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AI's growth is taking it from centralized systems into everyday workflows, and the enterprise endpoint is taking on a new role and new risks. At the break, AMD's Magda Petwarden will discuss how enterprises are rethinking security to protect Today's AI enabled PCs.
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Welcome to Tech News briefing. It's Tuesday, March 10th. I'm Isabel Busquette for the Wall Street Journal. Today we're looking at two industries that seemed ripe for AI disruption or maybe even. But so far we're seeing the opposite. First, AI might be the savior local news has been waiting for. Across the country, local reporters are using the tech to cover more stories more deeply, although it's not without risks. Next up, the consulting industry is also getting a boost from AI giants. We're diving into how a flurry of deals between AI labs and large consultancies are mutually beneficial, at least for now. But first, for years, AI has felt like a threat to journalism with its promise to create loads of cheap content online without any human intervention. But it turns out the technology has actually been a boon for local news. Reporters in underfunded and understaffed newsrooms are now using AI to monitor police scanners in town meetings, saving them hours that they say they can now spend on deeper investigative reporting. Across the industry, AI is writing the first draft of an article which a human then edits. Wall Street Journal media reporter Alexander Bruel joins us to talk about how it's all working and what could go wrong. Alex, from your perspective, how much of a game changer is this for these local reporters and these local outlets?
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It depends on the outlet and it depends on the reporter. I've talked to a number of people who say that this is huge. This enables to do better coverage, to write about communities that have long gone uncovered, to potentially do more investigative reporting and cover stories and topics that, you know, they've been wanting to dig into. I talked to one reporter at Axios who covers Des Moines and is looking forward to the time that it's saving her so that she can go out and do more investigative work on water quality issues in the state. And there's a lot of excitement around that time saving and the ability to be able to do some real reporting and to more quickly and efficiently file FOIA requests for public records. And we are starting to see some actual results. One example I thought was very interesting is the Newsquest example. Newsquest is owned by USA Today, the biggest local news business in the country. They said in January they used AI to draft a quarter of the 60,000 stories they put out in Data January, and that is the use of AI to do the first draft of these stories, which are then edited and reviewed by actual human editors. But they say that this is going to lead to the potential hiring this year of more reporters.
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When drafts of stories are being written by AI, there is a lot that can go wrong. So what are some of the risks here or what kinds of fumbles have we seen so far, if any?
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Yeah, there's certainly a risk and overreliance on AI. We saw this in the early days of experimenting with AI in newsrooms. We saw certain publishers using vendors for the creation and curation of content that ended up being wrong or putting errors into stories. So there's a fear there in over relying on AI to do the drafting of stories to taking jobs. There's, you know, also a fear that some of the time saved could be used for more AI slop or, you know, just hey reporter, you now have 10% more time in your day. Go generate more quick stories that aren't necessarily meaningful. So there's a fear that this will just turn into a content engine, you know, in some places as opposed to a means to good journalism.
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You wrote about at least one AI company that has started creating its own local news sites. Curious about what's going on there?
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It's a really interesting company, it's called Nota. And this company works with newsrooms and media companies around the country to help them with their operating system and using AI tools and plugging into systems. But something they're doing as well is they're starting their own local news sites. They are trying to prove out a concept. It's really an experiment at this point. They've built 11 new sites around the country that are managed by two part time bilingual editors who are able to collect and curate data and very quickly turn this data into story drafts and publish these story drafts on topics from weather to local events to more important newsworthy information about what's going on in these towns. And so what they're trying to do is to show that they can use AI for efficiencies and eventually they can generate revenue through traffic and advertising and potentially AI licensing. That revenue can go back into the sites and eventually the hope and the goal is to be able to fund the expansion of these sites and journalists and actual investigative reporting that the bots can't do.
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That was Wall Street Journal media reporter Alexandre Bruel. What are your thoughts on the future of AI powered journalism? If you're a listener on Spotify Be sure to leave us a comment with your thoughts. Coming up, America's largest companies are struggling to get real value from AI, but it's a windfall for the consulting groups promising to help. That's after the break.
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AI PCs are increasingly where sensitive data is acted on in real time. How should enterprise security leaders address that? Here's Magna Petwarden, corporate vice president of Product Management Client business unit at AMD, with some thoughts.
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People are going to use AI PCs and enterprises have to think about AIPCs as a natural extension of their zero trust policies. They have to embrace this idea of security that is distributed versus centralized with sort of a moat built around it. Because there are no more moats.
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It turns out AI does need management consultants after all. Despite fears that AI tools could displace expensive consultancy engagements, the leading AI companies are tapping consulting partners more than ever. Fueling the boom are a host of new partnerships between tech giants like OpenAI and anthropic and consulting firms like McKinsey and Boston Consulting Group, who together promise to bring both the cutting edge tech and the playbook for how to actually deploy it. But is it working? WSJ's Allison Polly joins us to discuss so companies like OpenAI and Anthropic theoretically have great technology. What do they need the McKinseys and BCGs of the world for? And why are they so interested in striking these deals?
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So they have the tech, but they don't have enough engineers or enough people to explain how it works and to get it into all of these companies. So what the McKinsey's and BCGS provide is those client relationships where they've already been working with a ton of companies, they have been part of their workflows. In some cases they know how things work and so they're able to then bring the tech into those companies. So it's not necessarily an exclusive partnership that they have with OpenAI, but they do have access to the OpenAI team, to the resources to be able to say, hey, can you help us figure out exactly how this workflow should work or how we should redesign things for this specific company? So it essentially gives the AI companies a bigger workforce because they have people working on the tech on their behalf.
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And how are the teams and pricing structures set up for these engagements and does it differ from the typical consulting engagements in the past?
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So we don't know the exact details of how the deals were done, but in terms of the pricing structure, yes, it's different. So a lot of the pricing is done based on Outcomes, the firm gets paid partly based on whether there's a specified result. Now what that result is in the age of AI is difficult to determine. So they're kind of figuring that out together. But rather than billing for time and materials or all the resources that they're using, they're billing having these outcome based pricing models where it's very much based on implementing the tech and making sure that the strategy is executed.
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You also reported that a huge number of companies aren't really seeing measurable value yet from AI. Does working with the consultants change that?
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A lot of companies haven't yet seen the returns on AI, including from their work with the consulting firms. So a lot of clients were not really pleased with the results that they were getting and they felt like the consulting firms were learning on the job with the tech. In this case, there is a more direct relationship with the AI companies where in theory, an OpenAI forward deployed engineer, for example, will be working right alongside the consultants to troubleshoot in real time as opposed to the consultants having been trained and then needing to go implement it on their own. So there is some hope that this arrangement will be different or lead to better outcomes for the clients. But yeah, up until this point, lot of CEOs had said in surveys that they haven't really seen a big financial impact from all these AI projects yet.
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Right. So where do you see all this going? Where is the consulting industry going in the next, say few years?
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I think it's going to become more product focused. Where really the consulting firms have to have AI as part of their strategy and the implementation also has to be part of the strategy as well. But not only that, they have to show that, that they have a plan and that there is an outcome that's associated with it. So in the past, consulting firms were able to say here's the strategy, now go ahead and do it and our work here is done. They didn't have to make sure that it succeeded, so to speak. Now the clients need to see results in order to justify the expense. At the same time, I do think that there will be a shrinking of the industry where there won't be as many junior consultants needed to do a lot of this work. Not to say that job will away completely, you just won't need as many of them.
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That was Wall Street Journal reporter Allison Poley. News Corp, owner of the Wall Street Journal has a content licensing partnership with OpenAI. And that's it for Tech News Briefing. If you're a listener on Spotify, be sure to leave us a comment. Today's show was produced by Julie Chang with supervising producer Katie Ferguson. I'm Isabel Busquette for the Wall Street Journal. We'll be back later this morning with TNB Tech Minute. Thanks for listening.
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How can enterprise security leaders protect AI PCs? Here again is AMD's Meghna Petwarden.
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You have to think about security as foundational and not something that comes after the fact and that has to be anchored in hardware. Hardware protecting software is more superior from a security strategy perspective and create sort of an immutable trust even before the operating system drivers and AI models ever load. These protections really create the root of trust for AI enabled workloads so that they can confidently run and as AI moves onto the device, then the more sensitive data and decision making shifts closer to the hardware and that means that software only is no longer sufficient.
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Learn more about how amd protects AI PCs from silicon to software@amd.com this content
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