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TECHx
25-07-2025
- Business
- TECHx
Artificial Intelligence Isn't the Magic We Think It Is
Home » Editor's pick » Artificial Intelligence Isn't the Magic We Think It Is It began with a simple click. An employee opened an email. It looked normal. A trusted supplier's invoice. But this message was crafted by artificial intelligence. Not by a human. Minutes later, the company's systems were compromised. This is the reality of artificial intelligence in 2025. It powers innovation and creativity. Yet, it also challenges our security and trust. Across industries, artificial intelligence is transforming how work gets done. According to a 2024 survey, 78 percent of organizations now regularly use AI to boost productivity and decision-making. That's nearly double compared to just a year earlier. Spending on artificial intelligence is skyrocketing too. IDC forecasts that global AI investments will exceed hundreds of billions by the end of 2025. In the Middle East and Africa, AI-related spending is expected to nearly triple from 4.5 billion dollars in 2024 to over 14 billion dollars by 2028. This surge reflects the growing belief that artificial intelligence drives business growth and competitive advantage. PwC estimates AI could add 15.7 trillion dollars to the global economy by 2030. The Middle East alone stands to gain about 320 billion dollars from this shift. However, growth brings challenges. Rapid AI adoption raises questions about ethics, transparency, and human impact. For instance, Stanford's AI Index warns about the environmental footprint and bias risks in large AI models. As a result, organizations are adopting smarter AI governance. They focus on clear policies, responsible deployment, and continuous oversight. In fact, IDC highlights that most AI spending in 2025 will be embedded in existing products and platforms, not standalone systems. This makes governance even more critical. Talent dynamics are changing as well. PwC's 2025 AI Jobs Barometer reveals a surge in demand for AI-fluent roles and hybrid skill sets. Artificial intelligence is reshaping labor markets, creating new opportunities while redefining job roles. So, how do leaders succeed in this fast-evolving landscape? First, measure AI's impact on people, not just technology. Track improvements in work quality, decision-making, and employee wellbeing alongside technical metrics. Second, build AI frameworks that empower users and ensure transparency. Use plain language policies, robust escalation paths, and tools to detect unintended AI use. Third, align AI strategies with local priorities. In the Middle East, this means tapping into national AI initiatives, talent programs, and infrastructure investments. We spoke with Peter Oganesean, Managing Director of Middle East and East Africa at HP, about this pivotal moment. He said: 'In 2025, AI is no longer a futuristic concept, it's a tangible driver of transformation across the region and beyond. At HP, we see AI not as a replacement for human potential, but as a powerful catalyst for it, enabling personalized work experiences, fostering deeper collaboration, and empowering businesses to innovate responsibly. The real story of AI today lies in its ability to balance high-performance technology with sustainable, human-centric impact.' His insight reminds us that artificial intelligence is not just about automation or speed. It is about human-centered innovation and responsible growth. The email at the start was a failure of process, not just technology. The future belongs to organizations that design AI for trust, security, and positive impact. Artificial intelligence is cool, but it's not magic. It's only as good as the people building and using it. If we go all in on speed and power without thinking about the impact, we'll miss the point. The real win is finding that sweet spot where AI makes life easier, businesses smarter, and society better, without losing sight of the humans at the center of it all.
Yahoo
27-06-2025
- Business
- Yahoo
Mondelēz demystifies AI-powered coding gains
This story was originally published on CIO Dive. To receive daily news and insights, subscribe to our free daily CIO Dive newsletter. As Mondelēz International embarked on a sizable systems overhaul, the snack maker was looking for ways to alleviate burdens on its tech team and developers. 'With all the things we've been doing, finding ways to speed up and make [engineers] more agile and give them capabilities was a No. 1 priority,' Sean Tibor, director of global cloud engineering at Mondelēz, told CIO Dive. A coding assistant fit the bill. Tibor gave developers access to Amazon Q, a generative AI-powered assistant, 'as early as I possibly could, to be honest.' Since embedding the tool in engineering workflows, Mondelēz shortened its development cycles and new hires began using it as a learning resource. Mondelēz measures the tool's value in three parts: quantitatively, qualitatively and anecdotally. 'We are set up well to encourage adoption, and then we've got the feedback loop on the metrics to be able to see what they're actually using it for and that we're getting the value out of the spend that we're putting into,' Tibor said. Enterprises have tied more development practices to AI as engineers have embraced coding assistants and the technology has improved. In one benchmark, AI systems solved nearly 72% of coding problems in 2024, compared to just 4.4% in 2023, according to the Stanford Institute for Human-Centered AI's latest AI Index report published in April. Mondelēz developers have free rein to use Amazon Q across any project in the company's environment. An internal AI review board helped make the decision after ensuring that teams could use encryption keys to manage data, monitor usage and disable training for outside use cases. 'We've done a major migration from legacy data centers over to the cloud, and this is wave three of cloud migrations for Mondelēz,' Tibor said. 'What we've been migrating over has been a lot of the most difficult legacy systems to bring over and finding new ways to modernize and run those workloads at scale.' In addition to code creation, engineers ask Q to validate and test code generated by the tool or a human. 'They've seen a speed up, not just in generating code, but in validating the code before it goes into our development,' Tibor said. The AI tool has also sped up server provisioning, which used to take seven to ten days. Fully compliant servers are now ready in about 20 minutes, said Tibor. Like most other enterprises, Mondelēz has grappled with tech talent woes. Skill gaps can threaten project momentum and have been blamed for hours wasted and exacerbated inefficiencies. A dearth of talent also puts pressure on existing staff. Tibor said it can be difficult to recruit and onboard cloud engineers into the company's environment in an agile way. 'It's a very high-demand job internally within our organization,' Tibor said. 'We found that we can use Q not just as a way to write code, but also to act as a tutor so that they can learn more about the services and offerings through chat capabilities.' Previously, developers might have had a question for a senior member of the team and had to wait for a response, which could slow down processes, given the organization's global nature. 'That senior engineer might still be asleep,' Tibor said. 'It's cut down that cycle time for learning and made iteration a lot faster, which has been exciting to see everyone taking advantage of, especially with our new hires onboarding.' Skill gaps can also push employees to try and find their own solutions, leading to problems down the line, like shadow IT. 'By offering a high-quality coding assistant, it kind of removed the desire for them to go get things like Copilot, which we're not using,' Tibor said. 'We're still very mindful of the security aspects of it and make sure that what we're doing is appropriate.' AI-powered productivity pushes can lead to unintended outcomes, such as degraded quality and security implications. Guardrails and security are crucial with output expectations on the rise as more than two-thirds of developers say AI tool adoption has put pressure on them to deliver on projects faster, according to a HackerRank report. 'Culture makes a huge difference,' Tibor said. 'I'm really proud of the engineering team, and they are highly accountable and trustworthy. They want to do the right thing, and when they look at coding, they're assessing it on the same rubric that I am, which is: how much is this helping me versus how much is this creating further problems and code integrity issues.' Recommended Reading How Mondelēz laid the groundwork for a major digital overhaul Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
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.
Yahoo
09-06-2025
- Business
- Yahoo
Corporate AI adoption may be leveling off, according to Ramp data
A healthy chunk of corporate America has eagerly embraced AI, betting the tech will bring unrealizable productivity gains. But adoption may be leveling off, according to transaction data from fintech company Ramp. Ramp's AI Index, which estimates the U.S. business adoption rate of AI products by drawing on Ramp's card and bill pay data, leveled off at 41% in May after close to 10 straight months of growth. As of May, 49% of large businesses had deployed AI in some form compared to 44% of medium-sized firms, and 37% of small companies, according to Ramp. Ramp's AI Index isn't a perfect measure. It only looks at a sample of corporate spend data from around 30,000 companies. Moreover, because the index identifies AI products and services using merchant name and line-item details, it likely misses spend lumped into other cost centers. But it's certainly true that businesses are beginning to realize that there's a limit to what today's AI can do. Last month, Klarna, which said it would work to replace hundreds of support agents with AI, was forced to hire some workers back after the company's cuts led to "lower quality" customer service. According to S&P Global, the share of companies abandoning most of their generative AI pilot projects has risen to 42%, up from 17% last year. This article originally appeared on TechCrunch at Sign in to access your portfolio
Fast Company
05-05-2025
- Business
- Fast Company
To realize AI's potential in the workplace, do one thing
The Fast Company Impact Council is an invitation-only membership community of leaders, experts, executives, and entrepreneurs who share their insights with our audience. Members pay annual dues for access to peer learning, thought leadership opportunities, events and more. In just a few short years, generative artificial intelligence has begun demonstrating its tremendous business potential. Stanford University's latest AI Index report reveals that global corporate investment in AI grew nearly 45% in 2024 to reach $252.3 billion. With private investment in generative AI up 8.5 times over 2022 levels, forecasts suggest that AI could soon contribute trillions of dollars to the American economy alone. By 2028, agentic AI, the next stage in AI's evolution, could be making at least 15% of day-to-day decisions at work and bring greater efficiency, productivity, and innovation. We're already seeing how AI is creating new businesses, products and services with the potential to expand access to new quality jobs and build new sources of wealth. Today, workers are using AI to inject creativity into their current jobs and start and grow their own businesses. Two-thirds of small businesses that use AI say their own employees are introducing AI tools to the workplace to improve operations, reduce costs and spark innovation. Many organizations are understandably focused on the near-term time- and cost-savings this emerging technology brings about. But pure efficiency won't unlock the true value of AI; that will require tapping into the expertise and creativity of their employees. To fully realize AI's potential to revolutionize our economy, we need to put workers at the center of the process of deciding where and how it shows up in the workplace. What does that look like in practice? AI training First, organizations should offer more AI training—from basic literacy to implementation. AI usage at work is surging, according to a new study from my team at JFF. Two years ago, only 8% of individuals used AI at work. Today, it's 35%. Those who use AI say AI is making them more efficient—and their jobs more interesting—by reducing the number of tedious tasks and allowing them to focus on more strategic and creative work. More training means more people experiencing these benefits and contributing to decision making around AI. Yet our survey also found wide training gaps. Fewer than one third (31%) of workers say their employers provide training on AI fundamentals or specific AI tools and systems. Slightly more than one third (34%) of employees not receiving AI training at work say they want their employer to offer it. This lack of access to training is creating barriers to the effective implementation of AI at work. Previous JFF research shows that nearly 60% of small businesses cited workforce readiness as the most common barrier to incorporating AI technology into their businesses. To overcome that barrier, organizations can start by providing affordable and practical AI literacy training that help employees learn how to get the most out of AI and become responsible users of this emerging technology. Employee-driven innovation Second, organizations should catalyze employee-driven innovation. Workers are already eager to use AI: according to JFF's recent survey, 20% of employees say they're taking the initiative to use AI at work in the absence of formal direction from their employers, while nearly 30% of workers are leveraging AI tools for strategic growth and innovation. There's a good business case to be made for bottom-up transformation. Research suggests that when workers are asked for their input, organizations are more likely to make effective use of AI tools and improve the quality of workers' jobs. To unlock growth using AI, businesses should involve their employees in piloting and deploying AI tools and processes across multiple roles and functions throughout an organization. Frontline employees—experts on their own workflows—are often in the best position to help improve and refine development of AI tools and processes. They're the ones companies should call on to find uses of AI that can create value and drive innovation. AI and human collaboration Finally, organizations should reconsider how their employees spend their time, the nature of the work they do, and their unique skills so they can unlock the best parts of collaboration between AI and humans. The immediate goal of AI implementation should be about enabling workers to prioritize work that creates new products, services and value that helps businesses grow. Collaboration between humans and AI has enormous potential. As a Harvard Business School working paper suggests, AI can help professionals significantly boost performance, expertise, and social connectivity in team settings. As AI becomes more capable of making its own decisions and completing complex tasks, humans will spend more time supervising AI, discerning and evaluating AI outputs, and managing interpersonal and collaborative activities with other humans. We've also seen that AI appears to significantly increase the value of human leadership in interpersonal and highly cognitive tasks like staffing organizations, building relationships, and guiding and motivating teams. Employers have an opportunity to prepare for this shift by designing high-quality jobs—and involving their workers in this process—that can get the best out of collaboration between humans and AI. The transformation of work is underway. Businesses seeking to navigate it should support employees in their earnest desire to develop AI literacy and skills, catalyze creativity and innovation throughout the organization, and intentionally redesign jobs to unlock the strengths of both AI and humans. Previous technological revolutions have shown that the benefits of progress are not distributed equally. But if companies keep their employees at the center, they can fulfill AI's potential as a force to expand access to quality jobs and economic opportunity for all.
