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Adobe Acrobat evolves beyond PDFs with enterprise search, AI content creation
Adobe on Wednesday unveiled a range of updates to Acrobat, including the ability to turn PDF documents into interactive visual reports and podcasts. And a new Knowledge Base feature connects Adobe’s Acrobat AI assistant to document sources such as Microsoft SharePoint and Google Drive.
It’s the biggest Acrobat update in several years, Adobe said, and highlights the application’s evolution from PDF reader to what the company now describes as an AI-powered document productivity and creativity platform.
Acrobat users open more than 400 billion PDFs in the app each year, Adobe said, claiming 650 million monthly active users as of last year.
Among the new additions is the ability to turn dense PDFs into interactive, visual documents and presentation slides. To create these, Acrobat’s AI assistant scans the selected file, asks questions about the user’s intent, then generates documents charts, images and navigation.
It’s also possible to turn documents and web links into podcast-style audio summaries — similar to capabilities in Google’s NotebookLLM and Microsoft Copilot Notebook. A new Stylize feature can enhance plain-looking documents, applying a template to turn them into “professional deliverables” such as CVs and invoices, Adobe said.
The audio and visual generation features are all available in paid Acrobat plans (Acrobat Studio, Acrobat Express and Acrobat AI Assistant).
Another addition, Acrobat Knowledge Base, lets customers connect the Acrobat AI assistant to a wider range of file types, enabling users to ask questions about information held in documents stored in Microsoft SharePoint and Google Drive, for example.
Acrobat’s Knowledge Base “transforms curated document collections — policies, playbooks, product information, pricing guidance, research — into cited answers available from Slack, Microsoft Teams, Acrobat, and other places employees already work,” Abhigyan Modi, senior vice president for Adobe Document Cloud, said in a blog post.
Adobe also added an Analyzer tool designed to retrieve data from large volumes of documents. This could involve analyzing thousands of contracts or invoices to identify information such as renewal dates and revenue clauses.
That turns information once trapped in files into data that can inform finance, procurement, compliance, and the systems that support them, said Modi.
Analyzer is the more interesting of the two releases, said Mike Leone, vice president and principal analyst at Moor Insights & Strategy. “Knowledge Base is a search product and search products get judged feature against feature. Analyzer is closer to a data product, because that extraction work is what companies currently pay people and pipelines to do,” he said.
“What I’d want Adobe to answer is whether that data can leave Acrobat and land where the rest of the company’s data lives. If it can, this starts competing for real data budget. If it stays inside the app, it’s a very good Acrobat feature.”
Access to Analyzer and Knowledge Base requires an Acrobat Studio for Enterprise subscription. (Adobe doesn’t publish pricing.)
In addition, Knowledge Base includes a credit-based model that places some restrictions on usage, with licensed users allowed up to 1,000 queries a month. Other actions, such as document uploads, queries from Slack and Microsoft Teams, and queries by employees without an Acrobat Studio license, draw varying amounts of Acrobat Studio “shared credits.” Adobe didn’t say how much additional credits cost once a yearly limit is reached.
More information about Adobe’s Knowledge Base credit usage policy is available on Adobe’s website.
Analyzer also includes a credit system that limits document ingestion and attribute extraction.
For enterprise customers, usage-based pricing can add complexity when managing employee access.
“The issue for a broad deployment is that headcount barely predicts usage,” said Leone. “One person pointing it at 10,000 contracts will burn more credits than a hundred people asking the occasional question. Pooling the credits across the whole organization is the right design, because usage on something like this is rarely spread evenly.
“One of the big challenges is that people could very well start rationing themselves because they don’t know what a question costs,” he said. “Or worse, a couple folks use all the credits and everyone else is out of luck. The last thing any organization wants is to pay for a knowledge tool that people won’t use or can’t use.”
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No, AI is not killing jobs for everyone, studies say
A slew of recent studies indicate that AI isn’t dramatically displacing workers. At the same time, there were no indicators that the fast-moving technology is creating a lot of jobs, even as AI skills remain in high demand.
Stanford University researchers in an August study found that any AI-related job declines were concentrated among young workers aged 22–25. But for older and more experienced workers that wasn’t the case.
“Claims of economy-wide AI-driven job losses are not visible in payroll data through June 2026,” the researchers said, citing ADP payroll information. Stanford partnered with ADP to conduct the research.
The decline for young workers is more often related to the automation of some work tasks by AI, as opposed to its use to complement work. In contrast, AI is more often used by experienced workers to augment what they do.
According to the Stanford report, workers between 22 and 25 and employed in jobs highly exposed to disruption by AI are falling behind their older counterparts. Their employment levels in June were about 19% below the same age group in less-exposed occupations. That’s compared to where they would be if both groups had kept pace with each other.
“Experienced workers show no comparable gap,” the researchers said, adding that “this is consistent with recent reports of a worsening job market for entry-level workers.”
Employment of younger workers in AI-exposed jobs fell about 11% from late 2022, while the same age group in less-exposed jobs actually grew about 10%. “For older age groups, we find much less marked differences in employment growth across AI exposure quintiles,” the researchers said.
Stanford, which created a lab last year to study AI’s impact amid heightened fears of the technology’s economic effects, said its numbers were based on available indicators.
AI’s adverse impact on young workers has been well documented, with many of them laid off in the initial wave of AI automation. AI has also suppressed wages for entry-level workers.
AI was cited for 116,175 job cuts in 2026, but that number is declining. The technology was blamed for 3,462 cuts in August, according to data from Challenger, Gray and Christmas.
It’s the “lowest monthly total since December 2025 when 142 cuts were attributed to AI,” the company wrote in a blog entry. The research firm also noted aggressive hiring plans for companies in 2027.
AI is adding value to companies in different ways, and humans are an important part of that process, said Michael Chui, a senior fellow at QuantumBlack, AI at McKinsey. “The night shift is real now,” he said. “People are sending off their agents to write code and checking in the morning.”
MIT late last year established an AI labor index to determine how agents are affecting the workforce. The school’s Project Iceberg looks at how the coordination and interaction with agentic AI changes how work is done.
Despite the disruptions, demand for AI-related talent continues to rise, tech industry consortium CompTIA said last week. About 320,000 job listings in August required AI-related capabilities, a 4.5% increase from July.
AI-related hiring is outperforming the broader tech market, with demand for AI skills up 96% year-over-year, said Kye Mitchell, head of Experis North America, which is part of ManpowerGroup.
“We’re seeing real growth…in marketing management and project management roles, suggesting employers are looking beyond the people building AI to the people applying it,” Mitchell said.
More broadly, the US economy added 162,000 jobs in August, according to US Department of Labor figures released last week. CompTIA noted that tech employment across all sectors rose by 86,000 workers in August.
But within the tech sector, 14,700 positions were cut, CompTIA said.
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Siri AI Recaps? Even if Apple builds it responsibly, others might not
Late-breaking reports suggest Apple has built a new Siri AI ‘Recaps’ feature that summarizes your day for you. The idea sounds great until you recognize that this summary will also include overheard conversations.
Suspending the huge red flag of concern over privacy and data protection for a moment or two, why would this be useful and who is it for?
How it’s supposed to workFirst, it is being described as an Apple Watch feature that will only be available on the latest models: Apple Watch Series 12 and Apple Watch Ultra 4, as these allegedly include secure audio processing hardware. Reading between the lines, that suggests the devices will be able to listen to and process audio on device, which implies that the information won’t need to leave your smartwatch, not even to your iPhone.
The report also says the feature doesn’t make a transcript, nor does it store the audio; it instead gathers key datapoints from what is said to include in the summary, deleting all the remaining information in the process. You can have the feature working all day, on-demand, or only in specific locations. The idea seems to be to provide some kind of actionable summary of events and key conversations that take place during the day. I imagine the subtext is to digitize as much as possible of your daily existence as Apple thinks you will be comfortable with to create the kind of datapoints contextual AI requires if it is going to help with your life.
The case for itThat sounds fine, up to a point — the idea that a digital assistant will be able to recognize key events, moments, and requirements to remind us of them, act on them, or suggest next steps concerning them is certainly a notion that’s gained currency in tech circles. They see it as augmenting human achievement, enabling people to become more productive, more efficient, and capable of doing more with less effort. At least, that’s part of the argument.
What is wrong with that (other than concerns over privacy or a desire not to have one’s entire waking life transformed into a series of datapoints that can be measured, tested, or surveyed by entities outside of our control), right? If you have nothing to hide, you have nothing to fear, at least, not until times change and what didn’t need to be hidden in the past becomes something that must be shrouded in future.
Apple’s privacy defenseApple, of course, has its strong privacy story to lean into as it introduces this surveillance-as-a-service solution; it’s an argument that says it recognizes how this tech can be abused, and wants to deploy it correctly. It will point to that record as it promises its system doesn’t gather data, doesn’t collect it, and doesn’t keep any form of transcript on or off the device. The company should be commended for building a system that works this way, recognizing as it does that the best way to protect confidential information is not to gather it in the first place.
The warningBut what Apple has also done with this new speculated upon — and as-yet-unconfirmed product — is to show us what these tools can already do. Much of this is already visible; take recent news that LG smart TVs constantly collect and upload user data as an illustration of the seemingly egregious ways in which such tech is used. (LG denies the claim.) What Apple shows us is that with AI in the picture, all your waking moments can be collated, curated, analyzed, digitized and rendered into actionable data. Apple may not be doing that, but others will not be equally cautious, so we owe Apple a debt for warning us of what’s at stake.
Though we don’t know whether Apple will actually introduce this new service, the source of the claims is one of the strongest in the industry. What we do know is that the technology required to build systems like this exists, along with AI systems capable of sourcing, sharing, and sifting through that information. What we don’t yet know is how to remove ourselves from the data stack.
Now please subscribe to my daily, human-curated Apple-related news headline feed at The Core, or follow me on BlueSky, LinkedIn, or Mastodon.
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