Latest news with #ArtificialIntelligenceIndexReport2025
Techday NZ
17-07-2025
- Business
- Techday NZ
Record investment & policy headline Stanford's AI report
The pace of progress in artificial intelligence has accelerated to historic highs, with breakthroughs in technical capabilities, adoption across sectors, and global governance, according to the latest Artificial Intelligence Index Report 2025 from Stanford University's Institute for Human-Centreed Artificial Intelligence (HAI). The eighth edition of the report describes 2024 as a pivotal year, marked by "unprecedented" leaps in AI performance, new records in private investment, and intensifying government involvement. "The 2025 Index is our most comprehensive to date and arrives at an important moment, as AI's influence across society, the economy, and global governance continues to intensify," write co-directors Yolanda Gil and Raymond Perrault in their introduction. "AI is no longer just a story of what's possible - it's a story of what's happening now and how we are collectively shaping the future of humanity." Record growth in performance and usage AI models continue to outperform previous benchmarks at a rapid rate. In the past year alone, performance rose by 18.8 percentage points on the MMMU benchmark, 48.9 points on GPQA, and 67.3 points on the SWE-bench, which tests advanced coding tasks. The report finds that "AI systems made major strides in generating high-quality video, and in some settings, language model agents even outperformed humans in programming tasks with limited time budgets." AI is also increasingly present in everyday life, particularly in healthcare and transportation. In 2023, the US Food and Drug Administration approved 223 AI-enabled medical devices, up from just six in 2015. Meanwhile, autonomous vehicle usage has scaled up: "Waymo, one of the largest US operators, provides over 150,000 autonomous rides each week, while Baidu's affordable Apollo Go robotaxi fleet now serves numerous cities across China." Investment and industry adoption surge Private investment in AI hit new highs in 2024. According to the report, "US private AI investment grew to $109.1 billion - nearly 12 times China's $9.3 billion and 24 times the UK's $4.5 billion. Generative AI saw particularly strong momentum, attracting $33.9 billion globally in private investment - an 18.7% increase from 2023." Business adoption of AI is also accelerating: "78% of organisations reported using AI in 2024, up from 55% the year before." The report cites research showing that "AI boosts productivity and, in most cases, helps narrow skill gaps across the workforce." The sector has experienced "dramatic expansion over the past decade, with total investment growing more than thirteenfold since 2014." Global leadership and competition While the US remains the leader in producing top AI models, China is rapidly closing the performance gap. In 2024, US-based institutions produced 40 notable AI models, compared to China's 15. However, "Chinese models have rapidly closed the quality gap: performance differences on major benchmarks such as MMLU and HumanEval shrank from double digits in 2023 to near parity in 2024," the report finds. China also leads in the number of AI research publications and patents, accounting for 69.7% of all AI patent grants in 2023. "Between 2010 and 2023, the number of AI patents has grown steadily and significantly, ballooning from 3,833 to 122,511. In just the last year, the number of AI patents has risen 29.6%," the authors note. Policy, regulation and public attitudes Governments are stepping up both investment and regulation. In 2024, US federal agencies introduced 59 AI-related regulations, more than double the number in 2023. Canada, China, France, India, and Saudi Arabia all announced major national AI investment packages, ranging from $1.25 billion to $100 billion. "Legislative mentions of AI rose 21.3% across 75 countries since 2023, marking a ninefold increase since 2016," the report states. Despite the optimism, trust and bias remain challenges. The report finds "fewer people believe AI companies will safeguard their data, and concerns about fairness and bias persist. Misinformation continues to pose risks, particularly in elections and the proliferation of deepfakes." In response, governments and international organisations are "advancing new regulatory frameworks aimed at promoting transparency, accountability, and fairness." A global survey in 2024 found notable regional divides in public optimism about AI. In China, Indonesia, and Thailand, more than 75% of respondents viewed AI as more beneficial than harmful, compared to just 40% in Canada and 39% in the United States. Still, optimism is rising: "Since 2022, optimism has grown significantly in several previously sceptical countries, including Germany (+10%), France (+10%), Canada (+8%), Great Britain (+8%), and the United States (+4%)." The path forward Looking ahead, the AI Index calls for continued vigilance, collaboration and data-driven policymaking. "In a world where AI is discussed everywhere - from boardrooms to kitchen tables - this mission has never been more essential," write the co-directors. "Longitudinal tracking remains at the heart of our mission. In a domain advancing at breakneck speed, the Index provides essential context - helping us understand where AI stands today, how it got here, and where it may be headed next."
Forbes
29-04-2025
- Business
- Forbes
How To 10x Your App Modernization Impact With AI Agents
AI is often viewed as the endpoint of a modernization journey, but what if organizations instead ... More viewed AI as a powerful accelerator to quickly begin seeing impacts from the latest tools and technologies? As businesses embrace AI and begin to see real impacts, app modernization has never been more urgent for organizations dragging their feet on getting started. Standford University's Artificial Intelligence Index Report 2025 found that 78% of organizations reported AI use in 2024, up from 55% the previous year. It concludes that 'AI has moved from the margins to become a central driver of business value.' Put bluntly: businesses that don't modernize will fall behind competitors, lose top talent and struggle to deliver a compelling customer experience. Yet many leaders feel stuck in place, unable to move forward with modernization initiatives for a myriad of fear-based reasons: The cost is too high; the process is too disruptive; the team isn't prepared to manage the technology; success feels too elusive. Gartner, for instance, found that less than half of digital initiatives meet or exceed their goals—a statistic that doesn't exactly inspire confidence. AI is often viewed as the endpoint of a modernization journey, but what if organizations viewed AI not as the final destination but rather as a powerful accelerator to quickly begin seeing impacts from the latest tools and technologies? My company, Centric Consulting, is experimenting with how AI can accelerate the modernization process, making it less expensive and less disruptive while delivering value much more quickly. Our efforts focus on two key areas of code modernization: migrating code from legacy systems and evaluating business test requirements. Migrating code from legacy systems: We used a custom, enterprise-class AI agent framework to analyze an existing legacy code base, documenting how the code works to understand how it's been supporting the business or use case. Without AI, this process can take a team weeks to accomplish. Using AI, the team achieved a 10x impact on productivity. Documenting legacy code is tedious work that must take place before an organization can even begin the migration process. Using AI to analyze and document the legacy code not only speeds up the process and makes it less costly, but it also frees employees to focus on the bigger, more interesting strategic problems of modernization and more quickly get to the meat of modernization work. AI can also accelerate the next steps of the process: deciding what coding language and architecture is best suited for the use case. AI can quickly compare the options and even offer an outline of an architecture and business feature roadmap, giving people a quick starting point to begin creating a more detailed, actionable plan. Evaluating AI readiness: We used a custom AI agent to evaluate over 40 hours of business stakeholder interviews to determine an organization's AI readiness. The agent analyzed the interviews, cataloging interview notes against assessment criteria. It also produced detailed reports, findings and recommendations, including an actionable roadmap for improving AI readiness and governance for the organization—all in a little over six hours. Without AI, this process would have taken a team weeks to accomplish. Then, the team used an AI agent to design new architectures, develop a plan based on the requirements and write new features with associated tests. What would have taken two developers months to complete, we were able to do in one week with a single architect. There's a potential to use AI for every step along the process of app modernization. When used appropriately, AI isn't a 10% or even a 20% multiplier—it can be a 10X multiplier, accelerating the app modernization process and solving timeline and cost challenges of modernization. That said, there are two important caveats for using AI for app modernization. One, AI is not 100% right all the time. Humans must remain in the loop, with frequent checkpoints designed into the process. It's important to note that AI should be viewed not merely as a tool but as an expertise multiplier. Humans play a vitally important role in ensuring AI has developed a consistent 'understanding' of its assigned tasks and providing expert guidance and correction along the way as needed. Two, an enterprise-class agent is going to produce the appropriate quality of outputs for app modernization work. An enterprise-class agent has clearly defined personas and tools and is able to maintain contextual awareness of the code. Comparatively, a generic AI coding assistant won't be able to handle the work—instead of the entire repository, it looks at only a few lines or a file of code at most and will likely produce lots of hallucinations. Many leaders fall into the trap of believing they need pristine conditions—all apps migrated to the cloud, data perfectly modernized and governed—before embracing AI. This mindset is not just limiting; it's potentially devastating to your competitive position. Consider the internet adoption curve of the late 1990s: companies like Amazon and eBay launched with imperfect platforms and messy backend systems, gaining irreplaceable market advantages while their competitors crafted 'perfect' digital strategies that never materialized in time. Walmart, despite its retail dominance, waited until 2000 to launch a robust e-commerce platform—years behind Amazon's 1995 start—a delay that created a competitive gap they're still working to close decades later. The stark reality? No organization's data is truly AI-ready. Those waiting for perfect conditions are standing still while competitors race ahead. When it comes to modernization, adopt the mantra "Progress over perfection." The mountain of legacy challenges may be high, but scaling it incrementally with AI as your climbing gear yields immediate returns. Begin extracting value now, even as you acknowledge greater treasures await once your data foundation is strengthened. Remember, while AI will not replace your app modernization strategy, organizations using AI to accelerate their modernization will replace organizations who don't. The AI revolution waits for no one—and the modernization journey you begin today, however imperfect, will create the competitive advantage you'll need tomorrow.
