Latest news with #AItalent
Asharq Al-Awsat
3 days ago
- Business
- Asharq Al-Awsat
Meta Spending Big on AI Talent but Will It Pay Off?
Mark Zuckerberg and Meta are spending billions of dollars for top talent to make up ground in the generative artificial intelligence race, sparking doubt about the wisdom of the spree. OpenAI boss Sam Altman recently lamented that Meta has offered $100 million bonuses to engineers who jump to Zuckerberg's ship, where hefty salaries await, reported AFP. A few OpenAI employees have reportedly taken Meta up on the offer, joining Scale AI founder and former chief executive Alexandr Wang at the Menlo Park-based tech titan. Meta paid more than $14 billion for a 49 percent stake in Scale AI in mid-June, bringing Wang on board as part of the deal. Scale AI labels data to better train AI models for businesses, governments and labs. "Meta has finalized our strategic partnership and investment in Scale AI," a Meta spokesperson told AFP. "As part of this, we will deepen the work we do together producing data for AI models and Alexandr Wang will join Meta to work on our superintelligence efforts." US media outlets have reported that Meta's recruitment effort has also targeted OpenAI co-founder Ilya Sutskever; Google rival Perplexity AI, and hot AI video startup Runway. Meta chief Zuckerberg is reported to have sounded the charge himself due to worries Meta is lagging rivals in the generative AI race. The latest version of Meta AI model Llama finished behind its heavyweight rivals in code writing rankings at an LM Arena platform that lets users evaluate the technology. Meta is integrating recruits into a new team dedicated to developing "superintelligence," or AI that outperforms people when it comes to thinking and understanding. 'Mercenary' Tech blogger Zvi Moshowitz felt Zuckerberg had to do something about the situation, expecting Meta to succeed in attracting hot talent but questioning how well it will pay off. "There are some extreme downsides to going pure mercenary... and being a company with products no one wants to work on," Moshowitz told AFP. "I don't expect it to work, but I suppose Llama will suck less." While Meta's share price is nearing a new high with the overall value of the company approaching $2 trillion, some investors have started to worry. Institutional investors are concerned about how well Meta is managing its cash flow and reserves, according to Baird strategist Ted Mortonson. "Right now, there are no checks and balances" with Zuckerberg free to do as he wishes running Meta, Mortonson noted. The potential for Meta to cash in by using AI to rev its lucrative online advertising machine has strong appeal but "people have a real big concern about spending," said Mortonson. Meta executives have laid out a vision of using AI to streamline the ad process from easy creation to smarter targeting, bypassing creative agencies and providing a turnkey solution to brands. AI talent hires are a long-term investment unlikely to impact Meta's profitability in the immediate future, according to CFRA analyst Angelo Zino. "But still, you need those people on board now and to invest aggressively to be ready for that phase" of generative AI, Zino said. According to The New York Times, Zuckerberg is considering shifting away from Meta's Llama, perhaps even using competing AI models instead. Penn State University professor Mehmet Canayaz sees potential for Meta to succeed with AI agents tailored to specific tasks at its platform, not requiring the best large language model. "Even firms without the most advanced LLMs, like Meta, can succeed as long as their models perform well within their specific market segment," Canayaz said.
Fast Company
10-06-2025
- Business
- Fast Company
In the AI era, tech talent strategies need a wake-up call
Generative AI has come a long way in a very short time. Since ChatGPT made its debut in late 2022, AI models have rapidly grown more powerful and more useful. Stanford University's latest AI Index reports that AI is now better than humans at classifying images and understanding English. AI has arguably surpassed humans in math, computer coding, and diagnosing medical ailments. And now that companies have experimented with and adopted AI to increase productivity, reduce costs, and shorten the product development lifecycle, it seems highly likely that companies will pivot toward applying these enormous large language models to more practical, more focused, and more profitable business uses. Yet, we've been here before. Despite the hype, companies are already struggling to source talent to manage the AI programs they currently have—much less find workers with the skills to expand their AI usage. The latest study from General Assembly, the education organization I lead, reveals the precarious state of AI talent. Hiring leaders say it's challenging and expensive to source candidates with the right AI skills, even as they're receiving more requests to add AI skills to job descriptions that have little or nothing to do with AI. Three-quarters of HR professionals say their company is hiring AI talent without taking the time to build pipelines of qualified and high-potential candidates. Just as companies are using a 'full steam ahead' approach to develop AI applications and software, hiring leaders are having to adopt a similar strategy just to keep up. But this approach threatens long-term viability and sustainability of talent practices. By reacting to immediate needs rather than charting a long-term course to hiring, training, and deploying the right candidates, companies risk repeating the mistakes of the digital transformation era of the 2010s that continue to cost them to this day. What can they do to avoid that fate? Employers that wish to stay competitive in an AI-driven economy should focus on the need to, in the words of pioneering talent analyst Josh Bersin, 'redesign, reskill, and redeploy people in a world of highly intelligent systems.' That means taking these approaches to recruiting and developing talent: BUILD AN AI-READY WORKFORCE AT EVERY LEVEL OF THE ENTERPRISE There's practically no role today that can't benefit from AI. HR teams can use it to screen candidates and streamline hiring processes. Programmers are using it to develop basic code that serves as a foundation for more complex tasks. Marketers use it to refine copy, generate ideas, and even create visuals. But of course, some fields—and some workers—will take to it more than others. Building an AI-ready workforce means not letting the tech-savvy or the early adopters be the only ones to test out new AI tools. Make AI platforms available to everyone, and make AI training mandatory before the technology advances to the point where it becomes moot for anyone who doesn't know how to apply it in their job. For companies that want AI talent throughout their organization, outside recruitment won't suffice. Companies should rethink and expand their AI training efforts to reach all employees—doing more with what they have instead of looking elsewhere for talent that may not even exist. As AI becomes a strategic imperative across the enterprise, upskilling and reskilling existing employees can unlock the solution to AI talent shortages, equipping the incumbent workforce to use AI to become more productive in their current roles and opening new paths to advancement. This approach has a powerful impact on retention, too: Numerous surveys suggest that employees welcome opportunities to advance their careers and be part of a culture of continuous improvement. RECOGNIZE WHERE AI CAN HELP—AND WHERE IT CAN'T Today, AI is fast becoming a critical copilot in everything from programming to marketing to design. But it's not a replacement for people, and it'll be a long time before it is. The companies that stay ahead of the curve in an AI-driven labor market will be the ones that recognize AI's limitations as much as its advantages, and plan accordingly. That means training your workforce to take a crawl-walk-run approach to implementing AI rather than throwing them into the deep end. The most effective applications of AI at work start with making your existing job more efficient, then progressing to automating tasks to increase scale and accelerate output, and finally, putting those tasks together to create AI-driven processes. The companies whose employees have the skill set to build and manage their own digital employees will stay ahead of those that try to use AI for everything without first understanding how to apply it well. The AI revolution is already making profound changes to how people work. To move forward, we need to build an AI economy that uplifts everyone—employees and companies alike. And that won't be possible in a world where tech talent pools haven't grown any wider or deeper since the digital transformation era. Satisfying current needs and future demands will require a much more holistic approach to talent development in the tech workforce. The race for AI talent is well underway. The ultimate winners aren't charging ahead with no set destination in mind. The companies that come out on top will be the ones that intentionally build and retain qualified AI talent that will put them in the lead and keep them there.
