Scott Olster

The AI workforce is changing everything -- not just turning the traditional SaaS model on its head but also redefining the very essence of service, forcing the reversal of the SaaS acronym from Software-as-a-Service to Service-as-a-Software, with the software now doing a full job.   In their insightful blog post, "The AI Workforce is Here: The Rise of a New Labor Market," venture capitalists Pete Flint and Anna Piñol of NFX argue that AI is not just a tool but a revolutionary force that merges software and labor into a colossal market, especially when software can both organize and execute tasks. The new AI Workforce intersects the $5.5 trillion labor market and the $230 billion B2B SaaS market.   Flint and Piñol offer two approaches to “AI Workforce” companies: AI Colleagues and AI Vendors. The former is seen as selling into an existing job description, like an AI programmer or sales agent. The latter is described as either replacing BPO (e.g., customer service) or creating a new services firm from a fragmented industry (e.g., a full-stack AI law firm).   WorkFusion is a prime example of a company that has successfully introduced AI colleagues/agents. In 2022, WorkFusion introduced its AI Digital Workers, which help banking and financial services organizations fight financial crime by doing complete end-to-end level 1 analyst jobs to automate anti-money laundering (AML) compliance operations.   As opposed to technology like RPA that simply automates tasks, WorkFusion’s AI agents do a full job complete with decision-making -- and working side-by-side with human analysts. Simply put, the goal is to increase the capacity of compliance organizations with AI agents to automate low-level, mundane work so that humans can work on deeper investigations to catch the bad guys.   Staffing challenges plague many compliance organizations and are of particular concern for regulated industries that must comply with stringent regulations. With AI Digital Workers, attrition and volume spikes have zero impact on operations, and analysts can spend 90 percent more time on challenging and rewarding work.   WorkFusion has even personified its AI agents with human names like Evelyn, Tara, Issac and Kayla ... and given them faces using actors so that the team can accept them as colleagues.   WorkFusion’s AI Digital Workers, which now include GenAI, are integrating into the workforce at more than 60 banks, including three of the five top in the U.S., and renowned institutions like Deutsche Bank and BMO (Bank of Montreal). https://lnkd.in/eNKuiHyx   #AI #artificialintelligence #GenAI #SaaS #ServiceasaSoftware #digitalworkers #futureofwork

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Since our last State of the Press Release Report, we've seen a shift in how pros are leveraging tech like AI. 🤖  Curious to see how your peers are using AI in press release creation? Our new report dives into the latest press release trends across the industry: https://lnkd.in/eUPwYG2V 💬 Let's chat: What are some of the biggest changes you've seen in PR in recent years? #PR #comms #pressrelease #AI #contentmarketing

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NAVER Corp launches 'Short Content,' an #AI-powered recommendation service using #HyperCLOVA X. InIt initially focuses on five topics and initially focuses on five topics, plans to expand. #Content #Discovery https://lnkd.in/g9QQhPDW

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Open Data Science Conference (ODSC) East 2024 provided a glimpse into AI advancements, but also words of caution against biases and potential for algorithmic harms. Learn some of the ways experts advocate for human-centric approaches in the midst of our AI boom. Applause #datascience #ethicalAI #largelanguagemodels #digitalquality https://lnkd.in/dt7Uh5PM

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For decades, internet politics has been shaped by a cyberlibertarian perspective that obsessed about government while enabling the corporate dystopia we live in today. If we want a better internet, we must abandon that perspective and reclaim sovereignty over digital technology. #techindustry #brazil #socialmedia #twitter #telegram #digitalsovereignty

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I just can't stop thinking about Nasrudin Hodja's lamppost story. Now, explicit knowledge is easy to access. The entire AI industry is based on explicit knowledge (esp, written knowledge). Nasruddin's warning: explicit knowledge = lamppost. Tacit knowledge = where the key lies. (Image: Tinkle)

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For this Friday's (Aug. 16, 12noon ET) recording of the DOS Won't Hunt podcast, I am looking for panelists who are hiring managers and IT team leaders. Financial Times recently ran a story on how the flood of AI-generated job applications inundate hiring managers. Let's talk this Friday about what this means for IT teams. How can hiring managers sift through CVs of potentially questionable quality and veracity? How can IT leaders be sure they see job candidates who have the actual skills they need on their teams? Whiplash shifts in tech, especially AI, affect what enterprises want in terms of skills to help the organization grow--is that same tech getting in the way of the search for such talent? Potential guest panelists, please contact me ASAP: [email protected]

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From the always excellent #WSJCIO Network: Business technology leaders are winding down two years of fast-paced artificial intelligence experiments inside their companies, and putting their AI dollars toward proven projects focused on return on investment. While technology leaders previously had the blessing of corporate leadership to freely experiment with AI, “the window for experimenting is mostly behind us now,” Erik Brynjolfsson, co-founder of research and software company Workhelix, said Monday at The Wall Street Journal CIO summit in New York. To get over the experimentation hump, businesses need to ensure there is widespread access to corporate data so that technology builders can use it to implement AI, said Jim Siders, CIO of data analytics company Palantir Technologies. “That’s how you get to the workable prototype that you know is fit for purpose, that you know will move the needle on the business,” he said. One way to tell if the needle has moved: AI-based tools must be able to prove their worth in less than 12 months, said Nicholas Parrotta, chief digital and information officer and president of digital transformation solutions at HARMAN International. That can be measured by either higher employee productivity or revenue generation, he said. Another option: breaking down AI initiatives into smaller chunks that are more easily proven out, instead of approaching them as a “big, monolithic” beast, said Naveen Rao, vice president of generative AI at cloud data firm Databricks,Rao said. That means getting to the point where AI projects can be treated as computer code that simply needs maintenance. Great coverage from Thomas Loftus, Belle Lin and Isabelle Bousquette. Excellent panels with Christopher Mims, Asa Fitch, Ben Ashwell and so many more.

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