Latest news with #ErikBrynjolfsson
Telegraph
03-08-2025
- Business
- Telegraph
The AI revolution is here to make you stupid
Despite the downsides, AI offers a seductive promise to companies driven by bottom lines: cost-cutting. Yet what may flatter the balance sheet in the short-term could cost them in future. 'Managers tend to systematically underestimate the expertise needed to do the work of their employees, meaning that they may classify more work as replaceable or deskilled than is appropriate,' one metastudy led by Professor Kevin Crowston of Syracuse University cautioned. In seven cases studied by Crowston where AI had been used, six experienced some deskilling, even alongside upskilling and efficiency gains. An examination of call centre staff in the study Generative AI At Work led by Erik Brynjolfsson showed greater gains amongst the lower skilled, penalising the higher skilled. If managers are metric-obsessed, they'll be tempted to dispense with the skilled staff quicker. Once again, the firm deploying the AI becomes less capable and more stupid. In a widely circulated essay that went viral this spring, called The Co-Pilot Delusion, a highly skilled software developer described his experience with an AI assistant he knew was deeply flawed. 'I got lazy. Of course I did,' he confessed. 'When the system forces you to code with a hallucinating clown, eventually you stop resisting. You let him type. You let him be 'productive'. You check out. You surrender your brain to the noise and just float.' Warp speed warning So what to do? In Forster's story, when The Machine glitches people are so in awe of it that they treat the issues not as a crisis but as divine wisdom. They've turned it into a deity. Are we doing the same with generative AI? The novelist Ewan Morrison, whose new thriller For Emma revolves around a fatal AI experiment, thinks so. 'I think we in our naivety have bought into all the hype,' he says. 'But integrating AI into healthcare, the military and education means introducing something with an error rate of between 33pc and 90pc. The Government is introducing factual errors into everything it touches.' Such warnings are falling on deaf ears. Tech companies are in a hurry and have found a willing servant eager to do their bidding in the Labour Government. AI will cut waiting times, identify bottlenecks and even make services 'feel more human', the Government claims in its AI Action Plan. We have even been told that the technology can stop prison riots before they even start, such is its omniscient power. MIT's Kosmyna is sceptical. 'Generative AIs do not show objectively any gain in productivity, any gain in scientific discovery or any gain in employee performance – but we are told we have to implement them in such an aggressive manner,' she says. 'What are we afraid of missing out on, exactly?' While Britain is embracing AI at warp speed, there is a healthier scepticism in Asia than in the technocrat-driven West. 'Tony Blair has been convinced there's a ghost in the machine, but the Chinese, and in Singapore, they don't believe that for one minute,' says Georg Zoeller, a former Facebook engineer based in Singapore who advises governments and is also VP of technology at a healthcare start-up. He adds: 'Eighty per cent of decision makers and people crafting the laws in China are Stem [science, technology, engineering and mathematics] graduates who understand the technology, and the industry is being regulated by the best people, and they are integrated into both policy and technology.' James Woudhuysen, visiting professor of forecasting at South Bank University, agrees with Zoeller that the quality of our policy elites makes them more reluctant to assess societal and human harm. 'There are many more engineers in the upper echelons of Chinese society who understand technology, and understand what AI really is, than there are in Britain,' he says. 'The tendency to personalise or anthropomorphise AI, to see it as a constant and wise friend – that's a Blair legacy. They don't understand technology at all.' A decade ago, the Finnish accountants realised there was something precious in the corporate ether – the company's value was in its intangible knowledge capital. It could not be replicated by software, even if the daily tasks could be. Perhaps if we refuse to believe AI is magic, we'll be wiser about its obvious and not so obvious flaws. Unfortunately, policymakers in the West have been overtaken by a desire to make machines seem magical. If we're getting dumber, then we can hardly blame the AI for that. We've done it to ourselves.
Hindustan Times
21-07-2025
- Business
- Hindustan Times
How AI agents could reshape the economy
Imagine a world where your digital assistant not only schedules meetings and books trips but also negotiates with dozens of businesses on your behalf, finding the best prices, customising services, and handling payments in seconds. This isn't science fiction. It's the emerging reality of what experts call the agentic economy, powered by generative AI. AI(REUTERS) Already, research from leading economists shows that these technologies are transforming productivity. A recent large-scale field experiment published in the Journal of Econometrics by Erik Brynjolfsson, Danielle Li, and Lindsey Raymond found that generative AI significantly boosts the output of knowledge workers, especially helping less-experienced employees reach the performance levels of their more seasoned peers. This real-world evidence offers a glimpse into how AI might not only make individuals more efficient but also help narrow skill gaps in the workforce. The concept of the agentic economy goes beyond individual productivity. As explored in a study by researchers at Microsoft Research, AI is poised to reduce the friction of communication between consumers and businesses. Instead of painstakingly filling out forms or explaining your situation repeatedly to different service providers, your assistant agent could securely transmit your preferences and history to business-side service agents, instantly tailoring offers to your needs. This could unlock entirely new options that were previously buried under cumbersome processes. For instance, switching accountants or trying a new insurer might become as easy as a short prompt to your AI assistant, who negotiates terms with multiple providers in real time. Such advances could dramatically alter who holds power in the digital economy. Today, giants like Amazon, Google, and Meta act as middlemen—platforms that set rules, curate experiences, and take commissions by bringing together millions of buyers and sellers. But if AI agents on both sides can communicate directly, the need for these costly intermediaries may shrink. Consumers' assistant agents could interact directly with businesses' service agents, comparing prices, customizing bundles, and even resolving disputes. This would foster a more decentralized, competitive market landscape. Still, experts caution that platforms often provide more than just matchmaking. They add value through validation, fraud prevention, and standardised experiences. As a result, we may see platforms evolve rather than disappear, competing fiercely in a market with much lower switching costs. Perhaps the most critical question is whether this agent-driven economy will flourish inside closed ecosystems, agentic walled gardens, or thrive in an open web of agents. Large tech companies are already taking steps to build their own controlled agent marketplaces. Meta, for example, recently launched business service agents on Facebook and Instagram that only work within their platforms. This model can ensure quality and security, but risks consolidating power in the hands of a few players, potentially stifling innovation and fragmenting the user experience. Conversely, an open agent ecosystem would resemble today's world wide web, where any consumer's agent could connect with any business's agent. This would democratise access and spur competition—but would require global cooperation on technical standards, along with robust systems for trust and security. AI agents could also revolutionise advertising. Right now, businesses pay to capture our attention. In an agentic economy, attention may be less scarce; instead, algorithms matching consumer assistants with service agents become the critical battleground. Paid prioritisation will likely remain in some form, but the true driver of success could be human feedback. As Brynjolfsson and his colleagues found, AI tools are most effective when they learn from high-quality user interactions. In the future, businesses may compete to attract early users whose feedback helps train smarter systems, shifting us from an attention economy to a preference economy. Imagine paying small amounts to access only what you need—whether it's a custom-tailored news article that skips what you've already read or a playlist dynamically mixed across streaming platforms. As assistant agents seamlessly handle transactions, micro-payments that once seemed impractical could become commonplace. This also sets the stage for extreme unbundling and rebundling of products. Assistant agents might pull from multiple content or service sources to build hyper-personalised offerings, negotiating micro-transactions behind the scenes. We stand at a pivotal moment, much like the dawn of the internet in the 1990s. Whether this next wave of AI delivers widespread opportunity or concentrates power even further depends on decisions made now by tech leaders, regulators, and consumers alike. The evidence is already here: From field experiments proving how AI boosts worker productivity to new frameworks enabling agents to communicate on our behalf. As we step into this agentic future, we must carefully choose the architecture of our digital economy because it will determine who benefits from this revolutionary technology. Generative AI is not just about personal productivity; it's about reshaping how markets work. Whether we end up in walled gardens controlled by tech giants or a vibrant, open web of competing agents will decide if this new economy truly serves us all. This article is authored by Narinder Kumar, assistant professor, RV University), Amit Kumar, research scientist, PGIMER, Chandigarh and Kiran Sood, professor, Chitkara University, Punjab.
&w=3840&q=100)
Business Standard
05-06-2025
- Business
- Business Standard
Tech firms must embrace AI fast or risk falling behind: KPMG report
The artificial intelligence (AI) boom is here, and tech companies need to act fast or risk losing competitive advantage, according to a recent report by KPMG International. According to The Intelligent Tech Enterprise report, while expectations and spending around AI are soaring, many tech firms around the world have yet to unlock the full value of their investments. The study surveyed 1,390 executives globally, including 183 from the tech sector, and drew on over 500 AI engagements conducted by KPMG. It found that while 88 per cent of technology leaders believe AI adoption is crucial for competitive advantage, only 47 per cent are currently seeing significant returns. Shareholder pressure is mounting, with 62 per cent of tech firms under increasing demand to deliver immediate results. Yet, even AI front-runners are struggling to scale their efforts effectively. Many companies lack a coherent AI strategy, the necessary infrastructure, or mechanisms to build trust in AI systems. Only 27 per cent reported having a 'transformational AI vision', and just 20 per cent have fully integrated AI into their broader business strategy. 'AI is triggering the biggest transformation wave the economy has ever seen. You want to be on the right side of that,' said Stanford professor Erik Brynjolfsson, who contributed to the report. AI opportunities remain untapped The report estimates the potential value of AI for 832 public tech companies at over $178 billion annually. This represents up to 16 per cent of earnings before interest, taxes, depreciation, and amortisation (Ebitda) for some firms, particularly in areas like customer analytics, operations execution and code generation. Still, KPMG noted a significant gap between what's possible and what's being achieved. While 70 per cent of respondents reported cost savings from AI, and 47 per cent cited high returns, challenges persist. Common barriers include data privacy concerns, talent shortages, and limited AI literacy across organisations. Just 44 per cent have clear plans for scaling AI or tracking its performance. 'This is likely to be the largest organisational change most firms will face,' the report states. 'You need a clear plan—and the courage to execute it.' India's tech sector ready to leap India's tech sector is ready to accelerate its AI adoption, according to Purushothaman KG, Partner and Head of Technology Transformation at KPMG in India. 'Eighty-one per cent of Indian tech firms plan to embed AI into products and services over the next year,' he said, highlighting the importance of strong governance, skilled talent and deep operational integration. With 63 per cent of Indian firms planning to increase AI spending by more than 10 per cent, the country has the potential to redefine its global competitiveness in the AI era. What should tech leaders do? To help tech companies close this gap, KPMG recommends five key actions: Develop a clear AI strategy with a solid business case and roadmap that can evolve as technology and markets change. Build trust in AI by using ethical frameworks, transparency tools, and systems that explain how decisions are made. Make products smarter by designing them with AI from the start and constantly improving them based on user feedback. Upgrade tech infrastructure, especially with intelligent cloud services and edge computing that bring data closer to where AI models run. Embed AI in day-to-day operations and encourage teams and customers to adopt and work with AI solutions. Grow with AI: Enable, embed, evolve The report also lays out a three-phase roadmap for companies looking to grow with AI:
Mint
26-04-2025
- Business
- Mint
Companies are struggling to drive a return on AI. It doesn't have to be that way.
AI adoption among companies is stunningly high, but most of them are struggling to put it to good use. They intuit that AI is essential to their future. Yet intuition alone won't unlock the promise of AI, and it isn't clear to them which key will do the trick. As of last year, 78% of companies said they used artificial intelligence in at least one function, up from 55% in 2023, according to global management consulting firm McKinsey's State of AI survey, released in March. From these efforts, companies claimed to typically find cost savings of less than 10% and revenue increases of less than 5%. While the measurable financial return is limited, business is nonetheless all-in on AI, according to the 2025 AI Index report released in April by the Stanford Institute for Human-Centered Artificial Intelligence. Last year, private generative AI investment alone hit $33.9 billion globally, up 18.7% from 2023. The numbers reflect a 'productivity paradox," in which massive improvements in AI capabilities haven't led to a corresponding surge in national-level productivity, according to Stanford University economist and professor Erik Brynjolfsson, who worked on the AI Index. While some specific projects have been enormously productive, 'many companies are disappointed with their AI projects." For companies to get the most out of their AI efforts, Brynjolfsson advocates for a task-based analysis, in which a company is broken down into fine-grained tasks or 'atomic units of work" that are evaluated for potential AI assistance. As AI is applied, the results are measured against key performance indicators, or KPIs. He co-founded a startup, Workhelix, that applies those principles. Companies should take care to target an outcome first, and then find the model that helps them achieve it, says Scott Hallworth, chief data and analytics officer and head of digital solutions at HP. A separate report from McKinsey issued in January helps explain why AI adoption is racing ahead of associated productivity gains, according to Lareina Yee, senior partner and director at the McKinsey Global Institute. Only 1% of U.S. companies that have invested in AI report that they have scaled their investment, while 43% report that they are still in the pilot stage. 'One cannot expect significant productivity gains at the pilot level or even at the company unit level. Significant productivity improvements require achieving scale," she said. The critical question then, is how companies can best scale their AI efforts. Ryan Teeples, chief technology officer of 1-800Accountant, agrees that 'breaking work into AI-enabled tasks and aligning them to KPIs not only drives measurable ROI, it also creates a better customer experience by surfacing critical information faster than a human ever could." The privately held company based in New York provides tax, booking and payroll services to 50,000 active clients, with a focus on small businesses. The company isn't a Workhelix customer. Additionally, he says, companies should look beyond individualized AI usage, in which employees use GenAI chatbots or AI-equipped productivity tools to enhance their work. 'True enterprise adoption…involves orchestration and scaling across the organization. Very few organizations have truly reached this level, and even those are only scratching the surface," he said. The use of AI at 1-800Accountant begins with an assessment of whether the technology improves the client experience. If the AI provides customers with answers that are as good, better or faster than a human, it's a good use case, according to Teeples. In the past, the company scheduled hourlong appointments with advisers who answered simple client questions, such as the status of their tax return. Now, the company uses an AI agent connected to curated data sources to address 65% of customer inquiries, with 30% arranging a call with a human. (The remaining 5% drop out of the inquiry process for various reasons.) The company uses Salesforce's Agentforce to handle customer inquiries and its Einstein platform for orchestration across 1-800Accountant's back end. Teeples said the company is saving money on the cost of human advisers. 'The ROI in this case was abundantly clear," he said. Orchestrating AI across the enterprise requires the right infrastructure, especially when it comes to data, according to Gabrielle Tao, senior vice president for data cloud at Salesforce. It is important, she said, to harmonize data, for example, by creating a consistent way to refer to business concepts such as 'orders" and 'transactions," regardless of the underlying data source. AI deployments should target tasks that are both frequent and generalizable, according to Walter Sun, global head of artificial intelligence at SAP. Infrequent, highly specific tasks such as a marketing campaign for a single event might benefit from AI, but applying AI to regularly occurring tasks will achieve a more consistent ROI, he said. Historically, it has taken years for the world to figure out what to do with revolutionary general-purpose technologies including the steam engine and electricity, according to Brynjolfsson. It isn't unusual for general-purpose models to follow a 'J-curve," in which there's a dip in initial productivity, as businesses figure things out, followed by a ramp-up in productivity. He says companies are beginning to turn the corner of the AI J-curve. The transformation may occur faster than in the past, because businesses—under no small amount of pressure from investors—are working to quickly justify the massive amount of capital pouring into AI. Write to Steven Rosenbush at
Trade Arabia
03-04-2025
- Business
- Trade Arabia
Aveva seals strategic partnerships at flagship US event
Aveva, a global leader in industrial software, driving digital transformation and sustainability, is announcing multiple new partnerships at its flagship event, Aveva World. Taking place this year in San Francisco, Aveva is partnering with data analytics group Databricks and cutting-edge material tracking and mobility solution provider Track'em to revolutionise industrial operations with a secure and open approach to data and AI. The strategic partnership with Track'em is aimed at helping deliver real time visibility and cost control in capital projects. Hosted from April 8 to 10, the three-day conference features over 160 global speakers including Stanford Professor Erik Brynjolfsson, CEO of Schneider Electric, Olivier Blum, and CEO of Archaea Energy, Starlee Sykes, as well as many other business leaders. The event includes over 150 breakout sessions across 12 industries, discussing how industrial intelligence is enabling companies to analyse, visualise, and contextualise their data to improve decision-making, build resilience, and enhance sustainability across the enterprise. Additionally, Aveva will be unveiling new portfolio capabilities as it looks to tackle pressing industry challenges within artificial intelligence, energy transition and digital transformation. Through innovations within generative AI for piping design, Aveva is accelerating design productivity, reducing project set-up time by 70%, and cutting installed costs by 15%. Aveva is also empowering users with AI-powered tools on the Connect platform, enabling smarter processing and summarising of large datasets, while boosting multi-site visibility with hybrid operations control. With seamless industrial AI deployment across the entire lifecycle, Aveva helps businesses minimise risk, maximise outcomes, improve energy management and rapidly drive value with greater speed and efficiency. "Aveva World 2025 will bring together customers and partners to discuss how radical collaboration can unlock innovation and drive sustainable value," remarked Rob McGreevy, the Chief Product Officer, Aveva. "Ahead of this year's event, we are announcing partnerships with Databricks and Track'em, demonstrating how working with experts in their respective fields further strengthens our product offerings and drives additional value for our customers," he stated. "By combining real-time tracking with digital project execution, Aveva and Track'em are paving the way for a smarter, more efficient, and cost-effective future in capital projects. Our partnership with Databricks can help bridge the gap between IT and OT through Artificial Intelligence (AI); unlocking new potential for data-driven decision-making," he added.
