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The Emerging Tech Order: Agent Orchestrators, Deepfakes, and the AI Transformation Every Business Needs to Track
AI’s accelerating trajectory in 2025 has introduced seismic operational shifts for companies—demanding close attention from every business owner and executive. Derived from a recent episode of Everyday AI, this comprehensive analysis delivers the granular details leaders must internalize to stay ahead. From new job roles engineered for AI-powered workflows to the complex risks introduced by deepfakes, the evidence compiled here can fundamentally inform decision-making.
AI Agent Orchestrators: Shaping Tomorrow’s Organizational Structure
Modern enterprise environments have begun integrating dedicated roles like “agent orchestrators,” “AI agent architects,” and “human-AI collaboration leaders.” These positions are actively involved in managing and coordinating dozens of specialized AI agents—demonstrated by corporations such as Walmart, KPMG, Salesforce, Adobe, and ServiceNow.
Notably, these functions exemplify permanent, recognized roles. Enterprises like AWS and Klarna have pivoted toward treating agent compute costs as “digital FTEs”—factoring AI agents into labor assets and procurement. Salesforce’s Agent Force subscription enables companies to “hire” AI agents for operational execution, shifting AI from a tool to a workforce strategy. The post-pandemic era’s “agent orchestration” is no longer experimental speculation; it’s now embedded in job classifications and quarterly reporting.
Enterprise Reasoning Data: Capturing Critical Insights for Private Models
The focus on “reasoning data” stands out. Enterprises are investing in proprietary data collection explicitly for training advanced reasoning models—those capable of agentic task breakdown, decision mapping, and iterative research across multi-step workflows. According to recent OpenAI and Red Hat analyses, organizations increased reasoning token consumption 320-fold in just twelve months, and synthetic data generation is being deployed to transform proprietary business knowledge into actionable training sets for private engines.
This direction means companies must go beyond structured data. Capturing and cleaning unstructured intellectual property and documenting internal decision-making processes will empower future AI tools to emulate core business reasoning, not just automate routine analytics.
Professional Services: Pricing Model Disruption in Law, Consulting, and Accounting
Billing frameworks within legal, consulting, and accounting industries are shifting away from time-based models. Output-based pricing has been formally adopted, triggered by client-side expectations and AI-driven cost efficiencies. According to S4 Capital and research by Thomson Reuters and McKinsey, professional firms are restructuring contracts to accommodate AI’s capacity for rapid data crunching and presentation-generation. Early AI adopters report up to 40% cost reductions.
As consultancies and firms reconfigure hiring practices, entry-level and junior roles—traditionally assigned repetitive analysis and deck creation—are declining. Products like Claude Opus 4.5 and GPT models now outpace junior consultants in producing quality deliverables at scale.
Universal Basic Income: AI Job Displacement Spurs Policy Conversation
While a universal basic income (UBI) has not reached mainstream enactment, legislative proposals and pilot programs are emerging with AI-related job displacement cited as a motivator. Cook County, Illinois, has permanently allocated funds to guaranteed income, and leading technology executives openly back policies considering automation’s threat to workforce stability. For business leaders, this signals a policy landscape increasingly shaped by AI’s labor impact, affecting long-term workforce planning.
Open Source AI Models: Benchmark Outperformance and Market Implications
Open source AI models—especially those from China—have overtaken proprietary models on key performance benchmarks. DeepSeek, for example, released an open weights model briefly outperforming OpenAI’s GPT-4o, causing market ripples and $1 trillion in lost US market cap until clarifications followed. Currently, almost a third of global AI usage relies on Chinese open source models, complicating enterprise evaluation and competitive intelligence.
Deepfake Risks Amplified: The Social Media Challenge
The growing sophistication of AI-generated media has transformed misinformation from nuisance to strategic threat. Deepfake fraud incidents surged 19% in Q1 2025, with research indicating only 0.1% of trained observers could reliably distinguish fake from authentic. High-profile events—such as the AI-driven impersonation of a US Secretary of State—underscore the strategic and reputational risks for companies with high-profile executives or sensitive communications. Social media platforms increasingly serve as proliferation vectors, multiplying the risk surface and requiring robust detection, validation, and response protocols.
Embodied AI Investment: Robotics, Drones, and Wearables Go Mainstream
Venture capital outlays in robotics and drone intelligence surged by over 40% in 2025. Organizations are investing heavily in humanoid robots, autonomous vehicles, and wearables—with leading VC voices projecting this category as AI’s largest opportunity. Large-scale deployments are evident in logistics, warehousing, and last-mile delivery, impacting daily business operations and customer experience design.
API Pricing Shifts: Frontier Intelligence at Commodity Cost Levels
Frontier-level intelligence is now available at fractions of previous costs—$0.15 to $0.27 per million tokens—well below the expectations set earlier in the year. Such reductions enable broader and deeper AI integration for business operations. Enterprises now have access to potent reasoning and analytic capabilities at negligible marginal cost, supporting aggressive experimentation in scalable workflows.
AI Video Production: Nearing Full-Scale Automation in Media Creation
AI video tools approached the milestone of one-shot HD video generation for five-minute segments. While most are currently capped at 20-60 seconds due to compute, stitching, and extension features (e.g., Cling AI), enabled three-minute scenes from single prompts. Major studio investments, including Disney’s $1 billion partnership with OpenAI, indicate mass content production will rapidly shift from CGI to pure AI generation.
Strategic Imperatives for Business Owners and Decision Makers
- Redefine workforce models to accommodate agent orchestrators and digital FTEs
Prioritize reasoning data collection to empower enterprise-specific AI models
Restructure billing models toward output-based pricing in professional services
Monitor policy shifts around universal income and workforce automation
Track open source adoption and supply chain security across global AI solutions
Develop robust protocols for deepfake detection and response
Assess embodied AI opportunities in operations and logistics
Capitalize on lower API costs for broad AI deployment
Experiment with AI-driven media creation in marketing and content
The next twelve months carry outsized consequences for leaders keen to leverage AI advancements. Integrating these specific insights from the latest technology landscape will prepare organizations to scale, protect, and compete effectively in the new tech order.
Topics Covered in This Episode:
- AI Agent Orchestrators as Job Title
- AI Agents in Company Hiring Trends
- Enterprise Reasoning Data Collection Growth
- AI Driving Professional Services Pricing Crisis
- Universal Basic Income and AI Job Loss
- Open Source AI Models Surpassing Proprietary
- Chinese AI Model Global Market Impact
- Perplexity Answers Engine Business Pivot
- Frontier AI API Price Drops
- VC Funding Surge in Embodied AI
- Advancements in AI Video Generation Tools
- AI’s Disruption of Traditional Internet Models
- Social Media Deepfake Misinformation Surge
Episode Transcript
Jordan Wilson [00:00:16]:
A lot can change in a year. Think about it. In your own personal or professional life, how much has it changed in 2025? Probably a lot, but probably not as much as AI. Because when we're talking about AI, time is like warp speed. I mean, a year in AI time is like seven dog years. So that's like forty nine real life years. So when I look back at the 2025 AI predictions show that I made back in January, it feels like a legit lifetime ago because that's how fast AI moves and how much the landscape shifts almost on a daily basis. So here we are eleven and a half months later, and it's time to revisit those AI predictions that I left you with.
Jordan Wilson [00:01:07]:
And over the five part series that I did back in January, I'd say I was actually a little bold and I didn't just call my AI predictions predictions. I actually called them the AI predictions and roadmap series. That's because as absolutely insanely crazy as many of those AI predictions were at the time, I knew that many of them would probably somehow eventually come true. And I wanted you to tune in, hear what I had to say, and make decisions that would hopefully grow your business. And I'm one well with the daily podcast. It's I have to hold myself accountable. Right? Yeah. You can say this is a fun informal thing, and it is.
Jordan Wilson [00:01:56]:
But, you know, we I'm lucky enough to be able to reach millions of people a year, and I take that responsibility very seriously. So we're checking back in today. I'm gonna hold myself accountable. We're gonna bust out, receipts longer than if you bought every item at CVS. So between today and tomorrow, we are hitting a rewind on our 2025 AI roadmap series. So did we get it right? Did we lead you astray or were we spot on and maybe you took advantage and grew your company or your career. Alright. Let's jump into it.
Jordan Wilson [00:02:35]:
Let's get recapping. I'm excited for today's show. I hope you are too. What's going on? If you're new here, my name is Jordan Wilson, and this is Everyday AI. Yeah. We do it every day. It's your daily unedited, unscripted, live stream podcast, and free daily newsletter helping everyday business like business leaders like you and me keep up with the whirlwind of changes because it's nonstop and help us hopefully make sense of it to grow our companies and careers. So make sure if you haven't already, please go to our website, youreverydayai.com.
Jordan Wilson [00:03:03]:
If you miss any of the half of the 25 of the AI predictions we're gonna be going over today, we're gonna be recapping it all in our newsletter as well as the news from today. So what you need today to be the smartest person in AI at your company. So what the heck went into these, predictions from, January 2025? Well, a lot. I did this the year before as well. But, essentially, if you are brand new here, I'm I'm lucky. Right? I'm I'm very lucky. I get to talk to a ton of really smart people, you know, from CEOs of Fortune 100 companies, to people building actual AI models at all the big tech companies, to, you know, small business CEOs, you know, who are trying to, better understand the AI landscape themselves. So, each year, I talk to hundreds of people, and that's really what went into the twenty twenty five AI predictions.
Jordan Wilson [00:04:02]:
Just a lot of conversations, both ones that you all maybe listened to and those that weren't even, you know, recorded. You know, I'm very, blessed to be in a situation to learn from a lot of smart people. And, you know, that's why I sometimes call everyday AI a cheat code. Right? You don't have to spend all the hours that I do. I just give you the bullet points, the hopefully golden nuggets that can help you make sense of it. So, a lot went into our 2025 AI predictions in 2025, not just, you know, me randomly, throwing some AI spaghetti at the wall and see what stuck. And if you do wanna go back and listen to all of those episodes, they're all on our website, youreverydayai.com, or if you're listening, on Spotify, Apple Podcasts, etcetera, go find episodes four forty three to four forty seven. You can listen to them all there.
Jordan Wilson [00:04:51]:
They're all pretty short. It was five. So we broke down five, predictions a day over the course of five days. In all of these shows, we're about twenty five minutes. So, today and tomorrow, we're gonna be tackling, about, you know, I think we're gonna do 12, 12 or 13 today. I actually forgot. We'll find out here, and then the other half tomorrow. So without further ado, let's get straight into it.
Jordan Wilson [00:05:16]:
This is gonna be a faster show FYI, because like I said, if you wanna go listen to the whole thing, go back and listen to the episodes. Alright. So we're gonna start with number 25. This is how we did it. In January, we went 25 through one. So in part one and part two, we're gonna be doing the same thing starting from prediction, 25 and going backwards. So number 25 in January 2025 was agent orchestrators will be a growing position. And just FYI, I'm I'm probably I'm gonna try not to say this every single prediction, but think back, think back to January 2025.
Jordan Wilson [00:05:53]:
This is when the main AI models were GPT four O and Claude three five SONNET and Gemini two. Not Gemini three, not Gemini 2.5. Gemini two. Right? We I mean, we had entire AI product lines that hadn't even yet been announced and have already been killed off. Right? Opening eyes operator hadn't even been announced yet, and it's been announced and essentially now killed off and replaced. Right? So keep that in mind when I'm talking about these predictions because when I talk about agent orchestrators, right, this is the first, prediction here. My prediction was that it's going to be an actual growing position and that you're gonna have people at companies who are gonna be, essentially, agent orchestrators overseeing dozens of specialized agents. Sounds safe now.
Jordan Wilson [00:06:43]:
Right? At the time, I literally couldn't find anything on the Internet about agent orchestrators. Right? This was a crazy prediction, but go back to today, not crazy at all. This one crushed it. Absolutely nailed this one. Right? So agent orchestration is now a common enterprise product in skill, especially in IT and ops. There was a recent MIT Sloan, report that said service, so kind of mentioning some, some big name companies that actually have, positions, in agent orchestration. So ServiceNow, has positioning now around AI agent orchestration. The Washington Post reported in October that Walmart, KPMG, and Salesforce are debuting new AI job titles, including orchestration engineer, AI agent architect, and human AI collaboration leader.
Jordan Wilson [00:07:42]:
So, you know, different ways to say agent orchestration. And Adobe literally has jobs for Adobe agent orchestrator, and they call it AO just like I called it AO back in January before anyone called it that. Just FYI. Alright. Not saying, you know, I I I started the craze of agent orchestration. I didn't. Right. But I I was talking about it back in, 2024, actually, which is one of the reasons why it made it into, the 2025 AI prediction and road map series.
Jordan Wilson [00:08:13]:
Alright. So, we'll say we did pretty okay. And by that, yeah, knock that one out of the park. Alright. Number '24, companies will post jobs for AI agents. So my actual prediction here was at least one public company will post a job where the candidate is actually an AI agent. So, company is gonna be posting jobs not for humans. So this one got it pretty much right, except it wasn't a publicly traded company, but there was plenty of instances where actual real companies posted jobs that were not for humans.
Jordan Wilson [00:08:49]:
Alright. Also, some recent reports have surfaced that AWS and Klarna have reclassified agent compute costs as a digital FTEs or digital full time employees. Right? So, shifting it from OPEX, to, CAPEX. So literally redefining, current roles within their organization, and essentially now saying that they have AI agents that have full time jobs. So this is a trend here because enterprises are effectively hiring agents for procurement and scheduling roles, treating them as labor assets in their quarterly reporting. So although, you know, we don't have public companies now posting, you you know, jobs for AI agents in a way at least, on their reporting, they are kind of retroactively going back and re, reformatting some jobs and some roles as such. We did see though, Salesforce Agent Force allowed companies to hire agents via subscription. So, you know, kind of reverse.
Jordan Wilson [00:09:56]:
Right? Kind of like, hiring, like, you might go and hire a, a specialist on, you know, Upwork or something like that. Salesforce's Agent Force, you can go hire agents as if you were hiring employees. So, kind of in a roundabout way, got that one there. But there's also I mean, for smaller companies, non public companies, it it was endless. Right? One of the more popular ones didn't this one didn't take long to hit, by the way. This was in February. But a a startup called FireCrawl, went viral after they listed a job that was not meant for humans, and it specifically only asked for AI agents to apply. So yeah.
Jordan Wilson [00:10:35]:
The the cool part there is I believe it wasn't you like humans were not even supposed to, meant to apply their agent for the job. It was only supposed to be agents discovering this and then applying for the job in that way. So, we saw actually, quite a few of these, postings from smaller companies. But, you know, like I said, with the Salesforce Agent Force and, some of the larger companies kind of reclassifying what they consider, you know, wasn't too far off on this one. Alright. Number 23, company reasoning data collection. So, would become a, a focus. So the prediction here was that companies would start collecting data specifically to support or shape reasoning models.
Jordan Wilson [00:11:23]:
Like the best way to think about this is even though it's technically not a 100% accurate, right? Like sometimes for our non technical audience, I like to say this is 99% accurate and, you know, hopefully, it'll appeal to 99% of the population. Right? The way I like to think of it is you have these old school transformer models. Right? And they worked great, when you put your company's structured data in there. Right? Reasoning models. So the newer breed of models, these are models that break down complex prompts, and they think about it, and they, you know, agentic models will go and, you know, research different paths, and they'll, you know, call different tools, and they'll go back, you know, from step five back to step three and, you know, go, you know, go down route c instead of route b. Right? These models, yeah, you can feed them structured data. You can feed them x's and o's and spreadsheets, but what really helps them is your company's IP, your company's decision making. Right? Your company's unstructured data.
Jordan Wilson [00:12:28]:
So that's kind of the, the crux of this, what this prediction was. So what happened? Where are the receipts? Well, in OpenAI's state of enterprise AI plan that was just, or sorry, a state of enterprise AI 2025 report that was just, released last week, they did reveal that the average reasoning token consumption per organization increased 320 fold in twelve months. So companies are burning, reasoning tokens like probably no one could have, guessed. And Red Hat. Alright. So one of the big leaders in the space, Red Hat did detail how enterprises right now are using synthetic data generation to convert proprietary data into training examples for private reasoning engines. Alright. So, this one might still be a little ahead of the curve.
Jordan Wilson [00:13:20]:
Right? So if you are listening to this and you've heard me talk before, about, company reasoning data, I think I had an acronym, for it. I'll have to go, in the newsletter and remember what that acronym was because I haven't talked about this in a couple of months. If you're listening to this, you need to start doing this. I'm probably gonna have maybe an entire, show or a series of shows just on this. It isn't that important. You know, I think finally, the general public is actually using these thinking or reasoning models more where I just assumed that when they came out right in early twenty twenty five, you you know, when they became publicly available, I assumed every single person would use them because they're better. But I was wrong. Humans are impatient.
Jordan Wilson [00:14:08]:
Even smart humans are impatient, and they're using inferior models when they shouldn't be. So this is, I still think, a huge area of growth. Whether you're an AI builder out there or leading AI, strategy implementation at your company, you have to start collecting, cleaning, curating, and categorizing your company's, reasoning. Right? It's it's huge. Alright. Number twenty twenty or sorry. Number 22, from our January 2025 prediction series. High end professional services will go through a pricing crisis.
Jordan Wilson [00:14:45]:
So I said AI will drive down prices and reshape billing in law, consulting, and accounting. I'd say definitely got this one right, but it is going to be, I think, an even bigger wave happening here over the next quarter or two. Because if I'm being honest, this one really didn't start to, quote, unquote, hit home until the last two months. Right? Some of these AI, predictions and and road maps hit instantly. This one didn't start to hit until literally probably quarter four, if I'm being honest. So here's the reality. There's a recent, s four capital announcement this summer that explicitly talked about the transition to output based pricing away from billable hours. Alright.
Jordan Wilson [00:15:31]:
Thompson Reuters report in April said that professional services pricing is going through a recognition that new technologies may impact the mac the mix of hourly work versus flat fees. Then you had the more recent McKinsey professional services report that said professional service forms are, firms are experiencing, quote, unquote, this is theirs, fundamental pricing model disruption. Yeah. That's what I said. Pricing crisis, fundamental pricing model disruption, Those are synonyms. So up to 40% cost reductions are possible for early AI adopters. So, yeah, it's happening and it's happening now. It hasn't been felt across, you know, all of these industries.
Jordan Wilson [00:16:15]:
Right? Consulting, accounting, law, but it's starting to trickle, and it is going to hit even harder in 2026. Let me just be honest. Cons consultancies are are gonna get hit very hard. We've already seen, significant job loss at the not just the big four, but even the tier after that. You know, essentially, they're cutting down, you know, in in intentionally, firing or laying off, people that are, not going to be in roles in the future that will be able to benefit or use AI. Right? We're seeing, tens of thousands of these cuts at a time. And then at the same token, right, in the past week, Accenture has signed deals with both OpenAI and Anthropic to train tens of thousands of their clients on using the these pieces of software, which is like about time. I've been saying this for for since I started the show that, you you know, these consultancies are gonna have to start using the off the shelf products.
Jordan Wilson [00:17:17]:
First, they're like, oh, we're not gonna touch it. Right? These models are dumb. And then they're like, oh, wait. The models are smarter than us. I think that kind of started to come around, you know, during the reasoning models in early twenty twenty five, the deep research products, products. And they're like, oh, maybe we should pay attention. But now instead, let's build our own models. And they're like, oh, no.
Jordan Wilson [00:17:34]:
Yeah. We just need to use Chad GBT, Claude, Gemini, etcetera. So, also, story that just came out a couple of weeks ago, headline in business insider, AI is reshaping how McKinsey makes money. So, yeah, the big four consulting companies, I think you're gonna see a lot of stories in quarter one, about they're either having to, switch away from billable hours to output base pricing, or they're just gonna be bleeding. Right? Yeah. Unfortunately, I think when we talk about AI's, impact on jobs, I think it's one of the industries that's gonna be hit first. Right? Especially and this is a small thing y'all. Keep an eye on this in 2026.
Jordan Wilson [00:18:17]:
The default based models now are good at just what consultants do. Right? What do consultants do? They look at, you know, they crunch a lot of data from public reports. They find connections between different data points. They identify trends. And then for the most part, they then create spreadsheets that show those things and then create PowerPoints. Guess what now? Claude, especially, the new Opus four five with skills can create better spreadsheets and PowerPoints than 99% of consultants. I said it. I'm probably gonna get some hate mail.
Jordan Wilson [00:18:51]:
Right? And GPT five two, their new model, not far behind, and it does it 10 times faster and probably better than, I'll say, 99% of juniors. Right? You know, not not your senior consultants, your your partners that have been there for, thirty years. But your average entry level worker, and that's also why at consultancies, hiring for new grads is down more than 40% over the past two years for this exact reason because consultants, the big consultancies are like, wait. As they're starting to see these reasoning models, deep research, you know, one click, you know, mini rad, they're like, wait. What are we doing? Right? And when you can see, you know, I've talked to plenty of consultants, over the past couple of years who will honestly tell me off the record, yeah. All I do is spreadsheets in PowerPoints, and now these models are just better. Sorry. So number 21, prediction here was that UBI or universal basic income becomes becomes a mainstream kitchen table topic even if it's not enacted.
Jordan Wilson [00:19:59]:
So this one might have been a little bit more of a miss. However, there is, a current, I I forgot to put it on my slide here. There is a current, proposal, in The US, house, for UBI. And one of the reasons for it, is because of AI job displacement. So this wasn't a complete miss. Obviously, that bill is not going to go anywhere. It doesn't have legs, but an actual bill, was introduced in the US Congress for UBI, and one of the main reasons, you know, a universal basic income. And one of the main reasons was AI job displacement.
Jordan Wilson [00:20:41]:
Not one of the main reasons, but one of the reasons cited. Also, here in Illinois, here in Chicago, you know, there's a an an article that I just read. There was kind of a pilot program here, but let me just read the first, you know, a couple paragraphs from this article. So it says, as artificial intelligence, it's accelerates automation across industries, policymakers are grappling with the economic consequences. AI driven systems are replacing not only repetitive tasks, but also increasingly performing, cognitive work, including decision making analysis and creative functions. The shift threatens traditional employment models, raising urgent questions about income security in a future where machines may outcompete humans in most jobs. Universal Basic Income, UBI, has been proposed as a solution, a policy that provides unconditional cash payments to all individuals to mitigate job displacement caused by automation. Tech leaders like XAI's Elon Musk and OpenAI's Sam Altman have publicly endorsed UBI, predicting that widespread automation will make such policies inevitable.
Jordan Wilson [00:21:48]:
In Illinois, Cook County recently made its guaranteed income program permanent, which allocated $7,500,000 in its 2026 budget to provide 500 monthly payments to thousands of residents. So that's the end of the article. That was for, lower income families. And so there you go. Even though, at least in some of these pilot programs, there's one, in Cook County here, the county that Chicago was in where I live, there's one in New York. Even though, you know, AI is not a main driving factor in news reports and in the conversation that has led up to these pilot programs, obviously, AI has been discussed. So although maybe, UBI has not become a household conversation, It is on the table and people are talking about. Alright.
Jordan Wilson [00:22:37]:
Number 20, open source models surge, and they temporarily overtake proprietary models. Yeah. I literally said it will temporarily overtake proprietary models and guess what happened. Well, exactly that happened. So, you know, one of the biggest ones was the DeepSeek shock. So that was in January. DeepSeek released r one, which was an open weights model, And at the time, the best model in the world was GPT four o. And on many benchmarks, the open source model, beat OpenAI's GPT four o.
Jordan Wilson [00:23:12]:
Obviously, OpenAI, I I believe it was just a couple weeks later, released an update to GPT four o that on most benchmarks, you you know, they kind of reclaimed, that top, that top spot. But this literally happened temporarily. Open models surge, and I think they continue to surge. Right? If you look at the top, 10 models, I believe, right now on LM Arena, you have, depending on the day, anywhere from three to four of them are open source. So they have, and they continue to, at least on certain category, categories of benchmarks, be a top one, two, or three model. Not usually overall. I still think that for the most part, you're always gonna have, Google Gemini or an open AI model, as the top model, especially on, you you know, these aggregate AI benchmarks or LM arena, but we did see it. It did happen.
Jordan Wilson [00:24:12]:
Alright. Next prediction kind of related to that number 19, Chinese AI will dominate and cause confusion. So, very similar, some of the reasoning and rationale from our last one. But 30% of global AI usage right now is Chinese open source models. That's according to an open router study of a 100,000,000,000,000 tokens. So, I'd say that's dominated. To just talk about Chinese open source AI models globally, 30% is a pretty big piece of the pie, and definitely causing confusion. Right? The whole, deep seek debacle of January, right, where they said, oh, we trained this thing for $6,000,000, and, The US stock market lost, more than a trillion dollars in market cap, although they did recover that, pretty quickly.
Jordan Wilson [00:25:06]:
Well, that was obviously not correct because, the according to a semi analysis report, they found that DeepSeek's, infrastructure and development costs were estimated at more than $1,000,000,000. So Chinese AI did open source. AI did dominate, and it did cause a lot of confusion because they were putting out, some, we'll call it half information, misinformation, put out there to intentionally short The US market. Alright. Number 18, perplexity will either pivot, get acquired, or get squashed. In Jan this was not a popular take. Let me say that. Back in January, you know, everyone was extremely, bullish on perplexity as an answers engine.
Jordan Wilson [00:25:52]:
And at the time, I'm like, there's no room for perplexity to be an answers engine only anymore. So I said they're either gonna pivot, they're gonna get acquired, or they're going to get crushed. So I will say this, perplexity did grow. Right? They did not grow at the rate of, you know, their other competitors, but they didn't get crushed. Well, why? Well, I think it's because they actually had a pretty hard pivot. Also FYI, they were, being considered for a, an acquisition, from Apple, just FYI. So the acquisition thing, we got kinda close, but I will say perplexity actually pivoted. I don't think if you look, in a year from now, the Answers Engine business will not be one where perplexity is, a player.
Jordan Wilson [00:26:42]:
And even though they were the first answers engine, they can't compete. They can't compete, with the users, from Gemini Google Gemini is surging. They can't compete, with with Chad GPT even now. Anthropic Claude, you know, has this piece covered, Copilot. Everyone has that piece covered. So perplexity actually had a pretty smart pivot. They were the first, big player to go into the agentic browser space with their Comet browser. They pivoted hard into shopping.
Jordan Wilson [00:27:13]:
They have their finance product, and also an iOS app that brought, their, perplexity assistant that brought AI actions to the phone before Apple's own Apple intelligence. So they had some very smart, and I will say some pretty hard pivots. Right? I wouldn't call it a, you know, a one eighty about face, by any means, but, I think we saw in 2025, perplexity, had to diversify from being just an answers engine just like I called. Alright. Number 17, I said API, prices are gonna be like early two thousands wrap, and they were gonna drop it like they're hot. So my prediction in January, which people scoffed at, that I said, you're gonna have a frontier or near frontier model API prices drop hard, and get below 50¢ per million tokens. And everyone's like, Jordan, you're an idiot. You have no clue what you're talking about.
Jordan Wilson [00:28:11]:
That's, you know, more than 15 x cheaper than what it's currently at. Not possible. Oh, look. Yeah. I was right. Sorry. So two of the top two of the top seven models right now on artificial analysis clock in there. Right.
Jordan Wilson [00:28:28]:
So Kimmy k two thinking, one of the top. I think it's the fourth model on on artificial analysis, which again is an aggregate benchmarker, and and both of these are also top 10, but the their frontier models. Kimmy k two Thinking, fantastic model, clocks in at 60¢, per million, but on cash, it's 15¢. Right? So yeah. Yeah. We hit that there. And then, obviously, a couple of weeks ago, we saw DeepSeq v three two, and this is uncashed at 27¢. Yeah.
Jordan Wilson [00:29:02]:
So, did that. And then on cashed, it's 2¢, FYI. So, yeah, hit that. Everyone thought everyone's like, there's no way there's no way intelligence frontier level intelligence will ever be that cheap. Yes. It is. I don't know what it's gonna be next year. Right? Gotta gotta bust out the, the calculator and spend some time with that.
Jordan Wilson [00:29:23]:
But, I would con I I I would assume, it continues to go down. I mean, even if you look at the, the recent Arc AGI, on on, Arc AGI two, from OpenAI, I think the cost, that they needed to, achieve what they achieved on the Arc AGI test, was like a multitude of 390 times cheaper. So things are getting way cheaper, and fast. Right? So yeah, the, it's gonna continue to drop. Alright. Number 16, embodied AI will be an exploding sector. So my actual prediction was that embodied AI, such as humanoid robots, autonomous vehicles, drones, and wearable AI would be an exploding sector with large scale funding in robotics and drones. Again, talk saying this today probably means nothing because you're like, okay.
Jordan Wilson [00:30:16]:
Duh. It wasn't like this in January. Right? You could say, like, figure in very few people, unless you cared about robotics, knew what figure was. But here's here's the receipts. Here's the reality. So VC funding in robotics and drones soared over 40%, alright, in 2025. Huge huge jumps. I I I mean, categorical leaps there.
Jordan Wilson [00:30:44]:
That doesn't happen. 40% jumps in VC funding doesn't happen. Cathy Wood, you know, obviously, very famous, Ark Invest, said in October that humanoid robots will be the biggest of all AI opportunities. Kathy, welcome to the party. Been saying this for years. Sorry, but just being honest. So figure AI also exceeded a billion dollars in series c funding alone in September at a $39,000,000,000 valuation. So, yes, embodied AI, even though, you know, people weren't talking about it too much, back in January unless you already had a preexisting, interest or specialty or overlap that needed you that you needed to you know, maybe you worked in, you you know, warehousing or logistics, so you had to be familiar.
Jordan Wilson [00:31:36]:
But this is huge. Right? Throw in there, you know, self driving vehicles, which changes logistics and transportation, you know, last mile deliveries, with odd, autonomous, you know, robots, you know, great computer vision capabilities and leaps. Right? I see them on my block all the time in Chicago. Right? Whereas, like, if you would have told me last year that I would see those things every day, I'd be like, no. That's from the future. No. I mean, they're literally out on the streets all the time. So embodied AI not only made a big splash in 2025, you know, and maybe most people weren't expecting it, but I think that splash is going to, go title in 2026.
Jordan Wilson [00:32:17]:
Alright. I think we only have one or two more here, so stick with me. So number 15, just barely missed this one. Dang it. And this was an absolutely outrageous claim at the time. So I said that AI video tools, will be able to one shot five minute HD videos. So I said that you will be able in one prompt to be able to produce a five minute HD video generation. Plus I said that we're gonna have some, advanced personalized media.
Jordan Wilson [00:32:48]:
So did it happen? Not quite. Right? But I wouldn't be surprised if in the last two weeks of December, if we actually get there. If not, we'll get there in the 2026. So while single shot generation is often capped by most of the big providers, between twenty to sixty seconds just due to compute. Technically, it's it's kind of possible in other ways. So one of them is YouTube shorts integrated, Google's VO to allow infinite remixing and stitching. So just by clicking a couple times, you can effectively achieve what I talked about with advanced personalized media, and, five minutes. Right? Just stitching them together.
Jordan Wilson [00:33:33]:
Also worth noting, Disney, just couple days ago, announced a $1,000,000,000 investment in OpenAI, and we are going to be seeing AI videos on Disney plus. So I did talk about that that we're gonna be seeing, AI videos and not even know it. Right? We've seen plenty plenty of stories, that we share in the newsletter, over the last couple of months. The biggest studios in the world are using AI video. As the models get better and better. Right? I wouldn't be surprised if in five years, the majority of everything we watch is just AI generated. It just makes sense. It's cheaper, and it will be better.
Jordan Wilson [00:34:15]:
Yes. AI video will be better eventually than what you can shoot with a camera. Right? Because even what you can shoot with a camera is somewhat limited. Obviously, if you have a billion dollar budget, you know, you can probably do great things. But for the most part, a lot of it is still done, with CGI, with special effects. But, you know, essentially, I think CGI. Right? Any any big production has some sort of CGI. I think it's just replace CGI with just AI video.
Jordan Wilson [00:34:42]:
Right? I think you're gonna have some baseline shooting always, so you can kind of have that to feed the video models. But I'd say the overwhelming majority of everything that we consume, on the big screen in five years will be AI generated. Oh, and we did get very close here because actually, Cling AI does have a feature, called, extend, using the extension feature to get to three minutes with a single prompt. So we just barely missed it. There's technically I could have said, oh, yeah. We hit this. Because there are some other AI video products that you can get up to an eight minute, video from a single prompt, but they're not good. And you can't just do any type of videos.
Jordan Wilson [00:35:25]:
It's only, like, certain, certain types. So I could, like, stretch it and be like, hey. Technically, you can get eight minute, but they're not good and no one would ever use them. But Cling AI, fantastic. One of the top AI, video models in the world. And with one prompt using the extension feature, you can get three minutes. So it stitches together all these different scenes, but you don't have to do it. One prompt, it can do three minutes.
Jordan Wilson [00:35:49]:
So we almost made it. Like I said, I wouldn't be surprised if by the end of the year or early twenty twenty six, we actually get that prediction one correct. Alright. Last one or two here. Let me see. Yeah. Two more. Alright.
Jordan Wilson [00:36:02]:
Here we go. So, number 14, the future of traditional Internet comes into question. So my prediction there was the traditional Internet model, which is ad supported click through traffic, would come into serious question as AI answer engines abstract content away from publishers. Not only that, but just the traditional Internet is just gonna become slop. Right? And I think we've seen that. So a lot of these studies I'm talking about here, I don't believe them, but I do think that they signify the truth. Right? So there's, you know, these studies that say, you know, 90% of new content online will be AI generated by 2026. Yeah.
Jordan Wilson [00:36:42]:
I probably believe that, but you can't technically prove it. There's an a, an HRAS study, in April that found that 74% of, the 900,000 newly created web page, web pages contained AI generated content. Can't technically prove that, but I believe it, if that makes sense. Right? But the the future of the Internet, it's it's not a great place. Right? Or it's it's at least, the future of the Internet or the future of visiting web pages. I think it's it's it's gonna be archaic, in a couple of years. Right? I think everything is gonna be driven by your AI operating system, whatever it is you use. Right? Whether that's, Copilot, whether it's Chad GPT, Gemini, or Claude, I think you're not gonna really browse websites.
Jordan Wilson [00:37:31]:
Right? And I think we're starting to see that also, with ChatGPT apps. It's bringing in the entire experience into, the ChatGPT interface. Right? And sharing all the context and all the data right there. So I do think that eventually browsing the Internet will be kind of like a lost art. I do think eventually I don't know when. I do think eventually most of the new content, that is published online will be just for, large language models and scrapers, not necessarily for humans. If humans discover it, great. But I do think the main reason, will be for large language models to show up in AI search.
Jordan Wilson [00:38:12]:
And also NPR declared this an extinction level event for online publishers, in July. So the reality is, yeah, that one, we hit it. Alright. Last one for part one. Number 13, social media makes deep fake problems worse. Yeah. That's that was the dang truth. So, my prediction there was social media platforms, would make deep fake problems worse in 2025, making misinformation and impersonation significantly worse and harder to spot.
Jordan Wilson [00:38:44]:
So, that one maybe wasn't the riskiest. But at the time, again, remember, the tech wasn't that good. The photo, photos AI photos weren't that good. You know, we didn't have nano banana. We didn't have GBT, image. It was kind of a little harder, right, to create a decent looking, deep fake photo or a deep fake video or even the deep fake audio wasn't the best. Now you can't tell the difference. So, some stats here.
Jordan Wilson [00:39:16]:
Deep fake fraud incidents surged 19% just in the first quarter, of 2025. Also, some deep fake detection research, from iProve found that only point 1% of participants in a study could correctly identify all fake and real media. So, yeah, hardly no one if you look at a series of what's fake and what's real, hardly no one can get it all right. CEO fraud using deep fakes now, according to reports, targets at least 400 major companies every single day. You you have targeted, a listers, celebrities, you you know, that people are using their likenesses, their literal videos to either scam people or to sell products that these celebrities have no, attachment to. I mean, literally, you stories of this every single day, a list celebrities. Someone just, you know, makes them go pitch their product, and they're like, no. I didn't pitch.
Jordan Wilson [00:40:12]:
It's happening all the time. And then, probably one of the more prominent ones as of recently, an AI imposter successfully mimicked the freaking US secretary of state, one of the most, important global positions of any political leader. Right? US secretary of state Marco Rubio's voice was cloned and, an AI imposter, fooled foreign ministers and other officials into believing it was US secretary of state Marco Rubio. Not a good thing. Right? The the the deep fake problems, unfortunately, are only going to get worse. Right? Although you see technology like OpenAI's Sora, in the cameo features as great things, right, as, oh, it's great fun. Yes. And there are some safeguards in place.
Jordan Wilson [00:41:07]:
But usually when good technology is born, bad technology replicates it. And it is going and like I said, it is getting nearly impossible, for even a trained eye to tell the difference between what is real and what is fake. So the reality is it's a problem, and that prediction was obviously correct. Alright. That is a wrap for volume one. So from AI agent orchestrators to deep fakes, the new tech order. So I hope this was helpful hitting rewind on that original roadmap. So let me know.
Jordan Wilson [00:41:44]:
Did I lead you astray? Right. And, and please remember, even though these might not seem like crazy predictions at the time. I'm telling you this now because also kind of pre promoting our 2026, AI prediction and road map series that we're gonna be probably in about one month from now. So, we're probably gonna do the same thing. We're gonna spread it out over five episodes. I'm letting you now know now I've been working on it for months. It is an absolute necessity that you listen in because again, you're gonna listen to the recap of this one in a year and be like, oh, yeah. Duh.
Jordan Wilson [00:42:25]:
You might as well know now. I'm literally laying out the roadmap for you to be more successful using AI, for your company, to be more successful using AI. Not saying, you know, I'm getting it all right each and every time, but I'm making some big bold steps that are gonna help you. So make sure mark your calendars mid January for our 2026, prediction and road map series, and make sure to mark your calendars for tomorrow as we deliver on part two. We're gonna get into numbers 12 through one. It's gonna be an exciting one. Thank you for tuning in. If you haven't already, tell someone about this.
Jordan Wilson [00:43:06]:
If you're listening on the pod podcast, please make sure to follow the show. That helps. Please do that. And if you could, if you find the podcast helpful, please leave us a rating on Spotify or on Apple Music. If you're listening on, the livestream, please repost this on LinkedIn. Other people need to know, and you need to go to your everydayai.com. Go sign up for the free daily newsletter. We'll see you back tomorrow and everyday for more everyday AI.
Jordan Wilson [00:43:31]:
Thanks, y'all.