Latest news with #techIndustry
CNA
3 hours ago
- Business
- CNA
CrowdStrike forecasts second-quarter revenue below estimates
CrowdStrike forecast second-quarter revenue below estimates, signaling soft enterprise spending on cybersecurity products, sending the company's shares down 6.7 per cent in after-hours trading on Tuesday. Higher interest rates and sticky inflation have forced clients to rein in tech spending, weighing on demand for companies such as CrowdStrike, despite an increasing need for robust cybersecurity solutions due to rising threats and ransomware attacks. CrowdStrike also faces stiff competition from other cybersecurity firms including Palo Alto Networks and Fortinet. CrowdStrike expects second-quarter revenue to be between $1.14 billion and $1.15 billion, compared with analysts' average estimate of $1.16 billion, according to data compiled by LSEG.
Forbes
a day ago
- Business
- Forbes
Degrees Vs. Skill Stacks: What Prepares You For The AI Economy?
Will AI skills matter more than degrees? College used to be the default launchpad for success. But in a world increasingly shaped by artificial intelligence, automation, and rapidly evolving industries, that formula is shifting. Today's students—and their parents—are asking a new question: Does a degree still guarantee a future-proof career? The answer is increasingly nuanced. While specific degrees remain valuable, especially in fields such as engineering, healthcare, and data science, a growing number of young people are adopting a "skill stack" approach to education. That means pairing classroom learning with real-world experience—like earning certifications, interning, or launching a business—to create a resume that reflects today's evolving job market. A skill stack refers to a personalized combination of marketable skills, credentials, and experiences that can evolve in response to emerging trends and market demands. For Gen Z and Gen Alpha, that might look like: It's not about abandoning formal education—it's about supplementing it with real-world experience, adaptability, and proof of initiative. The job market is undergoing a significant transformation as employers increasingly prioritize practical AI skills. This shift is evident in hiring practices across the tech industry and beyond, with a growing emphasis on demonstrated expertise and hands-on experience. According to McKinsey's 2024 AI Workforce Report, job postings for AI-related roles grew by 21% as a share of total listings between 2018 and mid-2024, underscoring the surging demand for AI talent with real-world capabilities. Leading companies such as Google, IBM, and Apple are at the forefront of this movement, frequently hiring candidates based on their skills, project portfolios, and industry-recognized certifications rather than traditional degree requirements. Google's career certificates—offered through platforms like Coursera—can be completed in just three to six months, providing a fast, practical pathway into high-demand AI roles. This trend reflects a broader industry consensus: in a rapidly evolving field like AI, up-to-date skills and proven problem-solving abilities are often valued more highly than conventional academic credentials. According to the World Economic Forum's 2025 Future of Jobs Report, AI and big data top the list of most in-demand skills, followed by network cybersecurity and technological literacy. But the most crucial AI skills aren't just technical—they're about working alongside artificial intelligence, not being replaced by it. A study published in Semantic Scholar (2023) revealed that AI skills command a wage premium of 23%, surpassing the value of degrees up to the PhD level. This premium reflects the high demand for professionals who can work effectively with AI systems across industries. The most in-demand AI-adjacent skills include: Technical fluency without deep programming expertise: Understanding how to use AI tools like ChatGPT, Midjourney, or automation platforms rather than building them from scratch. Python programming dominates the skill sets most in demand, with data science, computer vision, and natural language processing (NLP) following closely. Still, students don't need to become machine learning engineers to benefit from AI literacy. Prompt engineering and AI collaboration: Knowing how to communicate effectively with AI systems to generate useful outputs. This skill is becoming as valuable as traditional research or writing abilities. Data interpretation and critical thinking: Creative thinking, resilience, flexibility, and agility are also gaining importance, along with curiosity and a lifelong learning approach—the ability to analyze AI-generated insights and make informed strategic decisions based on them. Human-AI workflow design: Understanding how to integrate AI tools into existing processes to amplify human capabilities rather than replace them. The skill stack approach isn't limited to tech companies—it's reshaping hiring across sectors as AI integration accelerates. In healthcare, medical professionals are increasingly valued for their ability to work with AI diagnostic tools and telemedicine platforms. A nursing degree combined with certifications in health informatics creates competitive advantages that traditional education alone cannot provide. Marketing teams seek professionals who understand both creative strategy and AI-powered content creation tools. Finance firms want employees who grasp traditional principles while leveraging AI for risk assessment and algorithmic analysis. Even manufacturing companies now prioritize workers who combine industry knowledge with AI tool proficiency for predictive maintenance and quality control. This cross-industry demand explains why the skill stack approach is gaining traction regardless of chosen field. The shift away from degree-first hiring isn't happening in isolation. It's driven by several converging forces: Skills become obsolete faster: A computer science degree from 2020 may already be outdated in certain areas, while someone who learned current AI tools last month has more relevant capabilities. Portfolio work demonstrates ability: A GitHub repository showing actual projects, a business that generated revenue, or case studies from internships provide concrete evidence of capabilities that transcripts cannot. Remote work changes evaluation: When hiring for distributed teams, managers care more about demonstrated communication skills and self-direction than where someone went to college. Nearly 70% of recent graduates report needing more training on emerging technologies, especially generative AI, and a majority of employers expect foundational AI knowledge from new hires. For students and parents thinking about how to prepare for an AI-driven future, it comes down to being intentional about what you learn and how you apply it. The strongest approach often combines a college degree with targeted certifications and real-world experience, providing students with both a solid foundation and the flexibility to adapt as technology evolves. Start with foundation skills: Strong communication, problem-solving, and collaboration abilities remain essential. These human skills become more valuable, not less, in an AI-driven workplace. Add technical literacy: Learn to use current AI tools effectively. This doesn't require becoming a programmer—it means understanding how to leverage automation, create effective prompts, and interpret insights generated by AI. Gain real-world experience: Pursue internships, launch projects, or start small businesses that let you apply skills in authentic contexts. Document these experiences through portfolios, case studies, or demo reels. Pursue targeted certifications: Industry-recognized credentials from Google, Amazon, Microsoft, or specialized platforms often carry more weight than general degrees for specific roles. Programs offering hands-on, industry-recognized certifications are increasingly recognized as credible alternatives to formal education. Build continuously: The half-life of specific technical skills is shrinking. Develop the habit of continuous learning and adaptation. Instead of "What's the best major?" parents might consider these questions: The answer isn't to abandon college altogether—degrees still matter in many fields and remain essential for specific career paths. The students who excel are those who view education as more than just a diploma. They approach it with a broader lens, mixing classroom learning with hands-on experience and building specific skills. The AI economy rewards those who can adapt, create, and solve problems in partnership with intelligent systems. Whether that preparation occurs through a four-year degree, intensive bootcamps, certificate programs, launching entrepreneurial ventures, or some combination depends on individual goals and learning styles. What matters most when it comes to artificial intelligence and developing your AI skills is starting early, staying curious, and building a track record of real accomplishments. In a world where change is the only constant, the ability to learn, apply, and create value becomes the ultimate competitive advantage.
The Sun
a day ago
- Business
- The Sun
Major mobile brand is shutting down after 15 years – users warned to take action NOW as urgent deadline nears
A HUGE mobile brand is preparing to shut down for good at the end of June. Users now have less than 30 days to take action if they want to receive the very last update for their phones. 1 LG announced in 2021 that it was closing its smartphone division. Its first Android phone was released more than 15 years ago - although LG's roots in mobile go back even further. LG once held the crown as the world's third-bestselling mobile brand. But the South Korean tech giant struggled to keep up as new rivals emerged including Oppo and Xiaomi, as well as long-established competitors like Samsung. Despite the closure, the company continued to push out important Android updates to existing users. Bosses committed to do it for three years. But that time is now up with the last update due to come out on June 30, marking the very end for LG's mobile business. Affected users will no longer be able to download or install Android updates after that date, making their device more susceptible to cyber attacks. "We would like to extend our heartfelt gratitude towards our customers who have loved and supported LG Electronics mobile products," LG said. "After the termination date, you will no longer be able to use the software upgrade services. "If you wish to use the services, we strongly recommend upgrading your software before June 30, 2025. "Furthermore, as we will no longer provide application updates, you will not be able to download default applications deleted upon initialization." The company's last phone product was the LG Wing 5G which featured a unique two display design with one that swivels. LG's final nail in the coffin also spells the end for the LG Bridge, a piece of software allowing mobile users to update via their PC instead. People have reacted with sadness at the final curtain call for LG's mobile devices. "The loss of HTC and LG phones really stagnated the market," one user wrote on Reddit.
BBC News
2 days ago
- Business
- BBC News
The AI copyright standoff continues - with no solution in sight
The fierce battle over artificial intelligence (AI) and copyright - which pits the government against some of the biggest names in the creative industry - returns to the House of Lords on Monday with little sign of a solution in sight.A huge row has kicked off between ministers and peers who back the artists, and shows no sign of abating. It might be about AI but at its heart are very human issues: jobs and highly unusual that neither side has backed down by now or shown any sign of compromise; in fact if anything support for those opposing the government is growing rather than tailing off. This is "unchartered territory", one source in the peers' camp told me. The argument is over how best to balance the demands of two huge industries: the tech and creative sectors. More specifically, it's about the fairest way to allow AI developers access to creative content in order to make better AI tools - without undermining the livelihoods of the people who make that content in the first sparked it is the uninspiringly-titled Data (Use and Access) proposed legislation was broadly expected to finish its long journey through parliament this week and sail off into the law books. Instead, it is currently stuck in limbo, ping-ponging between the House of Lords and the House of bill states that AI developers should have access to all content unless its individual owners choose to opt out. Nearly 300 members of the House of Lords disagree. They think AI firms should be forced to disclose which copyrighted material they use to train their tools, with a view to licensing Nick Clegg, former president of global affairs at Meta, is among those broadly supportive of the bill, arguing that asking permission from all copyright holders would "kill the AI industry in this country". Those against include Baroness Beeban Kidron, a crossbench peer and former film director, best known for making films such as Bridget Jones: The Edge of says ministers would be "knowingly throwing UK designers, artists, authors, musicians, media and nascent AI companies under the bus" if they don't move to protect their output from what she describes as "state sanctioned theft" from a UK industry worth £ asking for an amendment to the bill which includes Technology Secretary Peter Kyle giving a report to the House of Commons about the impact of the new law on the creative industries, three months after it comes into force, if it doesn't change. Mr Kyle also appears to have changed his views about UK copyright once said copyright law was "very certain", now he says it is "not fit for purpose".Perhaps to an extent both those things are Department for Science, Innovation and Technology say that they're carrying out a wider consultation on these issues and will not consider changes to the Bill unless they're completely satisfied that they work for creators. If the "ping pong" between the two Houses continues, there's a small chance the entire bill could be shelved; I'm told it's unlikely but not it does, some other important elements would go along with it, simply because they are part of the same bill. It also includes proposed rules on the rights of bereaved parents to access their children's data if they die, changes to allow NHS trusts to share patient data more easily, and even a 3D underground map of the UK's pipes and cables, aimed at improving the efficiency of roadworks (I told you it was a big bill).There is no easy answer. How did we get here? Here's how it all started. Initially, before AI exploded into our lives, AI developers scraped enormous quantities of content from the internet, arguing that it was in the public domain already and therefore freely available. We are talking about big, mainly US, tech firms here doing the scraping, and not paying for anything they hoovered they used that data to train the same AI tools now used by millions to write copy, create pictures and videos in seconds. These tools can also mimic popular musicians, writers, artists. For example, a recent viral trend saw people merrily sharing AI images generated in the style of the Japanese animation firm Studio founder of that studio meanwhile, had once described the use of AI in animation as "an insult to life itself". Needless to say, he was not a has been a massive backlash from many content creators and owners including household names like Sir Elton John, Sir Paul McCartney and Dua Lipa. They have argued that taking their work in this way, without consent, credit or payment, amounted to theft. And that artists are now losing work because AI tools can churn out similar content freely and quickly Elton John didn't hold back in a recent interview with the BBC's Laura Kuenssberg. He argued that the government was on course to "rob young people of their legacy and their income", and described the current administration as "absolute losers".Others though point out that material made by the likes of Sir Elton is available worldwide. And if you make it too hard for AI companies to access it in the UK they'll simply do it elsewhere instead, taking much needed investment and job opportunities with opposing positions, no obvious compromise. Sign up for our Tech Decoded newsletter to follow the world's top tech stories and trends. Outside the UK? Sign up here.
Forbes
4 days ago
- Business
- Forbes
10 Steps To Corporate AI Adoption
Flat illustration of business people carry AI processing chip embracing artificial intelligence for ... More work success Last week, Shopify CEO, Tobi Lütke sent an email to all staff ordering them to prove they "cannot get what they want done using AI" before asking for extra hires. The email, extolling the virtues of AI adoption, came on top of reported layoffs of 14% in 2022, a further 20% in 2023, and 2.5% in December 2024. It set out a clear "AI first" manifesto requiring that staff train and use LLMs (Large Learning Models like Chat GPT) in their daily work, put AI at the heart of software development, and have AI usage and competence included in performance reviews. No doubt, Tobi's intention was to set a new reality for the firm, encouraging people to embrace AI. But put yourself in the shoes of the average Shopify employee—how inspired and enthusiastic might you feel reading this email? When people have been thinking and doing things in a particular way over and over for years, organizational practices, cultural norms, processes, methods, and structures become deeply ingrained in their brains as part of their "mental model of the world." Neural pathways form and a sort of tribal addiction ensues. Brains crave safety and consistency because learning new ways is metabolically expensive, and the brain has plenty to do without managing yet another new challenge. So when the brain is confronted by dramatic change, its first reaction is to say "no" and try to avoid the change—because it's much easier to keep doing things the way they've always been done. Right now, most brains that read the press, engage with social media, or watch TV have been given the impression that AI is a worrisome technology that might even take their jobs away. So the brain's reaction is to reject and resist. I suspect the brains at Shopify will now be in total resistance mode because Tobi's email will have created an existential threat in the minds of company employees, making his laudable ambition much harder to achieve. In my article Corporate AI Adoption May Fail If Education Doesn't Keep Up, I suggested that AI isn't a technology challenge—it's a culture and behavioral challenge. In this article, I've set out 10 people-centric steps for achieving mass adoption of AI across an organization safely, securely, efficiently, and quickly. These steps help every brain come to terms with a new reality while generating enthusiasm and support. They're based on 40 years of managing changes in workplace behavior and a recent study I directed involving leading companies from various sectors that examined AI's impact on jobs and organizational structures. Miss out on any one of these steps, and the journey to maturity gets longer and trickier. Here they are: Get top leaders must come together to align on what AI is and what it means for the organization. They must define whether AI is primarily for competitive advantage, operational efficiency, customer experience, or workforce augmentation, and create a compelling vision for AI. Address fundamental questions about cultural fit, risk tolerance, and organizational values. This shared vision becomes the North Star that guides all subsequent decisions and communications. Make a credible leader responsible for AI transformation at the C-suite level. Develop a powerful steering group and provide a program management office with the skills and influence to build and manage a cross-disciplinary change program that addresses skills, attitudes, behaviors, education, processes, legal issues, risks, and security. Evaluate whether your culture supports the transparency, experimentation, and iterative learning that AI requires. Identify cultural and skills barriers that could undermine AI adoption and plan how to address them. This includes understanding existing skills, power structures, decision-making processes, and how change has been received historically. Assess current roles, organizational structures, and capabilities alongside potential AI applications. Identify which positions will be eliminated, transformed, or enhanced. Create honest, transparent and consistent messaging about AI's role in your organization's future. Address fears directly rather than avoiding them. Explain the "what," "why," "how," "when," and "who" of AI adoption and what it means for individual employees. Ensure all leaders undergo AI training and can communicate the same message to prevent confusion and mistrust. Develop a list of "tricky questions" with associated answers to address the awkward questions people will ask. Consistency, honesty, and fairness are key. Develop an engagement and change program that is the cornerstone of your change program not a bolt on PR campaign. Find employees across all levels of the organization who have the skills and enthusiasm to become AI advocates within their teams—then train and nurture them. These champions bridge the gap between leadership vision and ground-level reality. They're the people who will get asked the questions their colleagues don't dare ask those in power. Invest in their development, maintain them as a special community, and give them platforms to share experiences and address concerns from their peers. For those with a technical bent, give them deeper "prompt engineering" skills and knowledge so they can become "super users" who train colleagues and new recruits and develop local apps to address micro-process challenges. Computer, black woman and manager training intern or coaching employee and helping with project, ... More work or collaboration. Mentor, corporate and talking about a question, error or pc learning in Nigeria McKinseys "Generative AI and the future of work in America" report suggests that by 2030 as many as 30% of the hours worked by US workers will be replaced by AI. It's critical therefore that training and support is provided to upskill every employee so they understand what AI is (and isn't) and feel confident and competent using core AI tools like LLMs (Large Language Models like ChatGPT, Gemini, Claude, etc.). By doing this, you remove some of the fear as people become familiar and skilled. New roles in IT, HR, and Legal will need to be defined, and new career development routes will need to be considered in an AI-enhanced organizational model. Use champion networks and teams to identify "use cases"—situations where AI can be applied to deliver immediate improvements in effectiveness. Start with AI applications that clearly augment rather than replace human capabilities. Choose initial projects that solve real problems employees face and make their work more interesting or valuable. Success here builds acceptance and enthusiasm for more advanced implementations. Create policies that ensure AI systems remain transparent, ethical, and under human control. Include diverse perspectives in governance decisions, especially from employees who will work directly with AI systems. This framework must address both technical and cultural concerns about AI decision-making and bias. Launch carefully selected pilot projects that demonstrate AI value while building organizational capability. Combine technical implementation with intensive change management support, putting people at the heart of the program. Create feedback mechanisms that capture both technical performance and human experience. Make sure you document these with diaries and videos, and create video testimonials based on outcomes. Expand AI implementation based on lessons learned. Continue investing in workforce development and cultural adaptation. Regularly reassess and adjust your approach based on organizational learning and evolving AI capabilities. Remember that unlike other change programs you may have been involved in, this one doesn't have an end because AI is constantly evolving. New developments will come quickly that may make your existing implementations redundant faster than you'd imagine. Perpetual change management is the new name of the game. By adopting these 10 steps, you'll have a greater chance of harnessing the energies and enthusiasm of your people, removing misunderstandings, and working with the brain's natural resistance to change. While AI adoption is underpinned by deep technology, the rewards will only be reaped by treating it as an organizational and behavioral change program.
