So not only maybe we be getting, a a new real time voice mode from OpenAI via codex, But also, we've seen some recent leaks that show anthropic is also, gonna be rolling out some new voice modes as well. And then, I mean, you can't forget Google and their Gemini live. So when it was announced, it was actually kind of the leader of the pack. But we know that Gemini is at least temporarily behind on getting new models, to market. Although, we did just get the, Gemini 3.6 flash. But in terms of their pro series in Gemini live updates, we haven't seen anything in a long time.
Jordan Wilson [00:06:46]:
But I would assume that whether it is part of the Gemini four that is now under pretraining or the Gemini 3.5 pro that, you know, has been delayed now for a couple of months, my assumption is we will get a new Gemini live mode. So the three big players here are seemingly starting to either invest or reinvest in the real time, voice space. Because like I said, now the models are smart enough. You can talk to a model. And kind of how OpenAI runs this is you talk to a model and it responds, and then it sends another model in the background to call tools and to search the web. And that was one of the big things that was missing. Well, number one, initially, the models were not real time and neural enough. They sounded robotic and, you know, it might have paused for a half second or a second.
Jordan Wilson [00:07:33]:
And when it comes to customer service and customer interactions, that's all you need to completely ruin it. Right? And that's why, you know, back in 2024, so many companies did not jump on this bandwagon rightfully so because the technology wasn't there. But now these models, right, they respond to you in real time, especially in the new, GBT live one and the, GBT two real time, which we'll be talking about those models and the differences between them. Right? So not only can they respond to you right away and sound fairly human, but it can send another model in the background to call tools because before, they couldn't really do that. So sometimes these voice models hallucinated or they couldn't really work with your data or understand, you know, what it was that you were talking about because it couldn't really do that in the background. Now it can. Alright. So with that in mind, let's talk a little bit more kind of about this, real time voice race because I always think it's important to understand that before we jump into any, you know, product or service.
Jordan Wilson [00:08:32]:
So OpenAI, though, has been quietly dominating the real time AI voice space. Right? And and again, I think this is one of the future modalities. I think multimodal AI, so AI is interacting with your desktop at least right now, and probably after that, in AI that you can just talk to and it can complete work on your desktop or your phone. Right? I think that is kind of the next iteration or the next wave that's coming with helpful AI. And it starts with well, a model that you can talk to is smart and can kind of do things in the background for you. So if we look at the artificial analysis speech to speech index, right, so that's probably the best, single index, right, that takes into account multiple, you you know, different benchmarks. And OpenAI has been winning this space. Like I said, kind of quietly because everyone, for the most part, is talking about just the basic, you know, text or agent benchmarks.
Jordan Wilson [00:09:28]:
Very few people are focusing on speech to speech, which is interesting to me because if more and more people at least that are playing on the edge of AI are dictating everything like me, right, I think that's an an early indicator of where the space as a whole is headed. Right? I think we'll and and maybe we're all just waiting on Apple, to finally get the smart Siri right, but that, I think, will start to shift how people work and interface with technology. So, OpenAI, when it comes to this benchmark, they've been winning, and it hasn't really been close. They actually have four of the top six models, including the best model in the artificial analysis speech to speech index in their new GPT, GPT real time two. But what's interesting to me is even their GPT real time 1.5, the old version, is is better than what Google has in their, Gemini 3.1 live. Alright. So let's take a quick look, and I'm gonna show our, live stream audience here a little bit on the kind of marketing side for what OpenAI is putting out there for OpenAI presence. So what they said is put trusted AI agents to work across customer channels and internal workflows.
Jordan Wilson [00:10:44]:
So right now, you do have to reach out to their sales team if you wanna access. So it's not like you're just gonna log in to chat g b t or log in to your, you you know, your company's, you know, OpenAI Playground and start deploying these things. So it is, a a very limited, rollout right now. But what they say, this is trusted AI agents, and they say each agent improves through real world experience with evaluations, guardrails, and human approval governing every change. So kind of the, the three ways that they break this out to explain it is they say that this gives you one presence across every channel. They say you can show up in consistent in a consistent way across voice and chat. So, ultimately right? So if your company is looking to deploy voice agents. Right? So a phone number, maybe you don't have all the humans you need to handle volumes of calls.
Jordan Wilson [00:11:34]:
That's one thing. But then also on your website. Right? So it it it's kind of a, one system that can work and stay in sync with both. So they say show up in a consistent way across voice and chat. You decide what remains consistent, such as policies, evaluations, and escalation rules, and what should change for each workflow or channel. Then they say trust built into every, deployment. Connect agents to company systems, define policies and permissions, and validates performance through simulations, evaluations, guardrails, and escalation paths. And then last but not least, they say improve quality continuously.
Jordan Wilson [00:12:15]:
They say presence continuously gets better with use. It uses production conversations and quality signals to recommend improvements that make agents more capable. And then OpenAI has shared some use cases with some big companies that they've been testing this out with, such as BBVA, SoftBank, IHE, and then obviously their own internal use cases as well. So things that they're saying this can be used for is customer support, demand generation, claims, procurement, IT help desk, human resource, etcetera. But, essentially, anywhere right now where maybe your company is experiencing human bottleneck and you can't really scale, at the point that you need to, whether it's for customers or maybe if you're a large organization, sometimes it's an internal, you know, almost IT, HR, type shortcoming that you're running into. And and, you know, I kinda wanna go back to this concept of what AI unlocks. And I think that initial voice agents maybe got this all wrong. Because what I think initial voice agents that were too early, it was more of just, scaling this technology out to as many people as possible, but in a similar way, which I think is not the point of generative AI and artificial intelligence.
Jordan Wilson [00:13:35]:
Right? I think a lot of people I talk about this a lot, but they think, oh, this is an easy button. Let's get a blanket approach that works for everyone, which I think is the absolute wrong approach. Right? The way that you should be doing this, and I think kind of tying in, the, you know, website chat side with the voice side is very helpful. Right? I think this is, you you you know, we'll see what kind of b to b applications work well for this, but I think you should think of b to c. Right? So if you're, you you know, working at a company or maybe a consumer. Right? Maybe you are constantly like Amazon. Right? That's not to pick on one certain company, but, you know, bless that my wife is always the one if something happens with Amazon. She's the one that braves, you know, getting on the website and, you know, talking on the phone to three or four or five or six different voice agents.
Jordan Wilson [00:14:22]:
I think Amazon is actually okay at this. Right? But think of those companies, if it's not your company that could use something like this, think of those companies that you interface with. So I do think this is on the b, b to c side. But having that data follow you around from whether it is you are online chatting or on the phone and not having to reexplain those things or, you know, what went wrong with an order because, presumably, it's all gonna be tracked. Right? That's the thing that OpenAI says here. You know, talking about how it connects to your own company systems. So in the same way that, you know, most companies have been rushing to get their data in order, you know, over the past, you know, post chat g p t phase when they're like, oh my gosh. All of a sudden, we really need to have our data in order, for AI systems to be able to read and make use of this.
Jordan Wilson [00:15:12]:
Right? This is this holds true, for voice in customer success or customer experience, agents as well. So that's a kind of brief overview of what OpenAI is, saying that this is. So it's not a new model. Alright? It's just kind of the infrastructure that surrounds their voice models. So every presence agent according to OpenAI starts with one narrow job and only the system access that the job needs. So companies set the allowed actions, required approvals, and exact moments that presence should escalate to a human. Right? So you can set that level. Maybe you set it very low, and I would probably recommend that when this does roll out to the masses is, you know, don't set that escalation bar high, especially when you're testing out a new technology in production.
Jordan Wilson [00:16:03]:
Right? You have to get it right. And, again, I think people always look at maximum autonomy when it comes to trying out new AI, which is the exact wrong way to look at it. You look at your, low stakes, high quantity, instances, and then you have to be able to develop, a system internally in the same way that I've always encouraged companies to create your own benchmarks. Right? But those are text based benchmarks. Don't just look at artificial analysis. Don't just look at, I don't know, whatever you're you're looking at, arena or, you know, humanity's last exam. Right? You can't look at a single benchmark, for enterprise AI adoption. Those are great starting points.
Jordan Wilson [00:16:42]:
Right? But you need to be, for text based or agent, kind of agent based, systems. You have to have your own internal text based benchmarks that say this is what, qualifies as a win. This is what qualifies as a loss. These are our guardrails. This is how we deploy this throughout our organization. You have to do the exact same thing for voice agents, which is a little more difficult because there's things like nuance and sarcasm in your voice. So that's one thing and maybe one reason, why these voice agents, I think, initially, when we saw this this first puff of smoke in 2024 with, oh my gosh. Voice AI agents are gonna take over customer service and they well, they didn't is because the models weren't even smart enough to get over that big, gray area of, hey.
Jordan Wilson [00:17:28]:
People are ambiguous. Right? If someone responds yes, you can say yes. Right? That someone's excited about it. If they say, yeah. Right? That means they're maybe being sarcastic and not actually excited about something. So models for the most part, I think couldn't even get over one of those first big initial humps because the reason why most companies have, right, customer support with real humans is to understand that human nuance. So if if if all the model was doing in 2023, 2024 was essentially translating, your speech to text and then having a model in the background read that text, that's the reason why it just didn't work initially. So, what OpenAI actually bundles together is what presence actually is.
Jordan Wilson [00:18:16]:
So they're giving you the policies, the guardrails, approved actions, simulations, and evaluation tools inside of one product. So this is a codex powered improvement process that's built directly into the platform. It's not sold separately. And OpenAI's own, FDEs or, forward deployed engineers, connect each company systems and bring the agent live. So, yeah, we've been talking about this this FDE. Right? You'll see it in our newsletter today. Right? But Amazon just, you know, shut down kind of their AGI department or, you know, laid off a bunch of people in their AGI department, and they're focusing more and more resources on FDEs or, you know, actually deploying, putting their humans inside of these other companies. So it looks like that's what OpenAI's, kind of angle is here.
Jordan Wilson [00:19:05]:
Right? They already have their FDEs. You know, big companies already have their dedicated OpenAI, people working inside there. So this is just one other system that those FDEs or four deployed engineers will be able to implement, for OpenAI customers. So here's the thing you have to talk about. It's getting from beta, getting from demo to deployment because that is what is ultimately going to decide whether OpenAI presence is kind of the next big wave of not just customer service, but maybe where all the other AI players will play, versus just, oh, it's a new feature that may or may not pick up steam. So right now, the way that OpenAI frames it is that teams are able to simulate those common requests, edge cases, and higher risk scenarios before any customer actually sees the agents. So you can set those guardrails, humans can monitor and step in mid conversation, etcetera. And then after launch, codex can investigate real production signals and propose updates that teams can actually test before rollout.
Jordan Wilson [00:20:11]:
So now let's try to understand a little bit of what's happening under the hood. And I think this part, especially if you use OpenAI's new GPT live, and it is bonkers, y'all. It is good. I wanted to do a show on this. Right? But in our newsletter for our Wednesday demos, I I usually have you all vote. I really wanna do a show on this because I think GPT live, that's their new, essentially, the replacement for advanced voice mode inside of chat GPT. If you haven't used it, my gosh. It is good.
Jordan Wilson [00:20:46]:
Not just being able to understand your data, but, you you know, I think you can finally experience talking to an agent and then knowing that it's actually calling tools and looking things up in the background. Whereas before, I think live voice agents, whether it was chat GPTs at points, advanced voice mode, you know, Gemini live, those are probably the two, you know, big consumer versions. It almost seemed like all these voice agents would give you an intentionally, ambiguous and and vague answer, and you're like, okay. It seems to maybe be looking up something in the background, but maybe not. And it's almost like you couldn't tell. I remember one time I was literally just trying to test, like, you know, like, the hallucination or ambiguous rate, with, you know, head to head between Gemini Live and, the advanced voice mode with chat gbt. But regardless, the technology just wasn't good. But I think this last iteration from OpenAI makes it good, and it's multiple models.
Jordan Wilson [00:21:42]:
So first, let's talk about GPT real time two. Well, technically, it's now GPT real time 2.1 because they just came out with an update. But that's essentially the developer tool for building custom voice agents through OpenAI's API. So they essentially have this technology. Right? Let's just call it super smart AI voice. Right? So if you're a developer and if you wanna build with this new super smart AI voice, you would use GPT real time 2.1. If you're a consumer and you want to experience it just using your chat g p t account, that's called GPT live one. So both of these are new in the last two weeks.
Jordan Wilson [00:22:18]:
So that powers the new chat g p t voice where you can hold a live conversation while the AI quietly handles harder work off to another model, whether it's calling tools, looking at your data, searching something on the Internet, thinking, reasoning in the background about something that would normally take an AI model a little bit longer. Right. The last technical details we we saw was that they kicked this over to g p d 5.5, and it would think and reason about things while the real time model kept the conversation going. So presence, though, sits above both. So it's not a new model. Right? It sits above both, and OpenAI has not yet revealed, which model actually powers, presence. Although, I'm guessing it's probably something on the g p t real time two side. That would be my guess.
Jordan Wilson [00:23:04]:
Alright. So why do you have to pay attention to this? And I think this is something where I think trust either increases or erodes depending on your experience. Right? A a a very simple example. I don't I forgot what the company is. Right? But it's it's either a heating or air conditioning company that I use here in Chicago. They had their voice agents, and they're actually tricky at first. The first time I called, I don't know, heater, air conditioner wasn't working very well. And I'm like, wait.
Jordan Wilson [00:23:37]:
This kind of sounds real. And then instantly, obviously, being around AI, I knew it was AI, and I was having fun trying to, you know, jailbreak it on the phone, that kind of stuff. But it couldn't get human hand off. And that was a bad thing, because, ultimately, what matters here, it's not about the technology. It's about our consumers, queries being resolved or not, or are people just more frustrated. But the the reality is I think consumers want this. There was actually a study from 05/09 that said that 80% of consumers are willing to use AI customer service. Right? Yes.
Jordan Wilson [00:24:16]:
I know there's some companies out there that do customer service well, but I would say this is an argue that is literally just, sorry. This is an area that is literally begging to be disrupted because it is so bad. The quality is so slow. And ultimately, I don't know. Anytime I have to make a call to customer service, I feel there is no resolution. So maybe this is something I'm personally rooting for for the industry. Right? I don't let that impact, you know, if if you're a decision maker at your company, don't let that impact, you know, your decision on whether you should be using these type of voice in real time agents or not. But regardless, the consumer demand is almost overwhelming.
Jordan Wilson [00:24:56]:
Right? You've you've seen this whether it's, it has any merit or not. You've seen this recent kind of uprising against AI, and I'm not just talking about AI slop. Right? Companies, I think, are deploying sometimes AI in an irresponsible way, when it comes to job creation, job growth, job growth, things like that. So sometimes there's this kickback against AI, but at least when it comes to the appetite for, deploying real good AI agents, it seems like customer service right? Consumers want this. So if you are a a business leader, maybe you haven't even, you you know, maybe you're in the in the space where it's like, yeah. We don't even really offer customer service. Well, maybe you probably can. So that's another thing to, think about.
Jordan Wilson [00:25:44]:
So like I started the show off with as we wrap here, this was a quiet launch, which was interesting to me. And presence, I think, drew so little attention because essentially, it's not sexy. Right? Enterprise infrastructure doesn't look exciting when it's first launched. But that's what powers this thing. If you don't have the infrastructure set up, this isn't going to be a reality for you. So I think that, obviously, customer service organizations, they do have the infrastructure. But what about everyone else? What if customer, you know, service or phone service is, you know, not even a top 10 priority for you, but you've always been, offering it? I I I think customer service, though, may become AI's kind of first mass consumer disruption. Right? Aside from text, that's that's come and gone.
Jordan Wilson [00:26:28]:
So maybe it's the next big iteration. Yes. We've all seen AI photos and AI videos, in advertisements, but I think that's gonna continue to blur the line between what's real and what's not. But I think what is real is that this is a space that is probably likely going to explode. Because like I started with, both OpenAI, Google, Anthropic, and even technically Grok, all the players are saying to are starting to invest heavily in this space because the technology is finally good enough where this can actually be a customer service tool that is worthwhile and that, the users want. But whether that helps customers depends entirely on what companies optimize this first. And if you are just looking for that big red easy button or if you have the infrastructure in human power to actually deploy this in a responsible way that helps meet that demand. Alright.
Jordan Wilson [00:27:23]:
So that's a wrap on what's new with OpenAI Presence. And, hey, my kind of hot take, takeaway on this is, like I said, I'm rooting for this, not just for OpenAI Presence. I'm rooting for this segment. Because personally, as a consumer, I hated customer service for the longest time. I've very rarely had a good experience, and at least according to studies, it seems like that is normal across the board. So in my, in in in my experience, this is something that I think enterprise companies should be looking at. Obviously, if you're already in the b to c space, if you already have dedicated customer support, there's probably a good chance that you have the infrastructure to take advantage of this. So you should be looking at it.
Jordan Wilson [00:28:07]:
But for everyone else, I think this also begs the question. Should we be doing this? Whether it's for or maybe you're in the b to b space. Maybe you are in the b to c, space, but you just haven't had kind of a dedicated customer phone or customer chat service, and maybe you should. Or even for larger organizations looking to deploy something like this internally. Right? If you have tens of thousands of employees, being able to give that level of personalization like I was talking about easier, or or like I was talking about earlier, where I think companies when they find generative AI, they're like, okay. We could just put out more content that appeals to everyone when I think it's the reverse. You have to, ingest those signals, ingest those data points, and you should just be putting out more personalized, messaging and more helpful messaging to more people. So maybe that's internally, maybe that's externally.
Jordan Wilson [00:28:53]:
But regardless, I think the technology is finally there, and that's exciting. And, well, we'll see if OpenAI presence gets more eyeballs on it. So, that's a wrap for today's show. Thank you for tuning in. If you haven't already, please go to youreverydayai.com. Sign up for the free daily newsletter, and make sure to tune in tomorrow. We're gonna be going over our Friday features. There's a lot of new stuff that dropped both, yesterday and that I know is coming today, so you're not gonna wanna miss that one.
Jordan Wilson [00:29:18]:
Thanks for tuning in. We'll see you back tomorrow and everyday for more everyday AI. Thanks, y'all.