ثورة الذكاء الاصطناعي: من راحة الحجاج إلى تحول البنوك والموظفين

<a href="https://news.google.com/rss/articles/CBMi2gJBVV95cUxPdkRpMURjVXJodXZ4QXM0QjhrTkRlMV9sRFlncDdPQ0ZZanpJTW52ek82YXZsbmkxdlNEcFFReGZmVjZuM3VVcDlGc2tWVHVBRVZYWTlYbjZLRkt4TTdBb2gwZmViTUZYc2x6ZGgxWTJEN2kydEQ1Unhzd2pQeFR6Y0R6Y0FRUXI4T0pTTmZLdlRFUDlDQTJhU0N5LVZpc1lrLVpXX1dPN0E3QzNST0ZYcm9pRklkQ0NKRUlCWXFqODlMeENHSE5kUlJOc2w3TEl3QTM2QW1ienBHM0t5QlVVUlZoZ1Z3bEVfcENTZ2hWeWVCZlhVSUtFRmVGdVVZc3h0MVFrdFYwZTZhajBEYndkX3MycHk2eUVVTmxVeF9CZXRpYWhIandmVmNUMTEzNjJyeEkzVHZRelNGRExvSkJnZE16UWRUN3pzUWVlaHpsQVRuNmx5Qi14MXNR?oc=5" target="_blank">ثقة عالمية متزايدة.. السعودية تعتمد الرقمنة الشاملة لضمان راحة الحجاج</a>&nbsp;&nbsp;<font color="#6f6f6f">صحيفة الوئام</font>

Alexandra Mousavizadeh said banks are all racing to make sure engineers are up to speed on AI. Alexandra Mousavizadeh said banks are all racing to make sure engineers are up to speed on AI. Evident Alexandra Mousavizadeh said banks are all racing to make sure engineers are up to speed on AI. Evident AI is no longer optional at banks. The road map, and showing how it pays off, is the hard part. Alexandra Mousavizadeh, the cofounder and co-CEO of Evident, which tracks AI use in the financial industry, said some AI capabilities are "table stakes" for banks at this point — think back-office functions like reviewing legal documents and routine onboarding tasks. Beyond that, though, Mousavizadeh banks need to double down on their "competitive edge." "If you've got a big chunk of your business in a certain area, the banks will double down on AI there," she said. For firms with a big wealth management business, that might mean helping advisors better analyze client data; for banks more focused on retail, it might mean prioritizing chatbots and customer engagement. Banks are pouring billions into AI, and the technology is expected to redefine 44% of the work done there by 2030, according to consulting firm ThoughtLinks. JPMorgan, which has snagged the top spot in Evident's ranking of AI maturity, has invested at least $2 billion into the technology and is rolling out tools across its more than 300,000-person workforce. Some investors and analysts are starting to wonder about the returns, though. On their latest earnings calls, executives at several bulge-bracket banks fielded questions about when AI-driven productivity and revenue gains will start showing up on balance sheets. Banks are under pressure to show that AI is helping them gain an edge. Mousavizadeh said banks that have taken a "centralized" approach to technology decisions are often able to move faster and embed AI more seamlessly. Her comments on focusing on building AI into core areas of the business echo those of Dan Priest, the chief AI officer at consultancy PwC, who previously told Business Insider that companies that took a "crowdsourcing" approach to AI adoption had a "fairly disappointing" return on investment. Priest said a shift to a "top-down" approach has been more effective, allowing clients to focus on fewer tools and achieve deeper mastery of a smaller set of tasks. AI agents are top of mind as banks race to prove that their AI spend is worthwhile, but Mousavizadeh said the uptake is still in its early stages, particularly in externally facing roles, like bankers and traders. In those cases, agents will likely be combined with humans for the foreseeable future, as banks, some of the most highly regulated companies, work through what guardrails to install. For the past six months, Goldman Sachs has been working with Anthropic on co-autonomous AI agents that can automate tasks in the firm, including accounting for trades and transactions, and client onboarding. The bank's tech chief anticipates that the agents will launch "soon," and that it's too early to think they'll lead to job losses, CNBC reported. How banks are measuring AI wins Over the past year, banks have shifted how they measure AI success, Mousavizadeh said, moving away from tracking specific use cases toward scaling capabilities. They're thinking about how to apply capabilities in one line of business to others, and build an internal "architecture" that allows AI to reconfigure workflows companywide. Achieving that scale requires a combination of top-down and bottom-up approaches. Banks need to get technology into every employee's hands, Mousavizadeh said, and mandatory training often yields better results. But mandates alone likely aren't enough. "AI is a funny thing. You do need a culture where there's a lot of creativity," Mousavizadeh added. Looking ahead to the AI-integrated future, Mousavizadeh said that banks have a new "North Star": what does a fully AI-integrated bank look like a few years from now? "You need to be able to work back from that," she said. More than applying AI to preexisting products, that means creating new systems in the image of the bank of the future — and doing it faster than your competitors.

Daniel Yanisse, CEO of Checkr, is making all non-technical staff try vibe coding with AI days and stipends. Daniel Yanisse, CEO of Checkr, is making all non-technical staff try vibe coding with AI days and stipends. Harry Murphy/Sportsfile for Web Summit via Getty Images Daniel Yanisse, CEO of Checkr, is making all non-technical staff try vibe coding with AI days and stipends. Harry Murphy/Sportsfile for Web Summit via Getty Images If you work for a San Francisco startup and don't know how to code, you could soon be asked to get creative with vibe coding. Checkr, an AI-powered background check company, gave Business Insider a glimpse of how employees are actually using AI. Checkr CEO Daniel Yanisse said that the company is going "all in" and trying everything to encourage its employees to fully embrace AI — including staff that don't work in engineering roles. "We really pride ourselves on using AI to the maximum possible amount," said Yanisse. "We gave every employee a monthly stipend to try AI tools, and we did AI days and demos. After one year, 95% of the employees use prompting daily." "This year, we're going to level up and move to building with AI, as in vibe coding," Yanisse added. "I'm working with all of our teams now, and we're going to do our AI days soon in March, where we're going to make every non-technical person vibe code their own business apps." Yanisse said that many employees who have no idea how to code, who work in finance, legal, and HR, are already vibecoding apps to automate their workflows and problem-solve, such as building tools that help clean up large spreadsheets. While Checkr is evaluating a variety of builder tools like Lovable, Replit, and Claude Code, Yanisse said Cursor is a clear standout and "has amazing adoption" among both engineers and non-technical staff, but Lovable is the best place to start for people with no coding experience. "Probably, we're going to buy all of them and just use the right tool for the right person," Yanisse said of different AI coding tools. "We have AI solution engineers who are available to actually partner and help, so they would come and help you and unstuck you if you have a problem, and take you all the way to success," Yanisse added. "And then you're on your way because then we share success stories with everyone in the company." AI adoption in some companies can be complicated In practice, data shows that AI adoption can be complicated in a large enterprise. Competence with AI tools can be very uneven across the board, and security risks can mount without clear guidelines on AI usage. According to a survey published in November by Moveworks, an AI-powered platform that automates IT and HR support, most executives said that non-technical employees are playing a bigger role in driving AI use, and that 78% have seen successful AI projects originate directly from support staff looking to solve daily challenges. The National Cybersecurity Alliance also wrote in its Annual Cybersecurity Attitudes and Behaviors Report that AI adoption has surged to 65% globally as of the end of 2025, but more than half of these AI users never received any training in privacy and security risks. The report surveyed over 6,500 workers worldwide. "A few years ago, most businesses were still debating whether AI was something they really needed," Louis Riat-Bonello of Optisearch, an AI-powered marketing platform that specializes in SEO, told Business Insider. "The businesses getting the best results aren't blindly chasing automation. They're using AI to support smarter decisions, move faster, and free up teams to focus on strategy and creativity," Riat-Bonello added. "That balance is what will matter long after the hype fades." Yanisse said that in the age of AI, the company is looking for creative and adaptable people, because while AI will eliminate some roles, it will create others. "We are constantly training and helping people update their skills and careers," said Yanisse. "The job of the product designer and the job of the marketer are all completely shifting right now." "We're over 900 people, so we're not a small startup, but I'm a startup guy, and I'm a builder," Yanisse added. "The people who come here need to be OK with uncertainty, be self-driven, adaptable, flexible, willing to do new things, and solve new problems without too much guidance or structure."

Some Google employees took several years to pivot into AI roles. Some Google employees took several years to pivot into AI roles. Mason Trinca/Getty Images Some Google employees took several years to pivot into AI roles. Mason Trinca/Getty Images Pivoting to an AI job may be trendy, but that doesn't mean it's an easy feat. As AI-related roles continue to pop up and companies invest heavily in upskilling, more workers are looking to add "AI" to their job titles. To see how it can be done, Business Insider spoke with five Google employees who transitioned to AI teams. While each followed a different path, many spent a year or so building the necessary skills to land new roles — and for some, the transition took several years. From participating in employee hackathons to becoming AI content creators, the five Googlers share how they made the shift: Emrick Donadei Emrick Donadei is a software engineer working on AI and machine learning safety. Emrick Donadei Emrick Donadei said he didn't feel qualified to pivot to an AI team until he participated in Google's seven-day employee hackathon in 2024. The 32-year-old engineer said he didn't create a revolutionary product, but it gave him hands-on experience with tools, and something tangible he could use to start conversations with teams across the company. Roughly 10 months after his first hackathon, he said he landed his new role. While the hackathon kick-started his transition, his work didn't stop there. The Googler continued to experiment with tools outside the hackathon, he said. He also created a podcast about AI developments and watched Andrej Karpathy's YouTube videos to get up to speed on machine learning concepts and LLMs. After finding a new role, Donadei said that he participated in another hackathon in 2025, which opened up even more opportunities. He had the opportunity to transition into AI research, began working part-time on open-source committees and with AI research teams, and published a public technical disclosure with Google as a follow-up to his work. Maitri Mangal Maitri Mangal switched to the Workspace AI team at Google. Maitri Mangal Maitri Mangal, 27, worked as a traditional software engineer before transitioning to an AI team. During the roughly year-long period she took to prepare for the pivot, Mangal dedicated roughly two hours daily toward up-skilling, and she still spends hours learning weekly, she said. She said that creating social media content was a way for her to reinforce the material that she learned through Google's internal training and other online courses. "That really, for me, changed everything," Mangal said about content creation. She said seeing that her content helped other people motivated her to continue learning about the technology and making videos. Even though she already changed jobs, she said she still spends about an hour daily learning new information, whether that's in the form of internal trainings for her job, or watching YouTube courses to prepare for content. Rahul Kasanagottu Rahul Kasanagottu now works as a customer engineer at Google, specializing in AI and machine learning. Rahul Kasanagottu Rahul Kasanagottu, 32, spent two and a half years transitioning to an AI role at the tech giant. He said his paternity leave gave him a head start on reading about AI. In addition to reading 11 books on the topic, Kasanagottu also took a Deep Learning Specialization course taught by Andrew Ng, and watched 3Blue1Brown videos on YouTube. Similar to Donadei, Kasanagottu said solo projects were a key part of his career transition. He said it was difficult to convince hiring managers he could do the job without having demos and hands-on projects to show. While the books he read typically didn't come with assignments, the courses had a lot of hands-on exercises, Kasanagottu said. Milica Cvetkovic Milica Svetkovic landed a role in AI consulting at Google after getting her Master's in statistics. Milica Cvetkovic Milica Cvetkovic took a different path than the other Googlers who made internal pivots to AI teams. She landed a role in AI consulting at the tech giant about three years ago, after completing graduate school and conducting research in machine learning. After she received her Master's in statistics, she worked as a machine-learning engineer at a Madison-based startup and simultaneously taught machine-learning boot camps and college-level courses. "Having a skill to talk in a nontechnical way is probably the most valuable skill that I bring," Cvetkovic said. Her move to an AI team at Google was less of a deliberate pivot and more the result of the right opportunity aligning with her background and interests. She said that she realized she didn't want to code anymore, and that's when she came across a consulting role at Google. Cvetkovic said she can't name one single experience that led to her getting the job. Rather, she compared her career journey to training for a marathon. A marathon, she said, is the "celebration of all the work that you've done." "That's literally what my application was. It was just very good fit," Cvetkovic said. Max Buckley Max Buckley completed roughly 40 online open courses. Max Buckley Max Buckley, 38, first landed a role at Google in 2013 as a financial analyst. Now, nearly 13 years later, he's leading an LLM information retrieval applied research team. He told Business Insider that when he first started at the tech giant, his "North Star" was to become a data scientist. So he began taking online courses to make the pivot. From 2013 to 2021, he completed roughly 40 online courses , most through Coursera. He said he didn't have a particularly structured way of going about it, and mostly did them during evenings and weekends when he had time. "I don't think it came at a great cost to me," Buckley said. "I didn't feel like I was stressed out or burnt out, or anything from it." He also returned to school for multiple degrees, including a postgraduate certificate in statistics, a master's degree in Business Analytics, a master's degree in software engineering, and a diploma in Advanced Studies in Data Science. Buckley's transition took years, moving from the financial analysis team to business analysis, to trust and safety, and finally to an engineering team in 2016. He then joined several other teams before landing in his current role. Buckley said he doesn't regret studying finance because it gave him a business perspective, and he still wound up in computer science. Instead of racing to the finish line, he took courses based on his interests and their relevance to his career at the time. He said his résumé reflects that commitment to continuous learning. "That's what I suppose hiring managers or recruiters see in my profile," Buckley said. "That I'm not someone who just gets complacent." Did you transition to an AI role? We want to hear from you. Reach out to the reporter via email at aaltchek@insider.com or through the secure-messaging app Signal at aalt.19.