
OpenAI Presence 登場:AIによるカスタマーサービス革命はついに始まったのか(再放送)
Ep 879: New: OpenAI Presence. Has The AI Customer Service Takeover Finally Arrived? (Replay)

OpenAI Presence 登場:AIによるカスタマーサービス革命はついに始まったのか(再放送)
Everyday AI Podcast – An AI and ChatGPT Podcast
要約
Jordan Wilson 氏が、OpenAI が発表した企業向けプラットフォーム「Presence」を解説する回。音声・チャットのリアルタイムAIエージェントを構築・運用する基盤で、新モデルそのものではなく、ポリシーやガードレール、評価、エスカレーションを含む周辺インフラだと説明している。GPT Real-Time 2.1 や GPT Live といった音声モデルの進化を背景に、カスタマーサービスがAIによる最初の大規模な破壊的変化になり得ると述べ、導入時は低リスク・大量の業務から始め、独自の評価基準を持つべきだと助言している。
この回のポイント
- ●Presence は、顧客サポート・営業・HR・IT向けにリアルタイムの音声/チャットエージェントを構築・展開・管理する企業向けプラットフォームで、新しい音声モデルではないと説明されている。
- ●OpenAI は、エージェントが評価・ガードレール・人間の承認のもとで実運用の経験から改善されると説明している。現状は営業チームへの問い合わせが必要な限定提供である。
- ●Artificial Analysis の speech-to-speech 指数で、OpenAI が上位6モデル中4つを占め、GPT Real-Time 2 が首位だと紹介された。旧版の 1.5 でも Google の Gemini 3.1 Live を上回るという。
- ●開発者向けは GPT Real-Time 2.1、一般ユーザー向けは GPT Live 1 で、会話を続けながら裏で別モデルがツール呼び出しや検索・推論を行う構成が、以前の課題を解消したと述べている。
- ●導入では最初からの完全自律を避け、低リスクで件数の多い業務から始め、エスカレーション基準は慎重に設定し、皮肉などの機微も含めた自社の評価基準を作るべきだと助言している。
- ●発表が静かだったのは地味なインフラだからだと分析し、Five9 の調査(消費者の80%がAI顧客対応を利用する意向)を挙げて需要の大きさを指摘した。
章立て
Presence の発表と全体像
OpenAI Presence の概要と、静かな反応にもかかわらず重要だという番組の見立て、番組で学べる内容を紹介する。
音声AI競争の現状
Codex の音声モード、Anthropic、Google の Gemini Live など各社の動きと、リアルタイム音声が実用水準に達した背景を説明する。
音声ベンチマークでの OpenAI の優位
Artificial Analysis の speech-to-speech 指数で OpenAI が上位を占めている点を紹介する。
Presence の機能と使い方
チャネル横断の一貫性、ポリシーや権限による信頼性、継続的な改善という3本柱と、BBVA、SoftBank などの事例を紹介する。
導入の勘所とガードレール
狭い業務から始める設計、エスカレーション設定、独自評価基準の必要性、過去の音声エージェントが失敗した理由、FDE の役割を述べる。
裏側のモデル構成:GPT Live と Real-Time 2.1
GPT Real-Time 2.1、GPT Live 1、裏で推論するモデルの関係と、Presence がそれらの上位に位置することを整理する。
消費者の需要とまとめ
体験談や Five9 の調査をもとに需要を論じ、インフラの重要性と企業が検討すべき点を述べて締めくくる。
解説記事
AIポッドキャスト「Everyday AI」の司会、Jordan Wilson 氏が、OpenAI が発表した企業向けサービス「Presence」を取り上げた回である。発表後の反響は小さかったが、同氏はカスタマーサービスがAIによる最初の大規模な破壊的変化になり得ると見て、その意味を解説している。
Presence とは何か
Presence は、企業がリアルタイムの音声・チャットエージェントを構築・展開・管理するためのプラットフォームで、用途は顧客サポート、営業、HR、ITヘルプデスクなどだ。同氏は、これが新しい音声モデルではなく、音声モデルを取り巻くインフラだと強調している。
OpenAI の説明として、各エージェントは「狭い仕事」と必要最小限のシステム権限から始まる。企業は許可する操作、承認の要否、人間に引き継ぐタイミングを設定できる。ポリシー、ガードレール、シミュレーション、評価ツールが一体で提供され、Codex を使った改善の仕組みも組み込まれている。導入時には OpenAI の Forward Deployed Engineer(FDE、顧客企業に入り込んで実装を支援するエンジニア)が企業システムとの接続を担うという。現時点では営業チームへの問い合わせが必要な限定提供で、BBVA や SoftBank などが事例として挙がっている。
今になって実用化した理由
同氏は、2023〜24年にも音声エージェントによる顧客対応の自動化が語られたが、モデルが遅く不自然で、機械的に聞こえたと振り返る。会話が一瞬途切れるだけで顧客対応は台無しになるうえ、皮肉のような人間らしい曖昧さも扱えなかったという。
状況を変えたものとして、開発者向けの GPT Real-Time 2.1 と、ChatGPT 向けの GPT Live 1 を挙げている。会話を担うリアルタイムモデルが応答を続けつつ、裏で別モデルがツール呼び出し、検索、推論を行う構成で、以前の音声モデルでは難しかった部分だと説明する。また、Artificial Analysis の speech-to-speech 指数では上位6モデルのうち4つを OpenAI が占め、旧版の GPT Real-Time 1.5 でも Google の Gemini 3.1 Live を上回ると述べている。同氏は、Presence に使われるモデルは未公表だが、Real-Time 2 系だろうと推測している。
導入で気をつけたい点
同氏が繰り返すのは、最初から最大限の自律を目指さないことだ。低リスクで件数の多い業務から始め、人間への引き継ぎの基準は慎重に設定することを勧めている。テキスト向けと同様に、何を成功・失敗とみなすか、ガードレールをどうするかを自社の評価基準として定める必要があり、音声ではニュアンスや皮肉が加わるため難度が上がるとも述べる。
また、画一的な「簡単ボタン」として全員に同じ対応を配るのは誤りだと主張する。チャットと電話の履歴が連携し、顧客が何度も説明し直さずに済むことが価値であり、そのためには企業側がデータを整備し、社内システムとつなげておく必要がある。同氏自身、空調会社のAI電話対応で人間への引き継ぎができなかった経験を挙げ、技術より問い合わせが解決するかどうかが信頼を左右すると語る。
需要と競争環境
同氏は Five9 の調査として、消費者の80%がAIによる顧客対応を利用する意向を持つという数字を紹介している。顧客サービスの質に長年不満があるため、需要は大きいという見方だ。一方で、AIの雇用面での無責任な導入への反発があることにも触れている。
競争面では、OpenAI が Codex 向けのリアルタイム音声モードを準備していると報じられ、Anthropic も音声モードをリークされており、Google の Gemini Live も更新が見込まれるとして、主要各社が音声領域に投資を始めていると述べる。Presence の反響が小さかったのは、エンタープライズ向けインフラが華やかでないからだというのが同氏の分析だ。
まとめ
本回の主張は、音声AIの水準が上がった今、競争の焦点がモデル単体から、運用・統制・改善を含む仕組みに移りつつあるということだ。同氏は、結果が顧客の役に立つかは企業が何を最適化するかにかかっていると述べている。
日本の読者にとっては、コールセンターや社内ヘルプデスクの自動化を検討する際、モデルの性能だけでなく、権限設計、エスカレーション基準、自社評価、データ整備が成否を分けるという示唆が得られる。なお、Presence は限定提供で、効果を示す数値の詳細は本回では語られていない。実運用の成果は今後の公開情報で確認したい。
文字起こし(英語・自動生成)
OpenAI announced a new offering yesterday in OpenAI Presence, a service that I thought would make a pretty big splash. Yet, in the first 24-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 and 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 neural enough or fast enough or nearly smart enough.
Now they are. 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.
And right now, customer service, does anyone actually like it? For me, it's almost the bane of my existence. I know I'm going to 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 2 models, you would not know any better. You would say, oh, any AI agent. Yeah, I've heard these talking to customer service. They're slow and very robotic. Well, that's not the case anymore. So on today's show, here's what you're going to learn. You're going to know what OpenAI presence actually is and why it's not the new voice model everyone assumes. You're going to 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 going to 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. All right, welcome to Everyday AI. If you're new here, my name is Jordan Wilson, and we do this every day. This is your unedited, unscripted daily live stream 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 a cheat code. So it starts here, but make sure you go to our website at youreverydayai.com. We're going to 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. All right, so OpenAI 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 know, commercially and from the consumer side in like late 2023, early 2024, you know, there was already this first warning sign, right? The boy who cried wolf came and said, hey, customer service, you know, all these jobs are going to go away. But it wasn't the case. The models weren't good. But now this may be different now. But first, I want to zoom out and not just talk about OpenAI presence. And I want to talk about the space in general, because oftentimes it is the competition that ultimately drives the end product or the services that those products get rolled into. And reportedly, right, and 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. All right. 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 can 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 may we be getting a new real-time voice mode from OpenAI via Codex, but also we've seen some recent leaks that show Anthropic is also going to 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 and Gemini Live updates, we haven't seen anything in a long time. But I would assume that whether it is part of the Gemini 4 that is now under pre-training 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 says 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 And when it comes to customer service and customer interactions that all you need to completely ruin it right And that why you know back in 2024 so many companies did not jump on this bandwagon rightfully so because the technology wasn there
But now these models, right, they respond to you in real time, especially in the new GPT Live 1 and the GPT 2 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. All right. 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. So OpenAI, though, has been quietly dominating the real-time AI voice space, right? And again, I mean, 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, an 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 of 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 know, different benchmarks and open AI 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. 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 early indicator of where the space as a whole is headed, right? I think we'll, 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 Real-Time 2. But what's interesting to me is even their GPT real-time 1.5, the old version, is better than what Google has in their Gemini 3.1 Live. All right, so let's take a quick look, and I'm going to 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. So right now, you do have to reach out to their sales team if you want access. So it's not like you've just got to log into ChatGPT or log into your company's OpenAI Playground and start deploying these things.
So it is 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 in 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. That's one thing. But then also on your website, right? So 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 in 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. 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, etc. 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, you know, I kind of want to 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, 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 know, we'll see what kind of B2B applications work well for this, but I think you should think of B2C, right? So if you're, 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. 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 B2C side. But having that data follow you around from whether it is you are online chatting or on the phone and not having to re-explain those things or, you know, what went wrong with an order, because presumably it's all going to 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 phase when they 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 right
This holds true for voice and 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, all right? 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, 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 looking at, arena or, you know, humanities last exam. Right. You can't look at a single benchmark for enterprise A.I. adoption. Those are great starting points, right? But you need to be for text-based or 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 first puff of smoke in 2024 with, oh, my gosh, voice AI agents are going to 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, 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 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. 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's 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, 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 forward 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, etc. And then after launch, Codex can investigate real production signals and propose updates that teams can actually test before rollout. 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 usually have you all vote. I really want to 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. Not just being able to understand your data, but, 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 ChatGPT's advanced voice mode, you know, Gemini Live, those were probably the two, you know, big consumer versions. It almost seemed like all these voice engines would give you an intentionally ambiguous 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 ChatGPT. But regardless, the technology just wasn't good. But I think this last iteration from OpenAI makes it good in its multiple models. So first, let's talk about GBT Real-Time 2. Well, technically, it's now GBT 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 the super smart AI voice, right? So if you're a developer and if you want to 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 GPT account, that's called GPT Live 1. So both of these are new in the last two weeks So that powers the new chat GPT voice where you can hold a live conversation while the AI quietly handles harder work off to another model whether it 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 saw was that they kicked this over to GPT 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 GPT
real-time 2 side. That would be my guess. All right. 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 very simple example. I don't, I forgot what the company is, right? But 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, this kind of sounds real. And then instantly, obviously being around AI, I knew it was AI and I was having fun trying to jailbreak it on the phone, that kind of stuff. But it couldn't get human handoff. 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 reality is I think consumers want this. There was actually a study from Five9 that said that 80% of consumers are willing to use AI customer service, right? Yes, I know there's some companies out there that do customer service well, but I would say 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 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, right? You've seen this, whether 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, 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 business leader, maybe you haven't even, you know, maybe you're 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. 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 service or phone service is not even a top 10 priority for you, but you've always been offering it. I think customer service, though, may become AI's kind of first mass consumer disruption, right? Aside from text, that's come and gone. 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 going to continue the blur of a 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 Grot, all the players 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. All right. So that's a wrap on what's new with OpenAI Presence. And hey, my kind of hot 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 have 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 experience, this is something that I think enterprise companies should be looking at. Obviously, if you're already in the B2C 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. 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 B2B space, maybe you are in the B2C 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 like I was talking about earlier, where I think companies, when they find generative AI, they're like, okay, we can just put out more content that appeals to everyone, but 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, 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. Thanks for tuning in. If you haven't already, please go to your everydayai.com. Sign up for the free daily newsletter and make sure to tune in tomorrow. We're going to 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 going to want to miss that one. Thanks for tuning in. We'll see you back tomorrow and every day for more Everyday AI. Thanks, y'all. And that's a wrap for today's edition of Everyday AI. Thanks for joining us. If you enjoyed this episode, please subscribe and leave us a rating. It helps keep us going. For a little more AI magic, visit youreverydayai.com and sign up to our daily newsletter so you don't get left behind. Go break some barriers, and we'll see you next time.
番組の概要欄(原文)
OpenAI launched Presence, and it seems like no one really noticed. They should have. Presence gives companies a way to build and manage real-time AI voice and chat agents across customer service, sales, HR, and IT, which could make this one of OpenAI’s most important enterprise launches yet. The technology finally looks fast, natural, and capable enough to disrupt customer service at scale. That could mean faster answers and fewer terrible phone trees. Or an endlessly patient...
出典・この記事について
- 番組
- Everyday AI Podcast – An AI and ChatGPT Podcast(Everyday AI)
- 元の回
- Ep 879: New: OpenAI Presence. Has The AI Customer Service Takeover Finally Arrived? (Replay)
- 配信日
- 要約作成日
- 公式サイト
- youreverydayai.com
この要約・解説記事は、元の音声を文字起こしした内容をもとに AI(Claude)が日本語で作成したものです。 固有名詞や数値に誤りを含む場合があるため、正確な内容は元の音声でご確認ください。制作方法について


