AI in 2026: Challenging the status quo at work
By Dr. Tim Sandle
Image by © Tim Sandle.
AI is challenging the traditional hierarchies in technology, measurement, and talent. However, many uncertainties remain regarding the future of AI’s impact on business.
In 2026, Andy Sen, CTO of AppDirect, has told Digital Journal how the decentralization and democratisation of AI in business will progress. In particular, Sen envisages an explosion of AI tools and this will mark the end of the ERP era.
However, Sen also suspects that organisations will not be able to measure AI’s impact on the bottom line. Overall, Sen considers the future of AI innovation as talent-fluid – in other words, you no longer need to be an engineer to innovate.
The shift from ERPs to explosion of AI tools
In terms of enterprise resource planning, Sen sees a major contribution coming from AI: “We’re seeing the end of the big enterprise software suite era. While ERPs and similar systems won’t disappear, they’ll become less strategic. The focus is shifting to smaller, flexible AI-driven tools that evolve faster and can better match the pace of business.”
This will be in the form of new offerings. Here Sen foresees: “Expect an explosion of AI products next year – both consumer-facing and internal. Some of these solutions will inevitably overlap or even duplicate each other, but this is a good problem to have. In the early phases of AI development, this abundance of innovation will enable wide experimentation. Eventually, we will reach a point where consolidation makes sense. But for now the trend is clear: decentralized AI tools will outpace centralized systems.”
The ROI of AI in 2026
While firms will invest heavily into AI and expand the number of applications, there will not be any immediate ‘return on investment’. It’s a longer ball game, notes Sen: “In 2026, organizations still won’t be able to measure AI’s impact on the bottom line. Instead, we will see ROI measurement at the project level – how many transactions were AI-assisted, how many contracts were reviewed faster, how many deliveries were automated. With time, those incremental metrics will add up to something more transformative, but we can expect it to be a few more years before AI’s ROI shows up in traditional profit-and-loss terms.”
The future of AI innovation is talent-fluid
A key advantage of AI is with breaking down functional specialisms, observes Sen. As examples: “One of the biggest takeaways from this year is how fast AI is accelerating as its development becomes more decentralized. You no longer need to be an engineer to innovate. People across departments are creating tools that solve problems specific to their work, and that kind of innovation is something we’ve never seen before in enterprise tech.” In terms of how this innovation wave will manifest itself, Sen predicts: “This means the next wave of AI innovation won’t just come from the researchers building frontier models. Some of the biggest success stories will come from people who never saw themselves as ‘AI experts’ but had the outside perspective and imagination to apply it in powerful ways.”
By Dr. Tim Sandle
SCIENCE EDITOR
DIGITAL JOURNAL
November 12, 2025
Image by © Tim Sandle.
AI is challenging the traditional hierarchies in technology, measurement, and talent. However, many uncertainties remain regarding the future of AI’s impact on business.
In 2026, Andy Sen, CTO of AppDirect, has told Digital Journal how the decentralization and democratisation of AI in business will progress. In particular, Sen envisages an explosion of AI tools and this will mark the end of the ERP era.
However, Sen also suspects that organisations will not be able to measure AI’s impact on the bottom line. Overall, Sen considers the future of AI innovation as talent-fluid – in other words, you no longer need to be an engineer to innovate.
The shift from ERPs to explosion of AI tools
In terms of enterprise resource planning, Sen sees a major contribution coming from AI: “We’re seeing the end of the big enterprise software suite era. While ERPs and similar systems won’t disappear, they’ll become less strategic. The focus is shifting to smaller, flexible AI-driven tools that evolve faster and can better match the pace of business.”
This will be in the form of new offerings. Here Sen foresees: “Expect an explosion of AI products next year – both consumer-facing and internal. Some of these solutions will inevitably overlap or even duplicate each other, but this is a good problem to have. In the early phases of AI development, this abundance of innovation will enable wide experimentation. Eventually, we will reach a point where consolidation makes sense. But for now the trend is clear: decentralized AI tools will outpace centralized systems.”
The ROI of AI in 2026
While firms will invest heavily into AI and expand the number of applications, there will not be any immediate ‘return on investment’. It’s a longer ball game, notes Sen: “In 2026, organizations still won’t be able to measure AI’s impact on the bottom line. Instead, we will see ROI measurement at the project level – how many transactions were AI-assisted, how many contracts were reviewed faster, how many deliveries were automated. With time, those incremental metrics will add up to something more transformative, but we can expect it to be a few more years before AI’s ROI shows up in traditional profit-and-loss terms.”
The future of AI innovation is talent-fluid
A key advantage of AI is with breaking down functional specialisms, observes Sen. As examples: “One of the biggest takeaways from this year is how fast AI is accelerating as its development becomes more decentralized. You no longer need to be an engineer to innovate. People across departments are creating tools that solve problems specific to their work, and that kind of innovation is something we’ve never seen before in enterprise tech.” In terms of how this innovation wave will manifest itself, Sen predicts: “This means the next wave of AI innovation won’t just come from the researchers building frontier models. Some of the biggest success stories will come from people who never saw themselves as ‘AI experts’ but had the outside perspective and imagination to apply it in powerful ways.”
AI, language, and the future of work
By Dr. Tim Sandle
Image: — © AFP Drew ANGERER
Generation Alpha’s “brain rot” slang is creating real income opportunities (this is one of the worlds of 2024, as Digital Journal reported). From meme consulting to AI language training, young creators are turning viral words like “rizz” and “skibidi” into digital jobs and new forms of communication currency.
There’s been some buzz recently about Gen Alpha brain rot — words like “skibidi,” “rizz,” and “6-7” that confuse adults and drive teachers mad.
What if this digital slang fluency could actually make money?
From TikTok slang to translation gigs, words are driving income in unexpected ways.
According to the firm Notta.ai bilingual professionals fluent in French top the U.S. pay chart with average salaries of $145,836, followed by Italian ($94,640) and German ($87,814). Meanwhile, popular languages like Spanish, English, and Japanese dominate job openings across tech, customer service, and content localisation.
While most adults dismiss Gen Alpha slang as “nonsense,” it’s shaping how younger audiences engage online. Marketers, teachers, and brands are scrambling to keep up. From “delulu” to “skibidi,” these viral codes are rewriting the rules of digital attention, and the people who understand them are getting paid to translate them.
Fei Chen, financial strategist and CEO ofIntellectia.ai, has a deep insight into how communication, AI, and culture converge in the future of work. Chen has explained this to Digital Journal.
“Language is evolving faster than ever, and the smartest earners are those who learn how to translate culture into opportunity. Whether it’s a foreign language or a viral meme, fluency creates value,” says Chen.
Chen looks at the current trends:
Social Media Copywriting for Brands
Instead of avoiding slang, smart marketers use it strategically by creating captions, ads, and campaigns built around viral words like “slay” or “W” to make brands feel relatable and current. According to digital marketing insights and the rise of AI-native Martech tools, this fusion of human creativity and AI personalization allows brands to connect with each customer as a “segment of one,” driving higher engagement and sales.
“People see ‘Gen Alpha brain rot’ as a problem, but it’s really a new kind of cultural fluency,” Chen explains. “These kids aren’t zoning out because they’re redefining how communication works online. The creators and professionals who can translate that humour and energy into real-world strategy will lead the next wave of creative industries.”
Trend Consulting and Meme Strategy
Freelancers are turning Internet humour into income through the growing meme economy, where brands pay experts to translate viral culture into marketing strategy. According to a report, memes have become powerful tools for engagement and brand awareness.
Trend consultants now use data, social listening, and creativity to craft shareable campaigns that feel authentic to Gen Alpha audiences. These specialists, found on platforms like Upwork and Toptal, blend analytics with humour to help companies stay relevant online while earning a steady income through social media marketing projects.
Content Creation and Monetisation
By building videos around trending slang, memes, or sounds and using AI tools to speed up scripting, visuals, and editing, freelancers can quickly produce high-volume, engaging content that taps into cultural moments. The smartest creators monetize through multiple streams: platform ad revenue, brand sponsorships, affiliate marketing, and merchandise featuring viral phrases.
Some even sell digital products or license original characters inspired by these trends. In today’s fast-moving algorithmic landscape, those who blend cultural awareness with AI efficiency are turning “nonsense” slang into real income and sustainable digital careers.
Language & AI Localisation Jobs
As tech companies race to train smarter chatbots and virtual assistants, AI language trainers and data annotators who understand evolving Gen Alpha slang like “rizz,” “skibidi,” or “fanum tax” are in demand to teach models real-world conversational context.
“Understanding how slang spreads is no longer a fun side note, but rather a competitive skill,” Chen clarifies. “It shapes algorithms, builds communities, and fuels virality. When combined with AI and translation tools, it turns from a local trend into a global opportunity.”
Digital Merch & Meme Products
Entrepreneurs are using print-on-demand sites like Printful and Redbubble to sell apparel and accessories featuring viral words such as “Skibidi,” “Gyatt,” and “Rizz,” while others design digital sticker packs, AR filters, and in-game items inspired by meme culture. Top sellers even gamify their creations through Roblox mini-games or customizable merch where fans can add their favourite phrases.
This trend thrives on speed and authenticity; those who capture a meme’s energy before it fades can earn thousands each month through apparel, digital goods, and affiliate campaigns that mirror Gen Alpha’s chaotic, shareable humour.
Writing & Journalism
Journalists and copywriters can earn through explainer pieces that decode slang for parents and brands, or by producing youth-focused articles and video scripts that use the language authentically. Others monetise by crafting branded content that integrates slang naturally, creating humorous commentary on social trends, or analysing the evolution of Gen Alpha’s digital dialect for media and academic outlets.
“Language has always been the ultimate currency,” Chen concludes. “Whether you’re fluent in French or fluent in TikTok, communication drives connection and connection drives income. That’s the real power of words in today’s digital economy.”
By Dr. Tim Sandle
SCIENCE EDITOR
DIGITAL JOURNAL
November 12, 2025
Image: — © AFP Drew ANGERER
Generation Alpha’s “brain rot” slang is creating real income opportunities (this is one of the worlds of 2024, as Digital Journal reported). From meme consulting to AI language training, young creators are turning viral words like “rizz” and “skibidi” into digital jobs and new forms of communication currency.
There’s been some buzz recently about Gen Alpha brain rot — words like “skibidi,” “rizz,” and “6-7” that confuse adults and drive teachers mad.
What if this digital slang fluency could actually make money?
From TikTok slang to translation gigs, words are driving income in unexpected ways.
According to the firm Notta.ai bilingual professionals fluent in French top the U.S. pay chart with average salaries of $145,836, followed by Italian ($94,640) and German ($87,814). Meanwhile, popular languages like Spanish, English, and Japanese dominate job openings across tech, customer service, and content localisation.
While most adults dismiss Gen Alpha slang as “nonsense,” it’s shaping how younger audiences engage online. Marketers, teachers, and brands are scrambling to keep up. From “delulu” to “skibidi,” these viral codes are rewriting the rules of digital attention, and the people who understand them are getting paid to translate them.
Fei Chen, financial strategist and CEO ofIntellectia.ai, has a deep insight into how communication, AI, and culture converge in the future of work. Chen has explained this to Digital Journal.
“Language is evolving faster than ever, and the smartest earners are those who learn how to translate culture into opportunity. Whether it’s a foreign language or a viral meme, fluency creates value,” says Chen.
Chen looks at the current trends:
Social Media Copywriting for Brands
Instead of avoiding slang, smart marketers use it strategically by creating captions, ads, and campaigns built around viral words like “slay” or “W” to make brands feel relatable and current. According to digital marketing insights and the rise of AI-native Martech tools, this fusion of human creativity and AI personalization allows brands to connect with each customer as a “segment of one,” driving higher engagement and sales.
“People see ‘Gen Alpha brain rot’ as a problem, but it’s really a new kind of cultural fluency,” Chen explains. “These kids aren’t zoning out because they’re redefining how communication works online. The creators and professionals who can translate that humour and energy into real-world strategy will lead the next wave of creative industries.”
Trend Consulting and Meme Strategy
Freelancers are turning Internet humour into income through the growing meme economy, where brands pay experts to translate viral culture into marketing strategy. According to a report, memes have become powerful tools for engagement and brand awareness.
Trend consultants now use data, social listening, and creativity to craft shareable campaigns that feel authentic to Gen Alpha audiences. These specialists, found on platforms like Upwork and Toptal, blend analytics with humour to help companies stay relevant online while earning a steady income through social media marketing projects.
Content Creation and Monetisation
By building videos around trending slang, memes, or sounds and using AI tools to speed up scripting, visuals, and editing, freelancers can quickly produce high-volume, engaging content that taps into cultural moments. The smartest creators monetize through multiple streams: platform ad revenue, brand sponsorships, affiliate marketing, and merchandise featuring viral phrases.
Some even sell digital products or license original characters inspired by these trends. In today’s fast-moving algorithmic landscape, those who blend cultural awareness with AI efficiency are turning “nonsense” slang into real income and sustainable digital careers.
Language & AI Localisation Jobs
As tech companies race to train smarter chatbots and virtual assistants, AI language trainers and data annotators who understand evolving Gen Alpha slang like “rizz,” “skibidi,” or “fanum tax” are in demand to teach models real-world conversational context.
“Understanding how slang spreads is no longer a fun side note, but rather a competitive skill,” Chen clarifies. “It shapes algorithms, builds communities, and fuels virality. When combined with AI and translation tools, it turns from a local trend into a global opportunity.”
Digital Merch & Meme Products
Entrepreneurs are using print-on-demand sites like Printful and Redbubble to sell apparel and accessories featuring viral words such as “Skibidi,” “Gyatt,” and “Rizz,” while others design digital sticker packs, AR filters, and in-game items inspired by meme culture. Top sellers even gamify their creations through Roblox mini-games or customizable merch where fans can add their favourite phrases.
This trend thrives on speed and authenticity; those who capture a meme’s energy before it fades can earn thousands each month through apparel, digital goods, and affiliate campaigns that mirror Gen Alpha’s chaotic, shareable humour.
Writing & Journalism
Journalists and copywriters can earn through explainer pieces that decode slang for parents and brands, or by producing youth-focused articles and video scripts that use the language authentically. Others monetise by crafting branded content that integrates slang naturally, creating humorous commentary on social trends, or analysing the evolution of Gen Alpha’s digital dialect for media and academic outlets.
“Language has always been the ultimate currency,” Chen concludes. “Whether you’re fluent in French or fluent in TikTok, communication drives connection and connection drives income. That’s the real power of words in today’s digital economy.”
By Dr. Tim Sandle
SCIENCE EDITOR
DIGITAL JOURNAL
November 12, 2025
Scientists using laboratory instruments. — Image by © Tim Sandle
Generative AI can process information at incredible speed, but it cannot yet think like a scientist. In biopharma R&D, its real value lies in assisting scientists, automating routine tasks, interpreting data in context, and moving research faster.
AI can add value to science in certain context. This need has led to the emergence of third-generation Electronic Lab Notebooks (ELNs), sometimes referred to as Artificially Intelligent Lab Notebooks (AILNs) – AI-native platforms that go beyond documenting experiments.
Yet there are limitations: Many models often fail to distinguish between a sample and a reagent, and cannot interpret assay results in context or anticipate whether a protocol step is valid or flawed. They know a lot, but do not think like scientists.
This author has demonstrated this when assessing microbiological data in the context where increasing numbers of bacteria is a bad thing, AI has indicated that the growth is good – a conclusion unsuited to the task.
To understand these mixed results in a scientific context, Digital Journal has heard from Andrew Wyatt, who is the chief growth officer at Sapio Sciences.
AI complements, it doesn’t replace
Wyatt says: “In biopharma R&D, however, the question is not simply what AI can do, it is how it should help. Since the release of modern generative AI tools, there has been speculation about whether these systems could one day replace scientists, with suggested use cases ranging from accelerating literature reviews to protocol drafting. While these models are capable of impressive analysis and pattern recognition, they struggle to apply true scientific reasoning, understand experimental intent, interpret results in context, and link data to hypotheses.”
So, what can be done with AI as it currently stands. Wyatt thinks “the real opportunity for AI today is not as a replacement; it is as a complement to the tools and scientists already driving innovation. The issue is not that generative AI models aren’t powerful, it’s that they are designed to be broadly useful across many domains. They are trained using public content and generalised data, not the proprietary, structured, and experimental data that drives biopharma R&D.”
This is because, Wyatt points out: “Generative AI may excel at handling language, but it still lacks scientific fluency. These models often fail to distinguish between a sample and a reagent, and cannot interpret assay results in context or anticipate whether a protocol step is valid or flawed. They know a lot, but do not think like scientists.”
From assistance to agency
On the plus side, Wyatt says: “AI can help streamline repetitive or administrative lab tasks, assist in drafting workflows, and suggest possible interpretations of structured data. For most scientists, decision-making and creative problem-solving are core to their work. There is little appetite and no current need to give that up.”
In terms of examples: “Some of the most impactful AI applications today are focused on accelerating the gap between idea and execution. Rather than automating science itself, AI can reduce the manual burden of tasks that pull scientists away from research. This helps scientists stay focused on the science itself, rather than getting pulled into administrative or technical detail.”
AI can:Translate high-level experiment descriptions into structured steps and protocol templates
Retrieve data based on contextual, natural-language queries, rather than requiring complex filters or forms
Track materials and consumables based on protocol logic
Guide scientists through unfamiliar lab software, reducing the learning curve for new tools
However, Wyatt observes: “To do this well, the AI must not only understand language. It must understand science, and it must be embedded in scientific software that reflects real-world research environments.”
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