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Were still in the earliest days of artificial intelligence. It was just November 2022 when OpenAI released ChatGPT, and the world changed. However, enough time has passed for us to have a sufficient perspective to categorize AI and autonomous agents into three distinct eras. Introduction2024: In the initial shockwave, there was more novelty and hype than practicality around the possibilities of AI. Businesses and leaders understandably struggled to understand what was barreling toward them. Evaluation2025: There was a reality check for organizations as they began testing, experimenting with, and piloting AI projects in their search for use cases that created value. For various reasons, businesses often failed to achieve the results they expected or sometimes even saw their efforts completely stall. Production2026: The coming year is when we begin to see a real payoff from business investments as innovative organizations take what theyve learned and seriously embrace AI, embedding agents throughout their operations to realize value. Its an absolute certainty that AI activation will become the story of business. Were witnessing a profound shift from pilots to production agents embedded in real business processes, and its going to explode exponentially as AI adoption enters the mainstream enterprise and delivers measurable ROI. And the stakes will be incredibly high for businesses to get it right. TIME TO SEPARATE HYPE AND ACTIVATION Two things can be true at the same time. We can observe heightened speculation about AI alongside the on-the-ground emergence of agentic capabilities in real-world environments. The massive investments in power generation, data centers, and chip innovation are unlike anything weve ever witnessed. The market cap of hyperscalers is reaching vertigo-inducing heights. Jamie Dimon, the CEO of JPMorgan Chase, frequently references this as a picks-and-shovels moment in a modern gold rush because its the infrastructure that will enable the innovation that comes next. Much of the conversation today focuses on whether were in an AI bubble. That speculation will likely continue, but the real story is what comes next. Were not spending enough time imagining the world that will emerge on the other side of this period of intense innovation, whatever form that transition takes. From a historical perspective, there have been many boom-and-bust cycles that, over the long run, proved beneficial. Ive been in the software industry for nearly three decades, which means I know bubbles firsthand. I began my business career in the 1990s, at the dawn of the Internet era, and experienced the dot-com boom and the subsequent crash. The market disruption was profound and painful. Fast forward to today. Can anyone imagine if we couldnt order a sandwich on our phones and have it delivered in 15 minutes or less? There was an incredible payoff, but that only became apparent over time. Many of the innovations and infrastructure built in that era laid the groundwork for the world we live in today. We need to focus on the long game because AI will improve our lives immeasurably. In moments of rapid technological change, the broader environment typically undergoes significant shifts as innovation accelerates. Whats unmistakable, however, is that the future belongs to companies that view AI not simply as a tool, but as a game-changing intelligence thats omnipresent in everything they do as they deliver for their customers. Its why I remain so optimistic about the impact AI will have on all of us. PREDICTIONS FOR 2026 This will be the most productive year in history, as concerns about AI replacing humans fade and the technology instead augments people, enabling them to perform their jobs more effectively and improving their lives. Trust in AI. The level of confidence businesses place in AI to help them run their organizations will increase as they adopt measures that emphasize greater governance and data accuracy. AI translates to ROI. This relates directly to trust. Weve already begun to see it, but the growth in real business value (substance, not hype) will happen as we move beyond simplistic AI co-pilots to agentic solutions that become integral to making businesses and people more productive. As more agents enter production, it will inevitably lead to sprawl. A mindset shift toward agent governance will be crucial to delivering the greatest return. Race toward AGI. We will reach peak intensity in the development of artificial general intelligence. I expect well see announcements and investments that advance ambitious research initiatives across the field. Flood of mergers and acquisitions. As the pressure to adopt AI intensifies, companies that havent kept pace with innovation will be forced to explore new ways to advance their technology roadmaps. We can expect to see more organizations pursuing partnerships and selective acquisitions to strengthen their AI position. Its going to be a busy year. WHAT WILL DEFINE 2026 Weve reached the long-heralded moment of divergence between the AI natives and the AI nots. There will be a gap. It will be wide. And it will become painfully clear which category businesses fall into this year. The pressure will grow on CEOs and the board of directors to make AI activation their top technology investment priority. That means stopping experimentation and expecting production results. Businesses cant afford to fall so far behind that they cant catch up. The question for you in 2026 is this: What kind of foundation are you building in your business so that AI becomes a competitive advantage? Steve Lucas is the chairman and CEO at Boomi.
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In 2023, the science fiction literary magazine Clarkesworld stopped accepting new submissions because so many were generated by artificial intelligence. Near as the editors could tell, many submitters pasted the magazines detailed story guidelines into an AI and sent in the results. And they werent alone. Other fiction magazines have also reported a high number of AI-generated submissions. This is only one example of a ubiquitous trend. A legacy system relied on the difficulty of writing and cognition to limit volume. Generative AI overwhelms the system because the humans on the receiving end cant keep up. This is happening everywhere. Newspapers are being inundated by AI-generated letters to the editor, as are academic journals. Lawmakers are inundated with AI-generated constituent comments. Courts around the world are flooded with AI-generated filings, particularly by people representing themselves. AI conferences are flooded with AI-generated research papers. Social media is flooded with AI posts. In music, open source software, education, investigative journalism, and hiring, its the same story. Like Clarkesworlds initial response, some of these institutions shut down their submissions processes. Others have met the offensive of AI inputs with some defensive response, often involving a counteracting use of AI. Academic peer reviewers increasingly use AI to evaluate papers that may have been generated by AI. Social media platforms turn to AI moderators. Court systems use AI to triage and process litigation volumes supercharged by AI. Employers turn to AI tools to review candidate applications. Educators use AI not just to grade papers and administer exams, but as a feedback tool for students. These are all arms races: rapid, adversarial iteration to apply a common technology to opposing purposes. Many of these arms races have clearly deleterious effects. Society suffers if the courts are clogged with frivolous, AI-manufactured cases. There is also harm if the established measures of academic performancepublications and citationsaccrue to those researchers most willing to fraudulently submit AI-written letters and papers rather than to those whose ideas have the most impact. The fear is that, in the end, fraudulent behavior enabled by AI will undermine systems and institutions that society relies on. Upsides of AI Yet some of these AI arms races have surprising hidden upsides, and the hope is that at least some institutions will be able to change in ways that make them stronger. Science seems likely to become stronger thanks to AI, yet it faces a problem when the AI makes mistakes. Consider the example of nonsensical, AI-generated phrasing filtering into scientific papers. A scientist using an AI to assist in writing an academic paper can be a good thing, if used carefully and with disclosure. AI is increasingly a primary tool in scientific research: for reviewing literature, programming, and for coding and analyzing data. And for many, it has become a crucial support for expression and scientific communication. Pre-AI, better-funded researchers could hire humans to help them write their academic papers. For many authors whose primary language is not English, hiring this kind of assistance has been an expensive necessity. AI provides it to everyone. In fiction, fraudulently submitted AI-generated works cause harm, both to the human authors now subject to increased competition and to those readers who may feel defrauded after unknowingly reading the work of a machine. But some outlets may welcome AI-assisted submissions with appropriate disclosure and under particular guidelines, and leverage AI to evaluate them against criteria like originality, fit, and quality. Others may refuse AI-generated work, but this will come at a cost. Its unlikely that any human editor or technology can sustain an ability to differentiate human from machine writing. Instead, outlets that wish to exclusively publish humans will need to limit submissions to a set of authors they trust to not use AI. If these policies are transparent, readers can pick the format they prefer and read happily from either or both types of outlets. We also dont see any problem if a job seeker uses AI to polish their resumes or write better cover letters: The wealthy and privileged have long had access to human assistance for those things. But it crosses the line when AIs are used to lie about identity and experience, or to cheat on job interviews. Similarly, a democracy requires that its citizens be able to express their opinions to their representatives, or to each other through a medium like the newspaper. The rich and powerful have long been able to hire writers to turn their ideas into persuasive prose, and AIs providing that assistance to more people is a good thing, in our view. Here, AI mistakes and bias can be harmful. Citizens may be using AI for more than just a time-saving shortcut; it may be augmening their knowledge and capabilities, generating statements about historical, legal, or policy factors they cant reasonably be expected to independently check. Todays commercial AI text detectors are far from foolproof. Fraud booster What we dont want is for lobbyists to use AIs in astroturf campaigns, writing multiple letters and passing them off as individual opinions. This, too, is an older problem that AIs are making worse. What differentiates the positive from the negative here is not any inherent aspect of the technology; its the power dynamic. The same technology that reduces the effort required for a citizen to share their lived experience with their legislator also enables corporate interests to misrepresent the public at scale. The former is a power-equalizing application of AI that enhances participatory democracy; the latter is a power-concentrating application that threatens it. In general, we believe writing and cognitive assistance, long available to the rich and powerful, should be available to everyone. +The problem comes when AIs make fraud easier. Any response needs to balance embracing that newfound democratization of access with preventing fraud. Theres no way to turn this technology off. Highly capable AIs are widely available and can run on a laptop. Ethical guidelines and clear professional boundaries can helpfor those acting in good faith. But there wont ever be a way to totally stop academic writers, job seekers, or citizens from using these tools, either as legitimate assistance or to commit fraud. This means more comments, more letters, more applications, more submissions. The problem is that whoever is on the receiving end of this AI-fueled deluge cant deal with the increased volume. What can help is developing assistive AI tools that benefit institutions and society, while also limiting fraud. And that may mean embracing the use of AI assistance in these adversarial systems, even though the defensive AI will never achieve supremacy. Balancing harms with benefits The science fiction community has been wrestling with AI since 2023. Clarkesworld eventually reopened submissions, claiming that it has an adequate way of separating human- and AI-written stories. No one knows how long, or how well, that will continue to work. The arms race continues. There is no simple way to tell whether the potential benefits of AI will outweigh the harms, now or in the future. But as a society, we can influence the balance of harms it wreaks and opportunities it presents as we muddle our way through the changing technological landscape. Bruce Schneier is an adjunct lecturer in public policy at Harvard Kennedy School. Nathan Sanders is an affiliate at the Berkman Klein Center for Internet & Society at Harvard University. This article is republished from The Conversation under a Creative Commons license. Read the original article.
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Layoffs are at an all-time high since 2009, and we’re also experiencing the lowest hiring on record in the job market. But AI spending is also reaching all-time highsespecially among Big Tech companies, who are on an extravagant spending spree. As I recently reported, Alphabet, Meta, Microsoft, and Amazon are forecast to drop a staggering $650 billion on AI in 2026 alone. And while many companies are pouring a lot of that moneywe’re talking hundreds of billionsinto building massive data centers, hoping to establish a long-term strategic advantage in the AI arms race, many are still hiring workers for jobs that utilize AI skills. So, what are those skills? While many people assume the most in-demand AI skill is coding, according to a new report, it’s actually not. Here’s a look at what recruiters and companies are looking for right now. The most in-demand AI skills A recent report from online freelance marketplace Upwork found that the AI skill for which hiring is growing fastest is AI video generation and editing (a type of design and creative work). Demand for that skill is up over 329% year over year (YoY). That refers to the ability to use AI tools to cut down on time by generating and editing video content from text, images, or audio. Some of the other AI skills that are most in demand include the following (by category): Coding and web development: Artificial intelligence integration is up 178%. Data science and analytics: Data annotation and labeling is up 154%. Customer service and admin support: E-commerce management is up 130%. Design and creative work: AI image generation and editing is up 95%. Job skills are foundational, not replaceable “While the World Economic Forum estimates that 39% of workers skills will be transformed or become redundant by 2030only a small share of complex tasks can be fully automated by todays AI,” according to the report. While workers are increasingly concerned about being displaced by AI, Upwork’s findings show companies still rank talent acquisition and retention as their top strategic priority (consistently ahead of innovation and technology adoption). This means that instead of replacing workers with AI, businesses are still prioritizing adaptable and agile learners slightly ahead of those who can build or understand AI tools (at least, for now).
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